diff --git a/docs/user_guide/00_liquid-handling/_liquid-handling.rst b/docs/user_guide/00_liquid-handling/_liquid-handling.rst
index 32ea5d7d564..3de4229f65b 100644
--- a/docs/user_guide/00_liquid-handling/_liquid-handling.rst
+++ b/docs/user_guide/00_liquid-handling/_liquid-handling.rst
@@ -24,3 +24,4 @@ Examples:
    moving-channels-around
    tutorial_tip_inventory_consolidation
    mixing
+   container_no_go_zones
diff --git a/docs/user_guide/00_liquid-handling/container_no_go_zones.ipynb b/docs/user_guide/00_liquid-handling/container_no_go_zones.ipynb
new file mode 100644
index 00000000000..ac98feeb720
--- /dev/null
+++ b/docs/user_guide/00_liquid-handling/container_no_go_zones.ipynb
@@ -0,0 +1,907 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "h4mxa2wu6t9",
+   "metadata": {},
+   "source": [
+    "# Container No-Go Zones\n",
+    "\n",
+    "> **Mode:** Simulation (`STARChatterboxBackend`) - no hardware required.\n",
+    ">\n",
+    "> **Topic:** Defining obstructed regions and automatic channel avoidance using `Container` no-go zones.\n",
+    ">\n",
+    "> **Extra dependencies** (not included in pylabrobot):\n",
+    ">   - `matplotlib` - used for cross-section visualizations in this tutorial only\n",
+    "\n",
+    "---\n",
+    "\n",
+    "## What are no-go zones?\n",
+    "\n",
+    "Some containers have internal obstructions - divider walls, support beams, baffles - where pipette tips physically cannot go. When multiple channels target the same container (e.g. aspirating from a trough with 4 channels), `LiquidHandler` needs to know where these obstructions are to position tips safely.\n",
+    "\n",
+    "A **no-go zone** is a cuboid region inside a container, defined as a `Tuple[Coordinate, Coordinate]` - the front-left-bottom and back-right-top corners, relative to the container's origin.\n",
+    "\n",
+    "## How it works\n",
+    "\n",
+    "When `LiquidHandler.aspirate` or `.dispense` targets a single container with multiple channels:\n",
+    "\n",
+    "1. The container's Y axis is split into **compartments** (free space between no-go zones)\n",
+    "2. Each compartment is shrunk by `edge_clearance` (default 2mm) from each boundary\n",
+    "3. Channels are distributed across compartments **center-out, then back-first**\n",
+    "4. Each channel group is centered within its compartment\n",
+    "\n",
+    "```{note}\n",
+    "Single-channel operations are unaffected - the tip goes to the container center as usual.\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "v15b2poml7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Imports and visualization helper (collapse this cell in Jupyter via View → Collapse)\n",
+    "import matplotlib.pyplot as plt\n",
+    "import matplotlib.patches as mpatches\n",
+    "from matplotlib.lines import Line2D\n",
+    "\n",
+    "from pylabrobot.resources.container import Container\n",
+    "from pylabrobot.resources.coordinate import Coordinate\n",
+    "from pylabrobot.liquid_handling.utils import (\n",
+    "    _get_compartments,\n",
+    "    compute_channel_offsets,\n",
+    "    MIN_SPACING_EDGE,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "uan4wnlungq",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "MIN_CHANNEL_SPACING = 9.0  # mm, minimum center-to-center distance between adjacent channels\n",
+    "CHANNEL_DIAMETER = 9.0  # mm, minimum center-to-center spacing between adjacent channels\n",
+    "\n",
+    "def _draw_container_axis(ax, container, n_ch, spread=\"wide\", channel_spacings=None):\n",
+    "    \"\"\"Draw a single container cross-section with channels on the given axis.\"\"\"\n",
+    "    size_y = container.get_absolute_size_y()\n",
+    "    size_x = container.get_absolute_size_x()\n",
+    "    center_y = size_y / 2\n",
+    "    compartments = _get_compartments(container)\n",
+    "    label_bbox = dict(facecolor=\"white\", alpha=0.5, edgecolor=\"none\", pad=0.3)\n",
+    "    dist_bbox = dict(facecolor=\"white\", alpha=0.8, edgecolor=\"none\", pad=1)\n",
+    "\n",
+    "    # Container outline\n",
+    "    ax.add_patch(plt.Rectangle((0, 0), size_x, size_y, fill=False, edgecolor=\"black\", linewidth=2))\n",
+    "\n",
+    "    # No-go zones (red)\n",
+    "    for flb, brt in container.no_go_zones:\n",
+    "        ax.add_patch(plt.Rectangle((0, flb.y), size_x, brt.y - flb.y,\n",
+    "                                    facecolor=\"red\", alpha=0.3, edgecolor=\"red\", linewidth=1))\n",
+    "\n",
+    "    # Free compartments (green)\n",
+    "    for comp_lo, comp_hi in compartments:\n",
+    "        ax.add_patch(plt.Rectangle((0, comp_lo), size_x, comp_hi - comp_lo,\n",
+    "                                    facecolor=\"green\", alpha=0.1, edgecolor=\"green\",\n",
+    "                                    linewidth=1, linestyle=\"--\"))\n",
+    "\n",
+    "    # Channel positions\n",
+    "    try:\n",
+    "        kwargs = dict(spread=spread)\n",
+    "        if channel_spacings is not None:\n",
+    "            kwargs[\"channel_spacings\"] = channel_spacings\n",
+    "        offsets = compute_channel_offsets(container, n_ch, **kwargs)\n",
+    "        tip_ys = []\n",
+    "        for i, o in enumerate(offsets):\n",
+    "            tip_y = center_y + o.y\n",
+    "            tip_ys.append(tip_y)\n",
+    "            if channel_spacings is not None:\n",
+    "                d = channel_spacings[i]\n",
+    "            else:\n",
+    "                d = CHANNEL_DIAMETER\n",
+    "            ax.add_patch(plt.Circle(\n",
+    "                (size_x / 2, tip_y), d / 2,\n",
+    "                facecolor=\"none\", edgecolor=\"navy\", linewidth=1, linestyle=\":\"))\n",
+    "            ax.plot(size_x / 2, tip_y, \"o\", color=\"navy\", markersize=4, zorder=5)\n",
+    "            ax.text(size_x * 0.78, tip_y, f\"ch{i}\", ha=\"left\", va=\"center\",\n",
+    "                    fontsize=6, color=\"navy\", bbox=label_bbox, zorder=6)\n",
+    "\n",
+    "        tip_ys_sorted = sorted(tip_ys)\n",
+    "\n",
+    "        # Channel-to-channel distances (right side)\n",
+    "        brace_x = size_x + 2\n",
+    "        for i in range(len(tip_ys_sorted) - 1):\n",
+    "            y_lo = tip_ys_sorted[i]\n",
+    "            y_hi = tip_ys_sorted[i + 1]\n",
+    "            gap = y_hi - y_lo\n",
+    "            mid = (y_lo + y_hi) / 2\n",
+    "            ax.annotate(\"\", xy=(brace_x, y_hi), xytext=(brace_x, y_lo),\n",
+    "                         arrowprops=dict(arrowstyle=\"<->\", color=\"#444\", lw=1))\n",
+    "            ax.text(brace_x + 1, mid, f\"{gap:.1f}\", ha=\"left\", va=\"center\",\n",
+    "                    fontsize=7, color=\"#444\", fontweight=\"bold\", bbox=dist_bbox)\n",
+    "\n",
+    "        # Edge distances (left side)\n",
+    "        edge_x = -2\n",
+    "        for comp_lo, comp_hi in compartments:\n",
+    "            group = [y for y in tip_ys_sorted if comp_lo - 0.1 <= y <= comp_hi + 0.1]\n",
+    "            if not group:\n",
+    "                continue\n",
+    "            edge_lo = group[0] - comp_lo\n",
+    "            if edge_lo > 0.5:\n",
+    "                mid = (comp_lo + group[0]) / 2\n",
+    "                ax.annotate(\"\", xy=(edge_x, group[0]), xytext=(edge_x, comp_lo),\n",
+    "                             arrowprops=dict(arrowstyle=\"<->\", color=\"#888\", lw=0.8))\n",
+    "                ax.text(edge_x - 0.5, mid, f\"{edge_lo:.1f}\", ha=\"right\", va=\"center\",\n",
+    "                        fontsize=6, color=\"#888\", bbox=dist_bbox)\n",
+    "            edge_hi = comp_hi - group[-1]\n",
+    "            if edge_hi > 0.5:\n",
+    "                mid = (group[-1] + comp_hi) / 2\n",
+    "                ax.annotate(\"\", xy=(edge_x, comp_hi), xytext=(edge_x, group[-1]),\n",
+    "                             arrowprops=dict(arrowstyle=\"<->\", color=\"#888\", lw=0.8))\n",
+    "                ax.text(edge_x - 0.5, mid, f\"{edge_hi:.1f}\", ha=\"right\", va=\"center\",\n",
+    "                        fontsize=6, color=\"#888\", bbox=dist_bbox)\n",
+    "\n",
+    "    except ValueError:\n",
+    "        ax.text(size_x / 2, size_y / 2, \"Cannot fit!\", ha=\"center\", va=\"center\",\n",
+    "                fontsize=12, color=\"red\", fontweight=\"bold\")\n",
+    "\n",
+    "    ax.set_xlim(-8, size_x + 14)\n",
+    "    ax.set_ylim(-2, size_y + 2)\n",
+    "    ax.set_xlabel(\"X (mm)\")\n",
+    "    ax.set_aspect(\"equal\")\n",
+    "\n",
+    "\n",
+    "def plot_container_cross_section(container, num_channels_list, **kwargs):\n",
+    "    \"\"\"Plot container cross-sections for multiple channel counts.\"\"\"\n",
+    "    n_plots = len(num_channels_list)\n",
+    "    fig, axes = plt.subplots(1, n_plots, figsize=(2.2 * n_plots, 5), squeeze=False)\n",
+    "    axes = axes[0]\n",
+    "\n",
+    "    for ax, n_ch in zip(axes, num_channels_list):\n",
+    "        _draw_container_axis(ax, container, n_ch, **kwargs)\n",
+    "        ax.set_title(f\"{n_ch} channel{'s' if n_ch != 1 else ''}\")\n",
+    "        if ax != axes[0]:\n",
+    "            ax.set_yticklabels([])\n",
+    "        else:\n",
+    "            ax.set_ylabel(\"Y (mm)\")\n",
+    "\n",
+    "    legend_handles = [\n",
+    "        mpatches.Patch(facecolor=\"red\", alpha=0.3, edgecolor=\"red\", label=\"No-go zone\"),\n",
+    "        mpatches.Patch(facecolor=\"green\", alpha=0.1, edgecolor=\"green\", label=\"Free compartment\"),\n",
+    "        Line2D([0], [0], marker=\"o\", color=\"w\", markerfacecolor=\"none\", markeredgecolor=\"navy\",\n",
+    "               markersize=10, linestyle=\"None\", label=\"Tip diameter\"),\n",
+    "    ]\n",
+    "    fig.legend(handles=legend_handles, loc=\"lower center\", ncol=3, fontsize=8)\n",
+    "\n",
+    "    size_y = container.get_absolute_size_y()\n",
+    "    name = container.name\n",
+    "    model = container.model or \"\"\n",
+    "    fig.suptitle(f\"{name} ({model})\\nsize_y={size_y}mm, {len(container.no_go_zones)} no-go zone(s)\",\n",
+    "                 fontsize=11, fontweight=\"bold\")\n",
+    "    fig.tight_layout(rect=[0, 0.06, 1, 0.92])\n",
+    "    fig.subplots_adjust(wspace=-0.15)\n",
+    "    plt.show()\n",
+    "\n",
+    "\n",
+    "def plot_spread_comparison(container, n_ch, title=None, channel_spacings=None):\n",
+    "    \"\"\"Plot wide vs tight side-by-side for a single channel count.\"\"\"\n",
+    "    fig, axes = plt.subplots(1, 2, figsize=(8, 6), squeeze=False)\n",
+    "    axes = axes[0]\n",
+    "\n",
+    "    for ax, mode in zip(axes, [\"wide\", \"tight\"]):\n",
+    "        _draw_container_axis(ax, container, n_ch, spread=mode, channel_spacings=channel_spacings)\n",
+    "        ax.set_title(f'spread=\"{mode}\"')\n",
+    "        if ax != axes[0]:\n",
+    "            ax.set_yticklabels([])\n",
+    "        else:\n",
+    "            ax.set_ylabel(\"Y (mm)\")\n",
+    "\n",
+    "    if title is None:\n",
+    "        title = f\"{n_ch} channels on {container.name}: wide vs tight\"\n",
+    "    fig.suptitle(title, fontsize=11, fontweight=\"bold\")\n",
+    "    fig.tight_layout(rect=[0, 0, 1, 0.93])\n",
+    "    fig.subplots_adjust(wspace=-0.1)\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "nhdap5csut",
+   "metadata": {},
+   "source": [
+    "## Real-world examples: Hamilton troughs\n",
+    "\n",
+    "The Hamilton trough family has internal support structures that create no-go zones. These were measured from physical troughs using calipers (top of beams) and visual inspection through the transparent walls (base of tapered beams).\n",
+    "\n",
+    "### 60 mL trough - 1 center divider\n",
+    "\n",
+    "The `hamilton_1_trough_60mL_Vb` has a single center support wall (~1.2mm wide), creating 2 compartments."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "72t56n0fkzm",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Container: trough_60mL, size_y=90.0mm\n",
+      "No-go zones: [(Coordinate(x=0, y=44.4, z=5.0), Coordinate(x=19.0, y=45.6, z=60.25))]\n",
+      "Compartments: [(2.0, 42.4), (47.6, 88.0)]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1980x500 with 9 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pylabrobot.resources.hamilton.troughs import hamilton_1_trough_60mL_Vb\n",
+    "\n",
+    "trough_60 = hamilton_1_trough_60mL_Vb(name=\"trough_60mL\")\n",
+    "\n",
+    "print(f\"Container: {trough_60.name}, size_y={trough_60.get_absolute_size_y()}mm\")\n",
+    "print(f\"No-go zones: {trough_60.no_go_zones}\")\n",
+    "print(f\"Compartments: {_get_compartments(trough_60)}\")\n",
+    "\n",
+    "plot_container_cross_section(trough_60, [1, 2, 3, 4, 5, 6, 7, 8, 9])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "shj0sw6dkcg",
+   "metadata": {},
+   "source": [
+    "### 120 mL trough - 3 tapered support beams\n",
+    "\n",
+    "The `hamilton_1_trough_120mL_Vb` has 3 internal support beams (~2.5mm wide at the base, ~0.8mm at the top), creating 4 compartments. The no-go zones use the base width since that is the worst case for pipette tip clearance.\n",
+    "\n",
+    "Dimensional breakdown (from outer y=0):\n",
+    "\n",
+    "| Element | Y range (mm) | Size (mm) | Modelled as |\n",
+    "|---|---|---|---|\n",
+    "| Back wall | 141.1 - 142.5 | 1.4 | Not modelled (included in `size_y`) |\n",
+    "| Compartment 3 | 109.8 - 141.1 | 31.3 | Free space |\n",
+    "| Beam 3 | 107.3 - 109.8 | 2.5 | `no_go_zones[2]` |\n",
+    "| Compartment 2 | 76.0 - 107.3 | 31.3 | Free space |\n",
+    "| Beam 2 | 73.5 - 76.0 | 2.5 | `no_go_zones[1]` |\n",
+    "| Compartment 1 | 42.2 - 73.5 | 31.3 | Free space |\n",
+    "| Beam 1 | 39.7 - 42.2 | 2.5 | `no_go_zones[0]` |\n",
+    "| Compartment 0 | 1.2 - 39.7 | 38.5 | Free space |\n",
+    "| Front wall | 0 - 1.2 | 1.2 | Not modelled (included in `size_y`) |\n",
+    "\n",
+    "```{note}\n",
+    "size_y=142.5` is the **outer** dimension of the trough.\n",
+    "The front and back walls are not modelled as no-go zones - they are accounted for by the `edge_clearance` parameter during channel positioning.\n",
+    "\n",
+    "The internal beams *are* modelled as no-go zones because they obstruct pipette access within the container's interior.\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "20hbb649kmc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Container: trough_120mL, size_y=142.5mm\n",
+      "No-go zones: [(Coordinate(x=0, y=39.7, z=12.0), Coordinate(x=19.0, y=42.2, z=70.0)), (Coordinate(x=0, y=73.5, z=12.0), Coordinate(x=19.0, y=76.0, z=70.0)), (Coordinate(x=0, y=107.3, z=12.0), Coordinate(x=19.0, y=109.8, z=70.0))]\n",
+      "Compartments: [(2.0, 37.7), (44.2, 71.5), (78.0, 105.3), (111.8, 140.5)]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 2420x500 with 11 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pylabrobot.resources.hamilton.troughs import hamilton_1_trough_120mL_Vb\n",
+    "\n",
+    "trough_120 = hamilton_1_trough_120mL_Vb(name=\"trough_120mL\")\n",
+    "\n",
+    "print(f\"Container: {trough_120.name}, size_y={trough_120.get_absolute_size_y()}mm\")\n",
+    "print(f\"No-go zones: {trough_120.no_go_zones}\")\n",
+    "print(f\"Compartments: {_get_compartments(trough_120)}\")\n",
+    "\n",
+    "plot_container_cross_section(trough_120, [1, 2, 3, 4, 5, 6, 7, 8, 9, 12, 13])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d2prx1963mj",
+   "metadata": {},
+   "source": [
+    "## Defining no-go zones on a new container\n",
+    "\n",
+    "Any `Container` (or subclass: `Trough`, `Well`, `Tube`, etc.) accepts a `no_go_zones` parameter. Each zone is a pair of `Coordinate`s - the front-left-bottom and back-right-top corners of the obstructed cuboid, relative to the container's outer origin."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "zzzwi3r4vaf",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Container: custom_trough, size_y=100.0mm\n",
+      "Compartments: [(2.0, 28.0), (34.0, 63.0), (69.0, 98.0)]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1100x500 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pylabrobot.resources.trough import Trough, TroughBottomType\n",
+    "\n",
+    "# Define a custom trough with two dividers\n",
+    "custom_trough = Trough(\n",
+    "    name=\"custom_trough\",\n",
+    "    size_x=19.0,\n",
+    "    size_y=100.0,\n",
+    "    size_z=50.0,\n",
+    "    max_volume=80_000,\n",
+    "    bottom_type=TroughBottomType.V,\n",
+    "    no_go_zones=[\n",
+    "        (Coordinate(0, 30.0, 0), Coordinate(19.0, 32.0, 50.0)),  # divider 1\n",
+    "        (Coordinate(0, 65.0, 0), Coordinate(19.0, 67.0, 50.0)),  # divider 2\n",
+    "    ],\n",
+    ")\n",
+    "\n",
+    "print(f\"Container: {custom_trough.name}, size_y={custom_trough.get_absolute_size_y()}mm\")\n",
+    "print(f\"Compartments: {_get_compartments(custom_trough)}\")\n",
+    "\n",
+    "plot_container_cross_section(custom_trough, [1, 2, 3, 4, 6])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9ydm1lbbn8m",
+   "metadata": {},
+   "source": [
+    "## Edge clearance and tip size\n",
+    "\n",
+    "`edge_clearance` (default: `MIN_SPACING_EDGE = 2mm`) controls how close the automatic positioning places tip **centers** to compartment boundaries. It is a positioning safety margin, not a physical gate.\n",
+    "\n",
+    "It does **not** prevent a pipette from entering a container. Whether a tip physically fits is determined by tip diameter vs. container opening - e.g. a 1000 µL tip won't fit into a 1536-wellplate well. This is the **user's responsibility** to verify when choosing tips and containers."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "bee6v46lawm",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Container size_y: 20.0mm\n",
+      "No-go zone: Y=8-12mm -> two 8mm raw compartments\n",
+      "After 2mm edge clearance: compartments = [(2.0, 6.0), (14.0, 18.0)]\n",
+      "1 channel: [Coordinate(x=0, y=6.0, z=0)]\n",
+      "2 channels (1 per compartment): [Coordinate(x=0, y=6.0, z=0), Coordinate(x=0, y=-6.0, z=0)]\n",
+      "3 channels (needs 2 in one 4mm compartment): ValueError - Cannot distribute channels across compartments while respecting spacing constraints.\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 660x500 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# A narrow container where compartments are smaller than the default 9mm channel spacing.\n",
+    "# 1 channel per compartment still works - the channel is simply centered.\n",
+    "# 2 channels in one compartment would fail (needs 9mm, only 4mm available).\n",
+    "tiny = Container(\n",
+    "    name=\"tiny_container\", size_x=10, size_y=20, size_z=10,\n",
+    "    no_go_zones=[(Coordinate(0, 8, 0), Coordinate(10, 12, 10))],\n",
+    ")\n",
+    "print(f\"Container size_y: {tiny.get_absolute_size_y()}mm\")\n",
+    "print(f\"No-go zone: Y={8}-{12}mm -> two 8mm raw compartments\")\n",
+    "print(f\"After 2mm edge clearance: compartments = {_get_compartments(tiny)}\")\n",
+    "print(f\"1 channel: {compute_channel_offsets(tiny, 1)}\")\n",
+    "print(f\"2 channels (1 per compartment): {compute_channel_offsets(tiny, 2)}\")\n",
+    "try:\n",
+    "    print(f\"3 channels: {compute_channel_offsets(tiny, 3)}\")\n",
+    "except ValueError as e:\n",
+    "    print(f\"3 channels (needs 2 in one 4mm compartment): ValueError - {e}\")\n",
+    "plot_container_cross_section(tiny, [1, 2, 3])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "snfkeopew6",
+   "metadata": {},
+   "source": [
+    "## Spread modes with no-go zones\n",
+    "\n",
+    "The `spread` parameter on `aspirate` and `dispense` controls how channels are positioned within each compartment:\n",
+    "\n",
+    "- `spread=\"wide\"` (default) - channels are spread as far apart as possible within each compartment\n",
+    "- `spread=\"tight\"` - channels are packed at minimum spacing (9mm), centered in each compartment\n",
+    "- `spread=\"custom\"` - no-go zones are ignored entirely; the user controls all positioning via offsets"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "bbjg3lf6qa",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Compartments: [(2.0, 58.0), (63.7, 116.0)]\n",
+      "spread='wide'   -> offsets (from center): ['+43.9', '+30.9', '+17.8', '-15.0', '-29.0', '-43.0']\n",
+      "spread='tight'  -> offsets (from center): ['+39.9', '+30.9', '+21.9', '-20.0', '-29.0', '-38.0']\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Compare wide vs tight spread on the 200mL trough (2 large compartments, 6 channels)\n",
+    "from pylabrobot.resources.hamilton.troughs import hamilton_1_trough_200mL_Vb\n",
+    "\n",
+    "trough_200 = hamilton_1_trough_200mL_Vb(name=\"trough_200mL\")\n",
+    "print(f\"Compartments: {_get_compartments(trough_200)}\")\n",
+    "\n",
+    "for mode in [\"wide\", \"tight\"]:\n",
+    "    offsets = compute_channel_offsets(trough_200, 6, spread=mode)\n",
+    "    positions = [f\"{o.y:+.1f}\" for o in offsets]\n",
+    "    print(f\"spread={mode!r:8s} -> offsets (from center): {positions}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "yayka43i62",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_spread_comparison(trough_200, 6, title=\"6 channels on 200mL trough: wide vs tight\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "98rmf1z9e0c",
+   "metadata": {},
+   "source": [
+    "### Container without no-go zones\n",
+    "\n",
+    "`compute_channel_offsets` also works on plain containers. Without no-go zones, it falls through to standard wide/tight spread across the full Y axis."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "rp2rrixry2d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2-channel wide   -> ['+15.0', '-15.0']\n",
+      "2-channel tight  -> ['+4.5', '-4.5']\n",
+      "4-channel wide   -> ['+27.0', '+9.0', '-9.0', '-27.0']\n",
+      "4-channel tight  -> ['+13.5', '+4.5', '-4.5', '-13.5']\n",
+      "6-channel wide   -> ['+32.1', '+19.3', '+6.4', '-6.4', '-19.3', '-32.1']\n",
+      "6-channel tight  -> ['+22.5', '+13.5', '+4.5', '-4.5', '-13.5', '-22.5']\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1800x500 with 6 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# A plain trough without no-go zones\n",
+    "plain_trough = Trough(\n",
+    "    name=\"plain_trough\",\n",
+    "    size_x=19.0,\n",
+    "    size_y=90.0,\n",
+    "    size_z=65.0,\n",
+    "    max_volume=60_000,\n",
+    ")\n",
+    "\n",
+    "for n in [2, 4, 6]:\n",
+    "    for mode in [\"wide\", \"tight\"]:\n",
+    "        offsets = compute_channel_offsets(plain_trough, n, spread=mode)\n",
+    "        positions = [f\"{o.y:+.1f}\" for o in offsets]\n",
+    "        print(f\"{n}-channel {mode:6s} -> {positions}\")\n",
+    "\n",
+    "# Side-by-side: wide vs tight for 2, 4, 6 channels\n",
+    "channel_counts = [2, 4, 6]\n",
+    "n_pairs = len(channel_counts)\n",
+    "fig, axes = plt.subplots(1, n_pairs * 2, figsize=(3 * n_pairs * 2, 5), squeeze=False)\n",
+    "axes = axes[0]\n",
+    "\n",
+    "for pair_idx, n_ch in enumerate(channel_counts):\n",
+    "    for mode_idx, mode in enumerate([\"wide\", \"tight\"]):\n",
+    "        ax = axes[pair_idx * 2 + mode_idx]\n",
+    "        _draw_container_axis(ax, plain_trough, n_ch, spread=mode)\n",
+    "        ax.set_title(f'{n_ch}-channel \"{mode}\"')\n",
+    "        if pair_idx == 0 and mode_idx == 0:\n",
+    "            ax.set_ylabel(\"Y (mm)\")\n",
+    "        else:\n",
+    "            ax.set_yticklabels([])\n",
+    "\n",
+    "fig.suptitle(\"Plain trough (no no-go zones): wide vs tight\", fontsize=11, fontweight=\"bold\")\n",
+    "fig.tight_layout(rect=[0, 0, 1, 0.93])\n",
+    "fig.subplots_adjust(wspace=-0.05)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "qpv4b5xxlcq",
+   "metadata": {},
+   "source": [
+    "### Per-channel occupancy diameters\n",
+    "\n",
+    "Each channel has an occupancy diameter - the physical space it takes up. On a Hamilton STAR, 1mL channels have a 9mm occupancy diameter, while 5mL channels have 18mm. The required gap between two adjacent channels is the sum of their radii: `spacing[i]/2 + spacing[j]/2`.\n",
+    "\n",
+    "`compute_channel_offsets` accepts `channel_spacings` - one occupancy diameter per channel - and computes all gaps accordingly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "9wtrqbm2upq",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Compartments: [(2.0, 93.0), (107.0, 198.0)]\n",
+      "spread='wide'    centers=['24.8', '47.5', '70.2', '129.8', '152.5', '175.2']  gaps=[22.8, 22.8, 59.5, 22.8, 22.8]\n",
+      "spread='tight'   centers=['34.0', '43.0', '56.5', '139.0', '152.5', '166.0']  gaps=[9.0, 13.5, 82.5, 13.5, 13.5]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# 6 channels with mixed occupancy diameters on a wide demo trough\n",
+    "# 4 channels with 9mm occupancy (1mL), 2 with 18mm occupancy (5mL) - e.g. mixed Hamilton\n",
+    "mixed_spacings = [9.0, 18.0, 9.0, 18.0, 9.0, 9.0]  # 6 occupancy diameters for 6 channels\n",
+    "\n",
+    "# Create a wider trough to clearly show the difference between wide and tight\n",
+    "demo_trough = Trough(\n",
+    "    name=\"demo_trough\",\n",
+    "    size_x=37.0,\n",
+    "    size_y=200.0,\n",
+    "    size_z=95.0,\n",
+    "    max_volume=200_000,\n",
+    "    bottom_type=TroughBottomType.V,\n",
+    "    no_go_zones=[\n",
+    "        (Coordinate(0, 95, 0), Coordinate(37.0, 105, 95.0)),  # center divider\n",
+    "    ],\n",
+    ")\n",
+    "print(f\"Compartments: {_get_compartments(demo_trough)}\")\n",
+    "\n",
+    "for mode in [\"wide\", \"tight\"]:\n",
+    "    offsets = compute_channel_offsets(demo_trough, 6, spread=mode, channel_spacings=mixed_spacings)\n",
+    "    centers = sorted([demo_trough.get_size_y() / 2 + o.y for o in offsets])\n",
+    "    gaps = [round(centers[i + 1] - centers[i], 1) for i in range(len(centers) - 1)]\n",
+    "    print(f\"spread={mode!r:8s}  centers={[f'{c:.1f}' for c in centers]}  gaps={gaps}\")\n",
+    "\n",
+    "plot_spread_comparison(\n",
+    "    demo_trough, 6,\n",
+    "    title=\"6 channels, occupancy diameters [9, 18, 9, 18, 9, 9] mm\\n(demo trough, 200mm Y, center divider)\",\n",
+    "    channel_spacings=mixed_spacings,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f98db42a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "975b8b0e",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "t7qstevvf8b",
+   "metadata": {},
+   "source": [
+    "## Try it yourself\n",
+    "\n",
+    "Edit the parameters below to experiment with any container geometry:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "cqrxs83dgvi",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Compartments: [(2.0, 28.0), (34.0, 63.0), (69.0, 98.0)]\n",
+      "  1 ch: ['y=+33.5']\n",
+      "  2 ch: ['y=+33.5', 'y=-1.5']\n",
+      "  3 ch: ['y=+33.5', 'y=-1.5', 'y=-35.0']\n",
+      "  6 ch: ['y=+38.3', 'y=+28.7', 'y=+3.3', 'y=-6.3', 'y=-30.5', 'y=-39.5']\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 880x500 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# --- Edit these ---\n",
+    "CONTAINER_SIZE_X = 19.0   # mm\n",
+    "CONTAINER_SIZE_Y = 100.0  # mm\n",
+    "CONTAINER_SIZE_Z = 50.0   # mm\n",
+    "\n",
+    "# List of (y_start, y_end) pairs for no-go zones\n",
+    "NO_GO_Y_RANGES = [\n",
+    "    (30, 32),   # divider 1\n",
+    "    (65, 67),   # divider 2\n",
+    "]\n",
+    "\n",
+    "NUM_CHANNELS = [1, 2, 3, 6]  # channel counts to plot\n",
+    "# ------------------\n",
+    "\n",
+    "no_go_zones = [\n",
+    "    (Coordinate(0, y_lo, 0), Coordinate(CONTAINER_SIZE_X, y_hi, CONTAINER_SIZE_Z))\n",
+    "    for y_lo, y_hi in NO_GO_Y_RANGES\n",
+    "]\n",
+    "\n",
+    "custom = Container(\n",
+    "    name=\"custom_container\",\n",
+    "    size_x=CONTAINER_SIZE_X,\n",
+    "    size_y=CONTAINER_SIZE_Y,\n",
+    "    size_z=CONTAINER_SIZE_Z,\n",
+    "    no_go_zones=no_go_zones,\n",
+    ")\n",
+    "\n",
+    "print(f\"Compartments: {_get_compartments(custom)}\")\n",
+    "for n in NUM_CHANNELS:\n",
+    "    try:\n",
+    "        result = compute_channel_offsets(custom, n)\n",
+    "        status = [f\"y={o.y:+.1f}\" for o in result]\n",
+    "    except ValueError:\n",
+    "        status = \"Cannot fit\"\n",
+    "    print(f\"  {n} ch: {status}\")\n",
+    "\n",
+    "plot_container_cross_section(custom, NUM_CHANNELS)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "gfshxjfrbkm",
+   "metadata": {},
+   "source": [
+    "## End-to-end simulation\n",
+    "\n",
+    "Below we set up a full `LiquidHandler` with `STARChatterboxBackend` (simulation - no hardware needed) to verify that `aspirate` correctly distributes channels around no-go zones.\n",
+    "\n",
+    "The Hamilton-specific trough definitions (`hamilton_1_trough_60mL_Vb`, `hamilton_1_trough_120mL_Vb`) already have `no_go_zones` pre-configured - you don't need to define them manually when using these resources."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "wnozu8h6wt8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Trough: trough_60\n",
+      "Pre-configured no-go zones: [(Coordinate(x=0, y=44.4, z=5.0), Coordinate(x=19.0, y=45.6, z=60.25))]\n",
+      "Compartments: [(2.0, 42.4), (47.6, 88.0)]\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pylabrobot.liquid_handling import LiquidHandler\n",
+    "from pylabrobot.liquid_handling.backends.hamilton.STAR_chatterbox import STARChatterboxBackend\n",
+    "from pylabrobot.resources.hamilton import STARLetDeck\n",
+    "from pylabrobot.resources.hamilton.tip_racks import hamilton_96_tiprack_1000uL_filter\n",
+    "from pylabrobot.resources.hamilton.trough_carriers import Trough_CAR_5R60_A00\n",
+    "from pylabrobot.resources.hamilton.troughs import hamilton_1_trough_60mL_Vb\n",
+    "from pylabrobot.resources import TIP_CAR_480_A00, set_tip_tracking, set_volume_tracking\n",
+    "\n",
+    "set_tip_tracking(True)\n",
+    "set_volume_tracking(True)\n",
+    "\n",
+    "backend = STARChatterboxBackend(num_channels=8)\n",
+    "deck = STARLetDeck()\n",
+    "lh = LiquidHandler(backend=backend, deck=deck)\n",
+    "await lh.setup()\n",
+    "\n",
+    "tip_car = TIP_CAR_480_A00(name=\"tip_carrier\")\n",
+    "tip_car[0] = hamilton_96_tiprack_1000uL_filter(name=\"tips_1000\")\n",
+    "deck.assign_child_resource(tip_car, rails=1)\n",
+    "\n",
+    "trough_car = Trough_CAR_5R60_A00(name=\"trough_carrier\")\n",
+    "trough_car[0] = hamilton_1_trough_60mL_Vb(name=\"trough_60\")\n",
+    "deck.assign_child_resource(trough_car, rails=10)\n",
+    "\n",
+    "trough = deck.get_resource(\"trough_60\")\n",
+    "print(f\"Trough: {trough.name}\")\n",
+    "print(f\"Pre-configured no-go zones: {trough.no_go_zones}\")\n",
+    "print(f\"Compartments: {_get_compartments(trough)}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "w71fiy95wq",
+   "metadata": {},
+   "source": [
+    "### Aspirate with 2 and 4 channels\n",
+    "\n",
+    "Pick up tips, fill the trough, then aspirate. The chatterbox backend prints raw firmware commands - the `yp` values show absolute Y positions in 0.1mm units. Verify that channels land in separate compartments and avoid the divider at Y=44-46mm."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "bc6s5vhj5wh",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "C0TTid0001tt01tf1tl0871tv10650tg3tu0\n",
+      "C0TPid0002xp01179 01179 01179 01179 00000&yp1458 1368 1278 1188 0000&tm1 1 1 1 0&tt01tp2266tz2166th2450td0\n",
+      "2 channels -> offsets: ['+22.8mm', '-22.8mm']\n",
+      "4 channels -> offsets: ['+29.5mm', '+16.1mm', '-16.1mm', '-29.5mm']\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 440x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "tip_rack = deck.get_resource(\"tips_1000\")\n",
+    "await lh.pick_up_tips(tip_rack[\"A1:D1\"])\n",
+    "trough.tracker.set_volume(50_000)\n",
+    "\n",
+    "# Show expected offsets before aspirating\n",
+    "for n in [2, 4]:\n",
+    "    offsets = compute_channel_offsets(trough, n)\n",
+    "    print(f\"{n} channels -> offsets: {[f'{o.y:+.1f}mm' for o in offsets]}\")\n",
+    "\n",
+    "plot_container_cross_section(trough, [2, 4])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "mvpra250mkk",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Simulation stopped.\n"
+     ]
+    }
+   ],
+   "source": [
+    "await lh.stop()\n",
+    "print(\"Simulation stopped.\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "plr",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/pylabrobot/liquid_handling/backends/backend.py b/pylabrobot/liquid_handling/backends/backend.py
index dc3253986e3..945dfff6da3 100644
--- a/pylabrobot/liquid_handling/backends/backend.py
+++ b/pylabrobot/liquid_handling/backends/backend.py
@@ -18,6 +18,7 @@
   SingleChannelAspiration,
   SingleChannelDispense,
 )
+from pylabrobot.liquid_handling.utils import GENERIC_LH_MIN_SPACING_BETWEEN_CHANNELS
 from pylabrobot.machines.backend import MachineBackend
 from pylabrobot.resources import Deck, Tip
 from pylabrobot.resources.tip_tracker import TipTracker
@@ -158,6 +159,27 @@ async def request_tip_presence(self) -> List[Optional[bool]]:
 
     raise NotImplementedError()
 
+  def get_channel_spacings(self, use_channels: List[int]) -> List[float]:
+    """Get the per-channel occupancy diameter for each channel being used.
+
+    Each value is the channel's occupancy diameter - the physical space it takes up.
+    The required center-to-center distance between two adjacent channels is the sum of
+    their radii: ``spacing[i]/2 + spacing[j]/2``.
+
+    Args:
+      use_channels: The channels being used, in order.
+
+    Returns:
+      List of per-channel occupancy diameters (mm), length = ``len(use_channels)``.
+      Defaults to ``GENERIC_LH_MIN_SPACING_BETWEEN_CHANNELS`` (9mm) for all channels.
+      Backends with variable channel spacing should override this.
+
+    Note: This assumes channels spread along Y. Backends where channels are fixed in Y
+    (e.g. OT2 with 2 channels at fixed X spacing) should either override this or
+    signal that Y-spread is not supported via a ``supports_y_spread`` property.
+    """
+    return [GENERIC_LH_MIN_SPACING_BETWEEN_CHANNELS] * len(use_channels)
+
   @abstractmethod
   def can_pick_up_tip(self, channel_idx: int, tip: Tip) -> bool:
     """Check if the tip can be picked up by the specified channel. Does not consider
diff --git a/pylabrobot/liquid_handling/backends/hamilton/STAR_backend.py b/pylabrobot/liquid_handling/backends/hamilton/STAR_backend.py
index 6db6691bb75..8d23b3dfd3c 100644
--- a/pylabrobot/liquid_handling/backends/hamilton/STAR_backend.py
+++ b/pylabrobot/liquid_handling/backends/hamilton/STAR_backend.py
@@ -3,7 +3,6 @@
 import enum
 import functools
 import logging
-import math
 import re
 import sys
 import warnings
@@ -1358,15 +1357,16 @@ def __init__(
     self._setup_done = False
 
   def _min_spacing_between(self, i: int, j: int) -> float:
-    """Return the conservative minimum Y spacing required between channels *i* and *j*.
+    """Return the firmware-safe minimum Y spacing between channels *i* and *j*.
 
-    For adjacent channels, the constraint is the larger of the two channels' individual minimum
-    spacings, ceiling'd to 1 decimal place for safe movement.
-
-    For non-adjacent channels, the spacing is the sum of all intermediate adjacent-pair spacings.
+    Uses max() of both channels' spacings for firmware safety (conservative).
+    For adjacent channels, ceiling-rounded to 0.1mm.
+    For non-adjacent channels, the sum of all intermediate adjacent-pair spacings.
     """
     lo, hi = min(i, j), max(i, j)
     if hi - lo == 1:
+      import math
+
       spacing = max(self._channels_minimum_y_spacing[lo], self._channels_minimum_y_spacing[hi])
       return math.ceil(spacing * 10) / 10
     return sum(self._min_spacing_between(k, k + 1) for k in range(lo, hi))
@@ -2214,10 +2214,6 @@ def _compute_channels_in_resource_locations(
           )
           min_ch = min(use_channels)
           offsets = [all_offsets[ch - min_ch] for ch in use_channels]
-
-          if num_channels_in_span % 2 != 0:
-            y_offset = 5.5
-            offsets = [offset + Coordinate(0, y_offset, 0) for offset in offsets]
         # else: container too small to fit all channels — fall back to center offsets.
         # Y sub-batching will serialize channels that can't coexist.
 
@@ -2328,8 +2324,8 @@ async def probe_liquid_heights(
     Notes:
       - All specified channels must have tips attached
       - Containers at different X positions are probed in sequential groups (single X carriage)
-      - For single containers with odd channel counts, Y-offsets are applied to avoid
-        center dividers (Hamilton 1000 uL spacing: 9mm, offset: 5.5mm)
+      - For single containers with no-go zones, Y-offsets are computed to avoid
+        obstructed regions (e.g. center dividers in troughs)
     """
 
     if move_to_z_safety_after is not None:
@@ -4550,6 +4546,9 @@ async def move_channel_z_relative(self, channel: int, distance: float):
     current_z = await self.request_z_pos_channel_n(channel)
     await self.move_channel_z(channel, current_z + distance)
 
+  def get_channel_spacings(self, use_channels: List[int]) -> List[float]:
+    return [self._channels_minimum_y_spacing[ch] for ch in sorted(use_channels)]
+
   def can_pick_up_tip(self, channel_idx: int, tip: Tip) -> bool:
     if not isinstance(tip, HamiltonTip):
       return False
diff --git a/pylabrobot/liquid_handling/liquid_handler.py b/pylabrobot/liquid_handling/liquid_handler.py
index 7654d4af444..212c54877c8 100644
--- a/pylabrobot/liquid_handling/liquid_handler.py
+++ b/pylabrobot/liquid_handling/liquid_handler.py
@@ -30,8 +30,7 @@
   get_strictness,
 )
 from pylabrobot.liquid_handling.utils import (
-  get_tight_single_resource_liquid_op_offsets,
-  get_wide_single_resource_liquid_op_offsets,
+  compute_channel_offsets,
 )
 from pylabrobot.machines.machine import Machine, need_setup_finished
 from pylabrobot.plate_reading import PlateReader
@@ -348,6 +347,20 @@ def _check_args(
 
     return extra
 
+  def _compute_spread_offsets(
+    self,
+    resource: Resource,
+    use_channels: List[int],
+    spread: str,
+  ) -> List[Coordinate]:
+    """Compute channel spread offsets for a single-resource multi-channel operation."""
+    return compute_channel_offsets(
+      resource=resource,
+      num_channels=len(use_channels),
+      spread=spread,
+      channel_spacings=self.backend.get_channel_spacings(use_channels),
+    )
+
   def _make_sure_channels_exist(self, channels: List[int]):
     """Checks that the channels exist."""
     invalid_channels = [c for c in channels if c not in self.head]
@@ -768,10 +781,7 @@ async def discard_tips(
       raise RuntimeError("No tips have been picked up and no channels were specified.")
 
     trash = self.deck.get_trash_area()
-    trash_offsets = get_tight_single_resource_liquid_op_offsets(
-      trash,
-      num_channels=n,
-    )
+    trash_offsets = compute_channel_offsets(trash, num_channels=n, spread="tight")
     # add trash_offsets to offsets if defined, otherwise use trash_offsets
     # too advanced for mypy
     offsets = [
@@ -947,18 +957,8 @@ async def aspirate(
     if len(set(resources)) == 1:
       resource = resources[0]
       resources = [resource] * len(use_channels)
-      if spread == "tight":
-        center_offsets = get_tight_single_resource_liquid_op_offsets(
-          resource=resource, num_channels=len(use_channels)
-        )
-      elif spread == "wide":
-        center_offsets = get_wide_single_resource_liquid_op_offsets(
-          resource=resource, num_channels=len(use_channels)
-        )
-      elif spread == "custom":
-        center_offsets = [Coordinate.zero()] * len(use_channels)
-      else:
-        raise ValueError("Invalid value for 'spread'. Must be 'tight', 'wide', or 'custom'.")
+
+      center_offsets = self._compute_spread_offsets(resource, use_channels, spread)
 
       # add user defined offsets to the computed centers
       offsets = [c + o for c, o in zip(center_offsets, offsets)]
@@ -1130,18 +1130,8 @@ async def dispense(
     if len(set(resources)) == 1:
       resource = resources[0]
       resources = [resource] * len(use_channels)
-      if spread == "tight":
-        center_offsets = get_tight_single_resource_liquid_op_offsets(
-          resource=resource, num_channels=len(use_channels)
-        )
-      elif spread == "wide":
-        center_offsets = get_wide_single_resource_liquid_op_offsets(
-          resource=resource, num_channels=len(use_channels)
-        )
-      elif spread == "custom":
-        center_offsets = [Coordinate.zero()] * len(use_channels)
-      else:
-        raise ValueError("Invalid value for 'spread'. Must be 'tight', 'wide', or 'custom'.")
+
+      center_offsets = self._compute_spread_offsets(resource, use_channels, spread)
 
       # add user defined offsets to the computed centers
       offsets = [c + o for c, o in zip(center_offsets, offsets)]
diff --git a/pylabrobot/liquid_handling/liquid_handler_tests.py b/pylabrobot/liquid_handling/liquid_handler_tests.py
index d31cfed45d0..f7ea77c5501 100644
--- a/pylabrobot/liquid_handling/liquid_handler_tests.py
+++ b/pylabrobot/liquid_handling/liquid_handler_tests.py
@@ -70,6 +70,7 @@ def _create_mock_backend(num_channels: int = 8):
   type(mock).num_arms = PropertyMock(return_value=1)
   type(mock).head96_installed = PropertyMock(return_value=True)
   mock.can_pick_up_tip.return_value = True
+  mock.get_channel_spacings.side_effect = lambda channels: [9.0] * len(channels)
   return mock
 
 
@@ -1207,3 +1208,121 @@ async def test_load_state_backward_compatible(self):
     # Old state format without head96_state or arm_state
     old_state = {"head_state": {c: self.lh.head[c].serialize() for c in self.lh.head}}
     self.lh.load_state(old_state)  # should not raise
+
+
+class TestNoGoZoneIntegration(unittest.IsolatedAsyncioTestCase):
+  """Integration tests for no-go zone channel distribution through LiquidHandler."""
+
+  async def asyncSetUp(self):
+    self.backend = _create_mock_backend(num_channels=8)
+    self.backend.get_channel_spacings.side_effect = lambda channels: [9.0] * len(channels)
+    self.deck = STARLetDeck()
+    self.lh = LiquidHandler(backend=self.backend, deck=self.deck)
+
+    # A trough-like container with a center divider
+    from pylabrobot.resources.trough import Trough
+
+    self.trough = Trough(
+      name="trough",
+      size_x=19.0,
+      size_y=90.0,
+      size_z=65.0,
+      max_volume=60_000,
+      no_go_zones=[(Coordinate(0, 44, 0), Coordinate(19, 46, 65))],
+    )
+    self.deck.assign_child_resource(self.trough, location=Coordinate(100, 100, 0))
+
+    self.tip_rack = hamilton_96_tiprack_300uL_filter(name="tip_rack")
+    self.deck.assign_child_resource(self.tip_rack, location=Coordinate(0, 0, 0))
+    await self.lh.setup()
+
+  async def test_aspirate_2_channels_avoids_no_go_zone(self):
+    """2 channels on a trough with a center divider should be placed in separate compartments."""
+    t0 = self.tip_rack.get_item("A1").get_tip()
+    t1 = self.tip_rack.get_item("B1").get_tip()
+    self.lh.update_head_state({0: t0, 1: t1})
+    self.trough.tracker.set_volume(50_000)
+
+    await self.lh.aspirate([self.trough] * 2, vols=[100, 100], use_channels=[0, 1])
+
+    ops = self.backend.aspirate.call_args.kwargs["ops"]
+    y_offsets = [op.offset.y for op in ops]
+    # Both offsets should be non-zero (not centered) and in opposite compartments
+    self.assertEqual(len(y_offsets), 2)
+    # One positive (back compartment), one negative (front compartment)
+    self.assertTrue(y_offsets[0] > 0 and y_offsets[1] < 0, f"offsets: {y_offsets}")
+    # Neither should be near the divider (Y=44-46, container center=45, so offset ~0 is bad)
+    for y in y_offsets:
+      self.assertGreater(abs(y), 5, f"offset {y} too close to divider")
+
+  async def test_single_channel_respects_no_go_zone(self):
+    """Single channel on a container with no-go zones should be placed in a safe compartment."""
+    t = self.tip_rack.get_item("A1").get_tip()
+    self.lh.update_head_state({0: t})
+    self.trough.tracker.set_volume(50_000)
+
+    await self.lh.aspirate([self.trough], vols=[100], use_channels=[0])
+
+    ops = self.backend.aspirate.call_args.kwargs["ops"]
+    # Single channel should be placed in a compartment, not at container center
+    # (container center Y=45 is inside the no-go zone at Y=44-46)
+    self.assertNotAlmostEqual(ops[0].offset.y, 0.0)
+    # Should be in the back compartment center: (48+88)/2 = 68, offset = 68-45 = 23
+    self.assertAlmostEqual(ops[0].offset.y, 23.0)
+
+  async def test_dispense_uses_no_go_zones(self):
+    """Dispense should also use no-go zone logic."""
+    t0 = self.tip_rack.get_item("A1").get_tip()
+    t1 = self.tip_rack.get_item("B1").get_tip()
+    self.lh.update_head_state({0: t0, 1: t1})
+    t0.tracker.add_liquid(volume=100)
+    t1.tracker.add_liquid(volume=100)
+
+    await self.lh.dispense([self.trough] * 2, vols=[100, 100], use_channels=[0, 1])
+
+    ops = self.backend.dispense.call_args.kwargs["ops"]
+    y_offsets = [op.offset.y for op in ops]
+    self.assertTrue(y_offsets[0] > 0 and y_offsets[1] < 0, f"offsets: {y_offsets}")
+
+  async def test_no_go_zones_skipped_for_custom_spread(self):
+    """spread='custom' should bypass no-go zone logic."""
+    t0 = self.tip_rack.get_item("A1").get_tip()
+    t1 = self.tip_rack.get_item("B1").get_tip()
+    self.lh.update_head_state({0: t0, 1: t1})
+    self.trough.tracker.set_volume(50_000)
+
+    await self.lh.aspirate([self.trough] * 2, vols=[100, 100], use_channels=[0, 1], spread="custom")
+
+    ops = self.backend.aspirate.call_args.kwargs["ops"]
+    # Custom spread: offsets should be zero (user controls positioning)
+    for op in ops:
+      self.assertAlmostEqual(op.offset.y, 0.0)
+
+  async def test_no_go_zones_tight_vs_wide(self):
+    """spread='tight' should pack channels closer than spread='wide' within compartments."""
+    tips = [self.tip_rack.get_item(f"{chr(65 + i)}1").get_tip() for i in range(4)]
+    self.lh.update_head_state({i: t for i, t in enumerate(tips)})
+    self.trough.tracker.set_volume(50_000)
+    self.backend.get_channel_spacings.side_effect = lambda channels: [9.0] * len(channels)
+
+    # wide (default): channels spread far apart within each compartment
+    await self.lh.aspirate(
+      [self.trough] * 4, vols=[100] * 4, use_channels=[0, 1, 2, 3], spread="wide"
+    )
+    wide_ops = self.backend.aspirate.call_args.kwargs["ops"]
+    wide_offsets = sorted([op.offset.y for op in wide_ops])
+
+    self.lh.update_head_state({i: t for i, t in enumerate(tips)})
+    self.trough.tracker.set_volume(50_000)
+
+    # tight: channels packed at minimum spacing within each compartment
+    await self.lh.aspirate(
+      [self.trough] * 4, vols=[100] * 4, use_channels=[0, 1, 2, 3], spread="tight"
+    )
+    tight_ops = self.backend.aspirate.call_args.kwargs["ops"]
+    tight_offsets = sorted([op.offset.y for op in tight_ops])
+
+    # within each compartment, wide channels should be further apart than tight
+    wide_gap_lower = abs(wide_offsets[1] - wide_offsets[0])
+    tight_gap_lower = abs(tight_offsets[1] - tight_offsets[0])
+    self.assertGreater(wide_gap_lower, tight_gap_lower)
diff --git a/pylabrobot/liquid_handling/utils.py b/pylabrobot/liquid_handling/utils.py
index a59ed6e4e2d..4c5e8cbdd4f 100644
--- a/pylabrobot/liquid_handling/utils.py
+++ b/pylabrobot/liquid_handling/utils.py
@@ -1,75 +1,482 @@
-from typing import List
+import math
+import warnings
+from typing import List, Optional, Tuple
 
+from pylabrobot.resources.container import Container
 from pylabrobot.resources.coordinate import Coordinate
 from pylabrobot.resources.resource import Resource
 
 GENERIC_LH_MIN_SPACING_BETWEEN_CHANNELS = 9
 MIN_SPACING_BETWEEN_CHANNELS = GENERIC_LH_MIN_SPACING_BETWEEN_CHANNELS
-# minimum spacing between the edge of the container and the center of channel
-MIN_SPACING_EDGE = 1.0
+# minimum spacing between the edge of the container and the border of a pipette
+MIN_SPACING_EDGE = 2.0
 
 
-def _get_centers_with_margin(dim_size: float, n: int, margin: float, min_spacing: float):
-  """Get the centers of the channels with a minimum margin on the edges."""
-  if dim_size < margin * 2 + (n - 1) * min_spacing:
+def _get_compartments(
+  container: Container,
+  edge_clearance: float = MIN_SPACING_EDGE,
+) -> List[Tuple[float, float]]:
+  """Compute the usable Y compartments within a container created by no-go zones.
+
+  Each compartment is the free-space region between no-go zones and/or container walls,
+  shrunk by ``edge_clearance`` on each side.
+
+  Args:
+    container: The container whose no-go zones define the compartments.
+    edge_clearance: Minimum clearance between the pipette border and a compartment
+      boundary (container wall or no-go zone) in mm.
+
+  Returns:
+    List of (y_min, y_max) tuples representing usable Y ranges for channel centers.
+  """
+  container_y = container.get_size_y()
+  zones = sorted(container.no_go_zones, key=lambda z: z[0].y)
+
+  raw_compartments = []
+  prev_end = 0.0
+  for flb, brt in zones:
+    if flb.y > prev_end:
+      raw_compartments.append((prev_end, flb.y))
+    prev_end = max(prev_end, brt.y)
+  if prev_end < container_y:
+    raw_compartments.append((prev_end, container_y))
+
+  usable = []
+  for lo, hi in raw_compartments:
+    raw_width = hi - lo
+    usable_lo = lo + edge_clearance
+    usable_hi = hi - edge_clearance
+    if usable_hi > usable_lo:
+      usable.append((usable_lo, usable_hi))
+    elif raw_width > 0:
+      warnings.warn(
+        f"Compartment Y=[{lo:.1f}, {hi:.1f}] (width={raw_width:.1f}mm) is smaller than "
+        f"2 * edge_clearance ({2 * edge_clearance:.1f}mm). Automatic channel positioning will "
+        f"skip this compartment. Ensure the attached tip physically fits in the container.",
+        stacklevel=3,
+      )
+  return usable
+
+
+def _resolve_channel_spacings(
+  num_channels: int,
+  channel_spacings: Optional[List[float]] = None,
+) -> List[float]:
+  """Resolve channel_spacings to a validated per-channel list.
+
+  Args:
+    num_channels: Number of channels.
+    channel_spacings: Per-channel occupancy diameters (length = num_channels).
+      Each value is the physical space the channel occupies.
+      If None, defaults to GENERIC_LH_MIN_SPACING_BETWEEN_CHANNELS for all.
+
+  Returns:
+    List of per-channel spacings, length = num_channels.
+  """
+  if channel_spacings is None:
+    return [GENERIC_LH_MIN_SPACING_BETWEEN_CHANNELS] * num_channels
+  if num_channels <= 1:
+    return channel_spacings[:num_channels]
+  if len(channel_spacings) != num_channels:
+    raise ValueError(
+      f"channel_spacings has {len(channel_spacings)} entries, "
+      f"expected {num_channels} (one per channel)."
+    )
+  return channel_spacings
+
+
+def required_spacing_between(channel_spacings: List[float], i: int, j: int) -> float:
+  """Compute the required center-to-center distance between channels i and j.
+
+  Each channel's spacing value is its diameter - the minimum distance its center must maintain
+  from any neighbor. For adjacent channels, the required distance is the sum of both channels'
+  radii (half-spacings), ceiling-rounded to 0.1mm for safety. For non-adjacent channels, the
+  distance is the sum of all intermediate adjacent-pair required spacings.
+
+  Args:
+    channel_spacings: Per-channel spacing values (one per channel). Each value is the channel's
+      spacing diameter.
+    i: Index of the first channel.
+    j: Index of the second channel.
+
+  Returns:
+    Required center-to-center distance in mm, ceiling-rounded to 0.1mm.
+  """
+  lo, hi = min(i, j), max(i, j)
+  if hi - lo == 1:
+    return math.ceil((channel_spacings[lo] / 2 + channel_spacings[hi] / 2) * 10) / 10
+  return sum(required_spacing_between(channel_spacings, k, k + 1) for k in range(lo, hi))
+
+
+def _position_channels_wide(
+  resource_size: float,
+  channel_spacings: List[float],
+) -> List[float]:
+  """Compute channel Y centers spread wide across a single region.
+
+  Distributes channels as far apart as possible while respecting per-channel spacing constraints.
+  Edge clearance = each edge channel's radius (half its occupancy diameter).
+  Returns centers in front-to-back order (ascending Y).
+  """
+  num_channels = len(channel_spacings)
+  if num_channels == 1:
+    return [resource_size / 2]
+
+  gaps = [
+    required_spacing_between(channel_spacings, i, i + 1) for i in range(len(channel_spacings) - 1)
+  ]
+  needed = sum(gaps)
+  first_radius = channel_spacings[0] / 2
+  last_radius = channel_spacings[-1] / 2
+  usable = resource_size - first_radius - last_radius
+
+  if usable < needed:
     raise ValueError("Resource is too small to space channels.")
-  if dim_size - (n - 1) * min_spacing <= min_spacing * 2:
-    remaining_space = dim_size - (n - 1) * min_spacing - margin * 2
-    return [margin + remaining_space / 2 + i * min_spacing for i in range(n)]
-  return [(i + 1) * dim_size / (n + 1) for i in range(n)]
 
+  max_gap = max(gaps)
+  classic_gap = resource_size / (num_channels + 1)
+  if classic_gap >= max_gap:
+    return [(i + 1) * resource_size / (num_channels + 1) for i in range(num_channels)]
 
-def get_wide_single_resource_liquid_op_offsets(
+  # Can't achieve equal spacing; center block like tight
+  surplus = usable - needed
+  start = first_radius + surplus / 2
+  centers = [start]
+  for g in gaps:
+    centers.append(centers[-1] + g)
+  return centers
+
+
+def _position_channels_tight(
+  resource_size: float,
+  channel_spacings: List[float],
+) -> List[float]:
+  """Compute channel Y centers packed tight in the center of a single region.
+
+  Channels are placed at minimum gap distances, centered in the region.
+  Edge clearance = each edge channel's radius (half its occupancy diameter).
+  Returns centers in front-to-back order (ascending Y).
+  """
+  num_channels = len(channel_spacings)
+  if num_channels == 1:
+    return [resource_size / 2]
+
+  gaps = [
+    required_spacing_between(channel_spacings, i, i + 1) for i in range(len(channel_spacings) - 1)
+  ]
+  needed = sum(gaps)
+  first_radius = channel_spacings[0] / 2
+  last_radius = channel_spacings[-1] / 2
+  usable = resource_size - first_radius - last_radius
+
+  if usable < needed:
+    raise ValueError("Resource is too small to space channels.")
+
+  surplus = usable - needed
+  start = first_radius + surplus / 2
+  centers = [start]
+  for g in gaps:
+    centers.append(centers[-1] + g)
+  return centers
+
+
+def _centers_to_offsets(centers: List[float], resource: Resource) -> List[Coordinate]:
+  """Convert absolute Y centers to offsets relative to the resource center, sorted back-to-front."""
+  center_y = resource.center().rotated(resource.get_absolute_rotation()).y
+  offsets = [Coordinate(x=0, y=c - center_y, z=0) for c in centers]
+  offsets.sort(key=lambda o: o.y, reverse=True)
+  return offsets
+
+
+def _space_needed(spacings: List[float]) -> float:
+  """Compute the minimum space needed for a contiguous group of channels."""
+  if len(spacings) <= 1:
+    return 0.0
+  return sum(required_spacing_between(spacings, i, i + 1) for i in range(len(spacings) - 1))
+
+
+def _distribute_channels(
+  compartments: List[Tuple[float, float]],
+  num_channels: int,
+  spacings: List[float],
+) -> List[int]:
+  """Distribute channels across compartments proportionally to compartment width.
+
+  Channels are ordered and assigned contiguously. Wider compartments get more channels.
+  Falls back to shifting channels between neighbors if proportional assignment doesn't fit.
+
+  Args:
+    compartments: List of (y_min, y_max) usable compartment ranges.
+    num_channels: Total number of channels to distribute.
+    spacings: Per-channel spacing values (length = num_channels).
+
+  Returns:
+    List of channel counts per compartment.
+
+  Raises:
+    ValueError: If no valid distribution exists.
+  """
+  n_comp = len(compartments)
+  widths = [hi - lo for lo, hi in compartments]
+  total_width = sum(widths)
+
+  # Proportional targets (largest-remainder rounding)
+  targets = [w / total_width * num_channels for w in widths]
+  distribution = [int(t) for t in targets]
+  remainders = [t - int(t) for t in targets]
+  deficit = num_channels - sum(distribution)
+  # Give extra channels to compartments with largest remainders.
+  # Break ties by preferring back compartments (higher index = further back).
+  for _ in range(deficit):
+    idx = max(range(n_comp), key=lambda i: (remainders[i], i))
+    distribution[idx] += 1
+    remainders[idx] = -1  # don't pick again
+
+  # Validate: check each group fits
+  def _fits(dist: List[int]) -> bool:
+    idx = 0
+    for comp_idx, n_ch in enumerate(dist):
+      if n_ch == 0:
+        idx += 0
+        continue
+      group = spacings[idx : idx + n_ch]
+      needed = _space_needed(group)
+      if needed > widths[comp_idx]:
+        return False
+      idx += n_ch
+    return True
+
+  if _fits(distribution):
+    return distribution
+
+  # Try shifting channels from overloaded compartments to neighbors
+  for _ in range(num_channels):
+    improved = False
+    idx = 0
+    for comp_idx in range(n_comp):
+      n_ch = distribution[comp_idx]
+      if n_ch == 0:
+        continue
+      group = spacings[idx : idx + n_ch]
+      needed = _space_needed(group)
+      if needed > widths[comp_idx] and n_ch > 1:
+        # Try shifting last channel to next compartment
+        if comp_idx + 1 < n_comp:
+          distribution[comp_idx] -= 1
+          distribution[comp_idx + 1] += 1
+          improved = True
+          break
+        # Try shifting first channel to previous compartment
+        if comp_idx - 1 >= 0:
+          distribution[comp_idx] -= 1
+          distribution[comp_idx - 1] += 1
+          improved = True
+          break
+      idx += n_ch
+    if not improved:
+      break
+    if _fits(distribution):
+      return distribution
+
+  if _fits(distribution):
+    return distribution
+
+  raise ValueError(
+    "Cannot distribute channels across compartments while respecting spacing constraints."
+  )
+
+
+def compute_channel_offsets(
   resource: Resource,
   num_channels: int,
-  min_spacing: float = GENERIC_LH_MIN_SPACING_BETWEEN_CHANNELS,
+  spread: str = "wide",
+  channel_spacings: Optional[List[float]] = None,
 ) -> List[Coordinate]:
-  resource_size = resource.get_absolute_size_y()
-  centers = list(
-    reversed(
-      _get_centers_with_margin(
-        dim_size=resource_size,
-        n=num_channels,
-        margin=MIN_SPACING_EDGE,
-        min_spacing=min_spacing,
-      )
-    )
-  )  # reverse because channels are from back to front
-
-  # offsets are relative to the center of the resource, but above we computed them wrt lfb
-  # so we need to subtract the center of the resource
-  # also, offsets are in absolute space, so we need to rotate the center
-  return [
-    Coordinate(
-      x=0,
-      y=c - resource.center().rotated(resource.get_absolute_rotation()).y,
-      z=0,
+  """Compute Y offsets for positioning pipette channels in a resource.
+
+  Single entry point for all channel positioning logic. Handles containers with no-go zones
+  (distributing channels across compartments) and plain resources (wide/tight spread).
+
+  Args:
+    resource: The target resource (Container, Trough, Well, etc.).
+    num_channels: Number of channels to position.
+    spread: Positioning strategy:
+      - "wide": spread channels as far apart as possible (respects no-go zones if present)
+      - "tight": pack channels at minimum spacing (respects no-go zones if present)
+      - "custom": return zero offsets (caller controls positioning)
+    channel_spacings: Per-channel occupancy diameters in mm (length = num_channels).
+      Each value is the physical space the channel occupies. The required gap between
+      channels i and i+1 = spacing[i]/2 + spacing[i+1]/2 (sum of radii).
+      If None, defaults to 9mm for all channels.
+
+  Returns:
+    List of Y offsets relative to the resource center, sorted back-to-front (descending Y).
+
+  Raises:
+    ValueError: If channels cannot fit, or if spread is not "wide", "tight", or "custom".
+  """
+  if spread == "custom":
+    return [Coordinate.zero()] * num_channels
+  if spread not in ("wide", "tight"):
+    raise ValueError(
+      f"Invalid value for 'spread': {spread!r}. Must be 'wide', 'tight', or 'custom'."
     )
-    for c in centers
-  ]
 
+  spacings = _resolve_channel_spacings(num_channels, channel_spacings)
 
-def get_tight_single_resource_liquid_op_offsets(
+  # channel_spacings are back-to-front (ch0=backmost first).
+  # Compartments are processed front-to-back (ascending Y).
+  # Reverse for compartment assignment so spacings[0] = frontmost channel.
+  spacings_front_to_back = list(reversed(spacings))
+
+  # Container with no-go zones: distribute across compartments
+  if isinstance(resource, Container) and resource.no_go_zones:
+    compartments = _get_compartments(resource)
+    if not compartments:
+      raise ValueError(
+        f"Cannot fit {num_channels} channels into the compartments of "
+        f"'{resource.name}' while respecting its no-go zones. "
+        f"Use fewer channels or spread='custom' with manual offsets."
+      )
+
+    distribution = _distribute_channels(compartments, num_channels, spacings_front_to_back)
+
+    container_center_y = resource.get_size_y() / 2
+    offsets = []
+    spacing_idx = 0
+
+    for (comp_lo, comp_hi), n_ch in zip(compartments, distribution):
+      if n_ch == 0:
+        continue
+      comp_width = comp_hi - comp_lo
+
+      # Slice per-channel spacings for this group (front-to-back order)
+      group_spacings = spacings_front_to_back[spacing_idx : spacing_idx + n_ch]
+      spacing_idx += n_ch
+
+      if n_ch == 1:
+        if comp_width <= 0:
+          raise ValueError(
+            f"Cannot fit {num_channels} channels into the compartments of "
+            f"'{resource.name}' while respecting its no-go zones. "
+            f"Use fewer channels or spread='custom' with manual offsets."
+          )
+        centers = [(comp_lo + comp_hi) / 2]
+      else:
+        group_gaps = [
+          required_spacing_between(group_spacings, i, i + 1) for i in range(len(group_spacings) - 1)
+        ]
+        needed = sum(group_gaps)
+        # Edge clearance: first and last channel's radius must not extend past compartment
+        first_radius = group_spacings[0] / 2
+        last_radius = group_spacings[-1] / 2
+        usable = comp_width - first_radius - last_radius
+
+        if usable < needed:
+          raise ValueError(
+            f"Cannot fit {num_channels} channels into the compartments of "
+            f"'{resource.name}' while respecting its no-go zones. "
+            f"Use fewer channels or spread='custom' with manual offsets."
+          )
+
+        if spread == "wide":
+          max_gap = max(group_gaps)
+          classic_gap = comp_width / (n_ch + 1)
+          if classic_gap >= max_gap:
+            centers = [comp_lo + (i + 1) * comp_width / (n_ch + 1) for i in range(n_ch)]
+          else:
+            # Can't achieve equal spacing; center block like tight
+            surplus = usable - needed
+            start = comp_lo + first_radius + surplus / 2
+            centers = [start]
+            for g in group_gaps:
+              centers.append(centers[-1] + g)
+        else:
+          # Tight: minimum gaps, centered within usable space
+          surplus = usable - needed
+          start = comp_lo + first_radius + surplus / 2
+          centers = [start]
+          for g in group_gaps:
+            centers.append(centers[-1] + g)
+
+      for c in centers:
+        offsets.append(Coordinate(0, c - container_center_y, 0))
+
+    # Validate cross-compartment gaps: channels at adjacent compartment boundaries
+    # must respect their required spacing across the no-go zone.
+    all_centers = sorted([container_center_y + o.y for o in offsets])
+    ch_idx = 0
+    for comp_i in range(len(distribution) - 1):
+      n_a = distribution[comp_i]
+      n_b = distribution[comp_i + 1]
+      if n_a == 0 or n_b == 0:
+        ch_idx += n_a
+        continue
+      last_in_a = all_centers[ch_idx + n_a - 1]
+      first_in_b = all_centers[ch_idx + n_a]
+      # Spacing indices: last channel of group A and first channel of group B
+      spacing_idx_a = sum(distribution[: comp_i + 1]) - 1
+      spacing_idx_b = spacing_idx_a + 1
+      required = required_spacing_between(spacings_front_to_back, spacing_idx_a, spacing_idx_b)
+      actual = first_in_b - last_in_a
+      if actual < required - 0.05:
+        raise ValueError(
+          f"Cannot fit {num_channels} channels into the compartments of "
+          f"'{resource.name}' while respecting spacing constraints across no-go zones "
+          f"(gap {actual:.1f}mm < required {required:.1f}mm between compartments "
+          f"{comp_i} and {comp_i + 1}). "
+          f"Use fewer channels or spread='custom' with manual offsets."
+        )
+      ch_idx += n_a
+
+    offsets.sort(key=lambda o: o.y, reverse=True)
+    return offsets
+
+  # Plain resource (no no-go zones): wide or tight across full Y
+  resource_size = resource.get_absolute_size_y()
+  if spread == "wide":
+    centers = _position_channels_wide(resource_size, spacings_front_to_back)
+  else:
+    centers = _position_channels_tight(resource_size, spacings_front_to_back)
+  return _centers_to_offsets(centers, resource)
+
+
+# ---------------------------------------------------------------------------
+# Deprecated wrappers (remove after 2026-09)
+# ---------------------------------------------------------------------------
+
+
+def get_wide_single_resource_liquid_op_offsets(
   resource: Resource,
   num_channels: int,
   min_spacing: float = GENERIC_LH_MIN_SPACING_BETWEEN_CHANNELS,
 ) -> List[Coordinate]:
-  channel_space = (num_channels - 1) * min_spacing
-
-  min_y = (resource.get_absolute_size_y() - channel_space) / 2
-  if min_y < MIN_SPACING_EDGE:
-    raise ValueError("Resource is too small to space channels.")
+  """Deprecated. Use ``compute_channel_offsets(resource, num_channels, spread='wide')`` instead."""
+  warnings.warn(
+    "get_wide_single_resource_liquid_op_offsets() is deprecated and will be removed after 2026-09. "
+    "Use compute_channel_offsets(resource, num_channels, spread='wide') instead.",
+    DeprecationWarning,
+    stacklevel=2,
+  )
+  per_channel = [min_spacing] * num_channels
+  return compute_channel_offsets(
+    resource, num_channels, spread="wide", channel_spacings=per_channel
+  )
 
-  centers = [min_y + i * min_spacing for i in range(num_channels)][::-1]
 
-  # offsets are relative to the center of the resource, but above we computed them wrt lfb
-  # so we need to subtract the center of the resource
-  # also, offsets are in absolute space, so we need to rotate the center
-  return [
-    Coordinate(
-      x=0,
-      y=c - resource.center().rotated(resource.get_absolute_rotation()).y,
-      z=0,
-    )
-    for c in centers
-  ]
+def get_tight_single_resource_liquid_op_offsets(
+  resource: Resource,
+  num_channels: int,
+  min_spacing: float = GENERIC_LH_MIN_SPACING_BETWEEN_CHANNELS,
+) -> List[Coordinate]:
+  """Deprecated. Use ``compute_channel_offsets(resource, num_channels, spread='tight')`` instead."""
+  warnings.warn(
+    "get_tight_single_resource_liquid_op_offsets() is deprecated and will be removed after 2026-09. "
+    "Use compute_channel_offsets(resource, num_channels, spread='tight') instead.",
+    DeprecationWarning,
+    stacklevel=2,
+  )
+  per_channel = [min_spacing] * num_channels
+  return compute_channel_offsets(
+    resource, num_channels, spread="tight", channel_spacings=per_channel
+  )
diff --git a/pylabrobot/resources/container.py b/pylabrobot/resources/container.py
index 633cc6c9653..26106be6045 100644
--- a/pylabrobot/resources/container.py
+++ b/pylabrobot/resources/container.py
@@ -1,4 +1,4 @@
-from typing import Any, Callable, Dict, Optional
+from typing import Any, Callable, Dict, List, Optional, Tuple
 
 from pylabrobot.serializer import serialize
 from pylabrobot.utils.interpolation import interpolate_1d
@@ -24,6 +24,7 @@ def __init__(
     compute_volume_from_height: Optional[Callable[[float], float]] = None,
     compute_height_from_volume: Optional[Callable[[float], float]] = None,
     height_volume_data: Optional[Dict[float, float]] = None,
+    no_go_zones: Optional[List[Tuple[Coordinate, Coordinate]]] = None,
   ):
     """Create a new container.
 
@@ -35,6 +36,9 @@ def __init__(
         ``compute_volume_from_height`` and ``compute_height_from_volume`` are auto-generated
         via piecewise-linear interpolation if not explicitly passed. The data is also available
         for direct use (e.g. building firmware segments from calibration knots).
+      no_go_zones: List of cuboid regions within the container where tips must not be positioned.
+        Each zone is a tuple of two Coordinates: (front_left_bottom, back_right_top), relative to
+        the container's front-left-bottom origin.
     """
 
     super().__init__(
@@ -77,6 +81,46 @@ def compute_height_from_volume(v: float) -> float:
     self.tracker = VolumeTracker(thing=f"{self.name}_volume_tracker", max_volume=self.max_volume)
     self._compute_volume_from_height = compute_volume_from_height
     self._compute_height_from_volume = compute_height_from_volume
+    self.no_go_zones: List[Tuple[Coordinate, Coordinate]] = self._validate_no_go_zones(
+      no_go_zones or []
+    )
+
+  def _validate_no_go_zones(
+    self, zones: List[Tuple[Coordinate, Coordinate]]
+  ) -> List[Tuple[Coordinate, Coordinate]]:
+    """Validate no-go zones to ensure they are inside the container and well-formed.
+
+    Each zone is defined as (front_left_bottom, back_right_top).
+    """
+    validated: List[Tuple[Coordinate, Coordinate]] = []
+    for idx, (flb, brt) in enumerate(zones):
+      if not isinstance(flb, Coordinate) or not isinstance(brt, Coordinate):
+        raise TypeError(
+          f"no_go_zones[{idx}] must be a tuple of Coordinate instances, got {type(flb)!r}, {type(brt)!r}."
+        )
+
+      # Ensure front-left-bottom is not beyond back-right-top on any axis.
+      if flb.x > brt.x or flb.y > brt.y or flb.z > brt.z:
+        raise ValueError(
+          f"no_go_zones[{idx}] has invalid ordering: front_left_bottom must not exceed "
+          f"back_right_top on any axis (flb={flb}, brt={brt})."
+        )
+
+      # Ensure all coordinates lie within the container bounds.
+      for coord_label, coord in (("flb", flb), ("brt", brt)):
+        if coord.x < 0 or coord.y < 0 or coord.z < 0:
+          raise ValueError(f"no_go_zones[{idx}].{coord_label} has negative coordinates: {coord}.")
+        if (
+          coord.x > self.get_size_x() or coord.y > self.get_size_y() or coord.z > self.get_size_z()
+        ):
+          raise ValueError(
+            f"no_go_zones[{idx}].{coord_label}={coord} is outside the container bounds "
+            f"(size_x={self.get_size_x()}, size_y={self.get_size_y()}, size_z={self.get_size_z()})."
+          )
+
+      validated.append((flb, brt))
+
+    return validated
 
   @property
   def material_z_thickness(self) -> float:
@@ -99,6 +143,7 @@ def serialize(self) -> dict:
       if self.height_volume_data is not None
       else serialize(self._compute_height_from_volume),
       "height_volume_data": self.height_volume_data,
+      "no_go_zones": [(flb.serialize(), brt.serialize()) for flb, brt in self.no_go_zones],
     }
 
   def serialize_state(self) -> Dict[str, Any]:
diff --git a/pylabrobot/resources/container_tests.py b/pylabrobot/resources/container_tests.py
index 7d737092c2c..b45b3d63008 100644
--- a/pylabrobot/resources/container_tests.py
+++ b/pylabrobot/resources/container_tests.py
@@ -4,6 +4,7 @@
 from pylabrobot.serializer import serialize
 
 from .container import Container
+from .coordinate import Coordinate
 
 
 class TestContainer(unittest.TestCase):
@@ -41,6 +42,7 @@ def compute_height_from_volume(volume):
         "compute_volume_from_height": serialize(compute_volume_from_height),
         "compute_height_from_volume": serialize(compute_height_from_volume),
         "height_volume_data": None,
+        "no_go_zones": [],
         "parent_name": None,
         "rotation": {"type": "Rotation", "x": 0, "y": 0, "z": 0},
         "type": "Container",
@@ -165,3 +167,115 @@ def test_height_volume_data_validates_minimum_points(self):
       Container(
         name="c", size_x=10, size_y=10, size_z=10, height_volume_data={0: 0}
       )  # only 1 point
+
+  def test_no_go_zones_default_empty(self):
+    c = Container(name="c", size_x=10, size_y=10, size_z=10)
+    self.assertEqual(c.no_go_zones, [])
+
+  def test_no_go_zones_stored(self):
+    zones = [(Coordinate(0, 44, 0), Coordinate(10, 46, 10))]
+    c = Container(name="c", size_x=10, size_y=90, size_z=10, no_go_zones=zones)
+    self.assertEqual(len(c.no_go_zones), 1)
+    self.assertEqual(c.no_go_zones[0][0], Coordinate(0, 44, 0))
+    self.assertEqual(c.no_go_zones[0][1], Coordinate(10, 46, 10))
+
+  def test_no_go_zones_serialize(self):
+    zones = [(Coordinate(0, 44, 0), Coordinate(10, 46, 10))]
+    c = Container(name="c", size_x=10, size_y=90, size_z=10, no_go_zones=zones)
+    serialized = c.serialize()
+    self.assertEqual(
+      serialized["no_go_zones"],
+      [
+        (
+          {"type": "Coordinate", "x": 0, "y": 44, "z": 0},
+          {"type": "Coordinate", "x": 10, "y": 46, "z": 10},
+        )
+      ],
+    )
+
+  def test_no_go_zones_multiple(self):
+    zones = [
+      (Coordinate(0, 34.6, 0), Coordinate(10, 36.6, 10)),
+      (Coordinate(0, 70.2, 0), Coordinate(10, 72.2, 10)),
+      (Coordinate(0, 105.9, 0), Coordinate(10, 107.9, 10)),
+    ]
+    c = Container(name="c", size_x=10, size_y=142, size_z=10, no_go_zones=zones)
+    self.assertEqual(len(c.no_go_zones), 3)
+
+
+class TestNoGoZoneCollision(unittest.TestCase):
+  def _make_container(self, size_y, no_go_zones=None):
+    return Container(name="c", size_x=10, size_y=size_y, size_z=10, no_go_zones=no_go_zones)
+
+  def test_no_zones_uses_standard_spread(self):
+    from pylabrobot.liquid_handling.utils import compute_channel_offsets
+
+    c = self._make_container(90)
+    result = compute_channel_offsets(c, num_channels=1)
+    self.assertEqual(len(result), 1)
+    # No no-go zones: single channel goes to center (offset 0)
+    self.assertAlmostEqual(result[0].y, 0.0)
+
+  def test_1_channel_in_2_compartments(self):
+    from pylabrobot.liquid_handling.utils import compute_channel_offsets
+
+    # 90mm container, divider at Y=44-46 -> 2 compartments [0,44] and [46,90]
+    # edge_clearance = 2.0
+    # Usable: [2.0, 42.0] and [48.0, 88.0]
+    # 1 channel -> center-out back-first -> goes to back compartment (index 1)
+    # Center of back usable = (48.0 + 88.0) / 2 = 68.0
+    # Container center = 45.0, offset = 68.0 - 45.0 = 23.0
+    c = self._make_container(
+      90,
+      no_go_zones=[(Coordinate(0, 44, 0), Coordinate(10, 46, 10))],
+    )
+    result = compute_channel_offsets(c, num_channels=1)
+    self.assertEqual(len(result), 1)
+    self.assertAlmostEqual(result[0].y, 23.0)
+
+  def test_2_channels_across_2_compartments(self):
+    from pylabrobot.liquid_handling.utils import compute_channel_offsets
+
+    c = self._make_container(
+      90,
+      no_go_zones=[(Coordinate(0, 44, 0), Coordinate(10, 46, 10))],
+    )
+    result = compute_channel_offsets(c, num_channels=2)
+    self.assertEqual(len(result), 2)
+    # Sorted descending by Y (back-to-front)
+    self.assertGreater(result[0].y, result[1].y)
+
+  def test_4_channels_across_2_compartments(self):
+    from pylabrobot.liquid_handling.utils import compute_channel_offsets
+
+    c = self._make_container(
+      90,
+      no_go_zones=[(Coordinate(0, 44, 0), Coordinate(10, 46, 10))],
+    )
+    result = compute_channel_offsets(c, num_channels=4)
+    self.assertEqual(len(result), 4)
+
+  def test_raises_when_impossible(self):
+    from pylabrobot.liquid_handling.utils import compute_channel_offsets
+
+    # Entire container is no-go
+    c = self._make_container(
+      12,
+      no_go_zones=[(Coordinate(0, 0, 0), Coordinate(10, 12, 10))],
+    )
+    with self.assertRaises(ValueError):
+      compute_channel_offsets(c, num_channels=1)
+
+  def test_3_compartments_6_channels(self):
+    from pylabrobot.liquid_handling.utils import compute_channel_offsets
+
+    # 150mm container, 2 dividers -> 3 compartments, 6 channels -> 2 per compartment
+    c = self._make_container(
+      150,
+      no_go_zones=[
+        (Coordinate(0, 49, 0), Coordinate(10, 51, 10)),
+        (Coordinate(0, 99, 0), Coordinate(10, 101, 10)),
+      ],
+    )
+    result = compute_channel_offsets(c, num_channels=6)
+    self.assertEqual(len(result), 6)
diff --git a/pylabrobot/resources/hamilton/troughs.py b/pylabrobot/resources/hamilton/troughs.py
index 71c3b80b369..49026ba0bcd 100644
--- a/pylabrobot/resources/hamilton/troughs.py
+++ b/pylabrobot/resources/hamilton/troughs.py
@@ -2,6 +2,7 @@
 
 import warnings
 
+from pylabrobot.resources.coordinate import Coordinate
 from pylabrobot.resources.trough import Trough, TroughBottomType
 
 # --------------------------------------------------------------------------- #
@@ -43,11 +44,9 @@ def hamilton_1_trough_60mL_Vb(name: str) -> Trough:
   Trough 60 mL, w lid, self standing (V-bottom).
   True maximal volume capacity ~80 mL.
   Compatible with Trough_CAR_?? (194057 <- not yet integrated into PLR!).
+  Has a center support wall (~1.2mm wide at Y=44-46mm) but is still open
+  at the bottom.
   """
-  warnings.warn(
-    "hamilton_1_trough_60mL_Vb has a center support that can interfere with pipetting.\
-     If using an odd number of channels, use spread='custom' and define offsets for each channel to avoid collision."
-  )
 
   return Trough(
     name=name,
@@ -60,6 +59,9 @@ def hamilton_1_trough_60mL_Vb(name: str) -> Trough:
     model=hamilton_1_trough_60mL_Vb.__name__,
     bottom_type=TroughBottomType.V,
     height_volume_data=_hamilton_1_trough_60mL_Vb_height_volume_data,
+    no_go_zones=[
+      (Coordinate(0, 44.4, 5.0), Coordinate(19.0, 45.6, 60.25)),  # center divider
+    ],
   )
 
 
@@ -92,12 +94,9 @@ def hamilton_1_trough_120mL_Vb(name: str) -> Trough:
   Trough 120 mL, without lid, self standing (V-bottom).
   True maximal volume capacity ~120 mL.
   Compatible with Trough_CAR_?? (194058 <- not yet integrated into PLR!).
+  Has 3 in-container support beams (~2.5mm wide at base, ~0.8mm at top, tapered)
+  but is still open at the bottom.
   """
-  warnings.warn(
-    "hamilton_1_trough_120mL_Vb has 3 (!) in-container support beams that can interfere with "
-    "pipetting. If using an odd number of channels, use spread='custom' and define offsets "
-    "for each channel to avoid collision."
-  )
 
   return Trough(
     name=name,
@@ -110,6 +109,11 @@ def hamilton_1_trough_120mL_Vb(name: str) -> Trough:
     model=hamilton_1_trough_120mL_Vb.__name__,
     bottom_type=TroughBottomType.V,
     height_volume_data=_hamilton_1_trough_120mL_Vb_height_volume_data,
+    no_go_zones=[
+      (Coordinate(0, 39.7, 12.0), Coordinate(19.0, 42.2, 70.0)),  # beam 1
+      (Coordinate(0, 73.5, 12.0), Coordinate(19.0, 76.0, 70.0)),  # beam 2
+      (Coordinate(0, 107.3, 12.0), Coordinate(19.0, 109.8, 70.0)),  # beam 3
+    ],
   )
 
 
@@ -136,6 +140,7 @@ def hamilton_1_trough_200mL_Vb(name: str) -> Trough:
   Trough 200 mL, w lid, self standing (V-bottom).
   True maximal volume capacity ~300 mL.
   Compatible with Trough_CAR_4R200_A00 (185436).
+  Has a center support wall (~1.2mm wide at Y=59-61mm) which is open at the bottom.
   """
   return Trough(
     name=name,
@@ -148,6 +153,9 @@ def hamilton_1_trough_200mL_Vb(name: str) -> Trough:
     model=hamilton_1_trough_200mL_Vb.__name__,
     bottom_type=TroughBottomType.V,
     height_volume_data=_hamilton_1_trough_200mL_Vb_height_volume_data,
+    no_go_zones=[
+      (Coordinate(0, 60, 8.0), Coordinate(37.0, 61.7, 60.0))  # center divider
+    ],
   )
 
 
diff --git a/pylabrobot/resources/petri_dish.py b/pylabrobot/resources/petri_dish.py
index 410c105d1ee..2d9cbfe5dbf 100644
--- a/pylabrobot/resources/petri_dish.py
+++ b/pylabrobot/resources/petri_dish.py
@@ -20,6 +20,7 @@ def __init__(
     compute_volume_from_height: Optional[Callable[[float], float]] = None,
     compute_height_from_volume: Optional[Callable[[float], float]] = None,
     height_volume_data: Optional[Dict[float, float]] = None,
+    no_go_zones=None,
   ):
     super().__init__(
       name=name,
@@ -33,6 +34,7 @@ def __init__(
       compute_volume_from_height=compute_volume_from_height,
       compute_height_from_volume=compute_height_from_volume,
       height_volume_data=height_volume_data,
+      no_go_zones=no_go_zones,
     )
     self.diameter = diameter
     self.height = height
diff --git a/pylabrobot/resources/petri_dish_tests.py b/pylabrobot/resources/petri_dish_tests.py
index 956f191a964..a9e916c4b3e 100644
--- a/pylabrobot/resources/petri_dish_tests.py
+++ b/pylabrobot/resources/petri_dish_tests.py
@@ -25,6 +25,7 @@ def test_petri_dish_serialization(self):
         "compute_volume_from_height": None,
         "compute_height_from_volume": None,
         "height_volume_data": None,
+        "no_go_zones": [],
         "parent_name": None,
         "type": "PetriDish",
         "children": [],
diff --git a/pylabrobot/resources/trash.py b/pylabrobot/resources/trash.py
index 98ecd3e7f52..40c633d5072 100644
--- a/pylabrobot/resources/trash.py
+++ b/pylabrobot/resources/trash.py
@@ -17,6 +17,7 @@ def __init__(
     compute_volume_from_height=None,
     compute_height_from_volume=None,
     height_volume_data=None,
+    no_go_zones=None,
   ):
     super().__init__(
       name=name,
@@ -30,4 +31,5 @@ def __init__(
       compute_volume_from_height=compute_volume_from_height,
       compute_height_from_volume=compute_height_from_volume,
       height_volume_data=height_volume_data,
+      no_go_zones=no_go_zones,
     )
diff --git a/pylabrobot/resources/trough.py b/pylabrobot/resources/trough.py
index 1bdab42aec8..55aca488c44 100644
--- a/pylabrobot/resources/trough.py
+++ b/pylabrobot/resources/trough.py
@@ -31,6 +31,7 @@ def __init__(
     compute_volume_from_height: Optional[Callable[[float], float]] = None,
     compute_height_from_volume: Optional[Callable[[float], float]] = None,
     height_volume_data: Optional[Dict[float, float]] = None,
+    no_go_zones=None,
   ):
     if isinstance(bottom_type, str):
       bottom_type = TroughBottomType(bottom_type)
@@ -47,6 +48,7 @@ def __init__(
       compute_volume_from_height=compute_volume_from_height,
       compute_height_from_volume=compute_height_from_volume,
       height_volume_data=height_volume_data,
+      no_go_zones=no_go_zones,
     )
     self.through_base_to_container_base = through_base_to_container_base
     self.bottom_type = bottom_type
diff --git a/pylabrobot/resources/tube.py b/pylabrobot/resources/tube.py
index b684f5bb854..85e48d740a7 100644
--- a/pylabrobot/resources/tube.py
+++ b/pylabrobot/resources/tube.py
@@ -38,6 +38,7 @@ def __init__(
     compute_volume_from_height: Optional[Callable[[float], float]] = None,
     compute_height_from_volume: Optional[Callable[[float], float]] = None,
     height_volume_data: Optional[Dict[float, float]] = None,
+    no_go_zones=None,
   ):
     """Create a new tube.
 
@@ -67,6 +68,7 @@ def __init__(
       compute_volume_from_height=compute_volume_from_height,
       compute_height_from_volume=compute_height_from_volume,
       height_volume_data=height_volume_data,
+      no_go_zones=no_go_zones,
     )
     self.tracker.register_callback(self._state_updated)
 
diff --git a/pylabrobot/resources/well.py b/pylabrobot/resources/well.py
index 3cb6f5a4003..47983ca31c9 100644
--- a/pylabrobot/resources/well.py
+++ b/pylabrobot/resources/well.py
@@ -50,6 +50,7 @@ def __init__(
     compute_height_from_volume: Optional[Callable[[float], float]] = None,
     cross_section_type: Union[CrossSectionType, str] = CrossSectionType.CIRCLE,
     height_volume_data: Optional[Dict[float, float]] = None,
+    no_go_zones=None,
   ):
     """Create a new well.
 
@@ -99,6 +100,7 @@ def __init__(
       compute_height_from_volume=compute_height_from_volume,
       material_z_thickness=material_z_thickness,
       height_volume_data=height_volume_data,
+      no_go_zones=no_go_zones,
     )
     self.bottom_type = bottom_type
     self.cross_section_type = cross_section_type
diff --git a/pylabrobot/resources/well_tests.py b/pylabrobot/resources/well_tests.py
index f322d88521b..284c7cca82a 100644
--- a/pylabrobot/resources/well_tests.py
+++ b/pylabrobot/resources/well_tests.py
@@ -39,6 +39,7 @@ def test_serialize(self):
         "compute_volume_from_height": None,
         "compute_height_from_volume": None,
         "height_volume_data": None,
+        "no_go_zones": [],
       },
     )