diff --git a/jetson/ros2_ws/src/saltybot_bringup/saltybot_bringup/_vo_drift.py b/jetson/ros2_ws/src/saltybot_bringup/saltybot_bringup/_vo_drift.py
new file mode 100644
index 0000000..d23f1d7
--- /dev/null
+++ b/jetson/ros2_ws/src/saltybot_bringup/saltybot_bringup/_vo_drift.py
@@ -0,0 +1,150 @@
+"""
+_vo_drift.py — Visual odometry drift detector helpers (no ROS2 deps).
+
+Algorithm
+---------
+Two independent odometry streams (visual and wheel) are compared over a
+sliding time window.  Drift is measured as the absolute difference in
+cumulative path length travelled by each source over that window:
+
+    drift_m = |path_length(vo_window) − path_length(wheel_window)|
+
+Using cumulative path length (sum of inter-sample Euclidean steps) rather
+than straight-line displacement makes the measure robust to circular motion
+where start and end positions are the same.
+
+Drift is flagged when drift_m ≥ drift_threshold_m.
+
+Public API
+----------
+  OdomSample          — namedtuple(t, x, y)
+  OdomBuffer          — deque of OdomSamples with time-window trimming
+  compute_drift()     — compare two OdomBuffers and return DriftResult
+  DriftResult         — namedtuple(drift_m, vo_path_m, wheel_path_m,
+                                   is_drifting, window_s, n_vo, n_wheel)
+"""
+
+from __future__ import annotations
+
+import math
+from collections import deque
+from typing import NamedTuple, Sequence
+
+
+class OdomSample(NamedTuple):
+    t: float    # monotonic timestamp (seconds)
+    x: float    # position x (metres)
+    y: float    # position y (metres)
+
+
+class DriftResult(NamedTuple):
+    drift_m:     float   # |vo_path − wheel_path| (metres)
+    vo_path_m:   float   # cumulative path of VO source over window (metres)
+    wheel_path_m: float  # cumulative path of wheel source over window (metres)
+    is_drifting: bool    # True when drift_m >= threshold
+    window_s:    float   # actual time span of data used (seconds)
+    n_vo:        int     # number of VO samples in window
+    n_wheel:     int     # number of wheel samples in window
+
+
+class OdomBuffer:
+    """
+    Rolling buffer of OdomSamples trimmed to the last `max_age_s` seconds.
+
+    Parameters
+    ----------
+    max_age_s : float  — samples older than this are discarded (seconds)
+    """
+
+    def __init__(self, max_age_s: float = 10.0) -> None:
+        self._max_age = max_age_s
+        self._buf: deque[OdomSample] = deque()
+
+    # ── Public ────────────────────────────────────────────────────────────────
+
+    def push(self, sample: OdomSample) -> None:
+        """Append a sample and evict anything older than max_age_s."""
+        self._buf.append(sample)
+        self._trim(sample.t)
+
+    def window(self, window_s: float, now: float) -> list[OdomSample]:
+        """Return samples within the last window_s seconds of `now`."""
+        cutoff = now - window_s
+        return [s for s in self._buf if s.t >= cutoff]
+
+    def clear(self) -> None:
+        self._buf.clear()
+
+    def __len__(self) -> int:
+        return len(self._buf)
+
+    # ── Internal ──────────────────────────────────────────────────────────────
+
+    def _trim(self, now: float) -> None:
+        cutoff = now - self._max_age
+        while self._buf and self._buf[0].t < cutoff:
+            self._buf.popleft()
+
+
+# ── Core computation ──────────────────────────────────────────────────────────
+
+def compute_drift(
+    vo_buf:          OdomBuffer,
+    wheel_buf:       OdomBuffer,
+    window_s:        float,
+    drift_threshold_m: float,
+    now:             float,
+) -> DriftResult:
+    """
+    Compare VO and wheel odometry path lengths over the last `window_s`.
+
+    Parameters
+    ----------
+    vo_buf            : OdomBuffer of visual odometry samples
+    wheel_buf         : OdomBuffer of wheel odometry samples
+    window_s          : comparison window width (seconds)
+    drift_threshold_m : drift_m threshold for is_drifting flag
+    now               : current time (same scale as OdomSample.t)
+
+    Returns
+    -------
+    DriftResult — zero drift if either buffer has fewer than 2 samples.
+    """
+    vo_samples    = vo_buf.window(window_s, now)
+    wheel_samples = wheel_buf.window(window_s, now)
+
+    if len(vo_samples) < 2 or len(wheel_samples) < 2:
+        return DriftResult(
+            drift_m=0.0, vo_path_m=0.0, wheel_path_m=0.0,
+            is_drifting=False,
+            window_s=0.0, n_vo=len(vo_samples), n_wheel=len(wheel_samples),
+        )
+
+    vo_path    = _path_length(vo_samples)
+    wheel_path = _path_length(wheel_samples)
+    drift_m    = abs(vo_path - wheel_path)
+
+    # Actual data span = latest timestamp − earliest across both buffers
+    t_min = min(vo_samples[0].t,    wheel_samples[0].t)
+    t_max = max(vo_samples[-1].t,   wheel_samples[-1].t)
+    actual_window = t_max - t_min
+
+    return DriftResult(
+        drift_m=drift_m,
+        vo_path_m=vo_path,
+        wheel_path_m=wheel_path,
+        is_drifting=drift_m >= drift_threshold_m,
+        window_s=actual_window,
+        n_vo=len(vo_samples),
+        n_wheel=len(wheel_samples),
+    )
+
+
+def _path_length(samples: Sequence[OdomSample]) -> float:
+    """Sum of Euclidean inter-sample distances."""
+    total = 0.0
+    for i in range(1, len(samples)):
+        dx = samples[i].x - samples[i - 1].x
+        dy = samples[i].y - samples[i - 1].y
+        total += math.sqrt(dx * dx + dy * dy)
+    return total
diff --git a/jetson/ros2_ws/src/saltybot_bringup/saltybot_bringup/vo_drift_node.py b/jetson/ros2_ws/src/saltybot_bringup/saltybot_bringup/vo_drift_node.py
new file mode 100644
index 0000000..aae8735
--- /dev/null
+++ b/jetson/ros2_ws/src/saltybot_bringup/saltybot_bringup/vo_drift_node.py
@@ -0,0 +1,150 @@
+"""
+vo_drift_node.py — Visual odometry drift detector (Issue #260).
+
+Compares the cumulative path lengths of visual odometry and wheel odometry
+over a sliding window.  When the absolute difference exceeds the configured
+threshold the node flags drift, allowing the system to warn operators,
+inflate VO covariance, or fall back to wheel-only localisation.
+
+Subscribes (BEST_EFFORT):
+  /camera/odom            nav_msgs/Odometry   visual odometry
+  /odom                   nav_msgs/Odometry   wheel odometry
+
+  → For this robot remap to /saltybot/visual_odom + /saltybot/rover_odom.
+
+Publishes:
+  /saltybot/vo_drift_detected   std_msgs/Bool     True while drifting
+  /saltybot/vo_drift_magnitude  std_msgs/Float32  drift magnitude (metres)
+
+Parameters
+----------
+vo_topic           str    /camera/odom       Visual odometry source topic
+wheel_topic        str    /odom              Wheel odometry source topic
+drift_threshold_m  float  0.5                Drift flag threshold (metres)
+window_s           float  10.0               Comparison window (seconds)
+publish_hz         float  2.0                Output publication rate (Hz)
+max_buffer_age_s   float  30.0               Max age of stored samples (s)
+"""
+
+from __future__ import annotations
+
+import time
+
+import rclpy
+from rclpy.node import Node
+from rclpy.qos import QoSProfile, ReliabilityPolicy, HistoryPolicy
+
+from nav_msgs.msg import Odometry
+from std_msgs.msg import Bool, Float32
+
+from ._vo_drift import OdomBuffer, OdomSample, compute_drift
+
+
+_SENSOR_QOS = QoSProfile(
+    reliability=ReliabilityPolicy.BEST_EFFORT,
+    history=HistoryPolicy.KEEP_LAST,
+    depth=4,
+)
+
+
+class VoDriftNode(Node):
+
+    def __init__(self) -> None:
+        super().__init__('vo_drift_node')
+
+        self.declare_parameter('vo_topic',          '/camera/odom')
+        self.declare_parameter('wheel_topic',       '/odom')
+        self.declare_parameter('drift_threshold_m', 0.5)
+        self.declare_parameter('window_s',          10.0)
+        self.declare_parameter('publish_hz',        2.0)
+        self.declare_parameter('max_buffer_age_s',  30.0)
+
+        vo_topic       = self.get_parameter('vo_topic').value
+        wheel_topic    = self.get_parameter('wheel_topic').value
+        self._thresh   = self.get_parameter('drift_threshold_m').value
+        self._window_s = self.get_parameter('window_s').value
+        publish_hz     = self.get_parameter('publish_hz').value
+        max_age        = self.get_parameter('max_buffer_age_s').value
+
+        self._vo_buf    = OdomBuffer(max_age_s=max_age)
+        self._wheel_buf = OdomBuffer(max_age_s=max_age)
+
+        self.create_subscription(
+            Odometry, vo_topic, self._on_vo, _SENSOR_QOS)
+        self.create_subscription(
+            Odometry, wheel_topic, self._on_wheel, _SENSOR_QOS)
+
+        self._pub_detected  = self.create_publisher(
+            Bool,    '/saltybot/vo_drift_detected',   10)
+        self._pub_magnitude = self.create_publisher(
+            Float32, '/saltybot/vo_drift_magnitude',  10)
+
+        self.create_timer(1.0 / publish_hz, self._tick)
+
+        self.get_logger().info(
+            f'vo_drift_node ready — '
+            f'vo={vo_topic} wheel={wheel_topic} '
+            f'threshold={self._thresh}m window={self._window_s}s'
+        )
+
+    # ── Callbacks ─────────────────────────────────────────────────────────────
+
+    def _on_vo(self, msg: Odometry) -> None:
+        s = _odom_to_sample(msg)
+        self._vo_buf.push(s)
+
+    def _on_wheel(self, msg: Odometry) -> None:
+        s = _odom_to_sample(msg)
+        self._wheel_buf.push(s)
+
+    # ── Publish tick ──────────────────────────────────────────────────────────
+
+    def _tick(self) -> None:
+        now    = time.monotonic()
+        result = compute_drift(
+            self._vo_buf, self._wheel_buf,
+            window_s=self._window_s,
+            drift_threshold_m=self._thresh,
+            now=now,
+        )
+
+        if result.is_drifting:
+            self.get_logger().warn(
+                f'VO drift detected: {result.drift_m:.3f}m '
+                f'(vo={result.vo_path_m:.3f}m wheel={result.wheel_path_m:.3f}m '
+                f'over {result.window_s:.1f}s)',
+                throttle_duration_sec=5.0,
+            )
+
+        det_msg = Bool()
+        det_msg.data = result.is_drifting
+        self._pub_detected.publish(det_msg)
+
+        mag_msg = Float32()
+        mag_msg.data = float(result.drift_m)
+        self._pub_magnitude.publish(mag_msg)
+
+
+# ── Helpers ───────────────────────────────────────────────────────────────────
+
+def _odom_to_sample(msg: Odometry) -> OdomSample:
+    """Convert nav_msgs/Odometry to OdomSample using monotonic clock."""
+    return OdomSample(
+        t=time.monotonic(),
+        x=msg.pose.pose.position.x,
+        y=msg.pose.pose.position.y,
+    )
+
+
+def main(args=None) -> None:
+    rclpy.init(args=args)
+    node = VoDriftNode()
+    try:
+        rclpy.spin(node)
+    finally:
+        node.destroy_node()
+        rclpy.shutdown()
+
+
+if __name__ == '__main__':
+    main()
diff --git a/jetson/ros2_ws/src/saltybot_bringup/setup.py b/jetson/ros2_ws/src/saltybot_bringup/setup.py
index 3b2b609..01a3191 100644
--- a/jetson/ros2_ws/src/saltybot_bringup/setup.py
+++ b/jetson/ros2_ws/src/saltybot_bringup/setup.py
@@ -35,6 +35,8 @@ setup(
             'lidar_clustering        = saltybot_bringup.lidar_clustering_node:main',
             # Floor surface type classifier (Issue #249)
             'floor_classifier        = saltybot_bringup.floor_classifier_node:main',
+            # Visual odometry drift detector (Issue #260)
+            'vo_drift_detector       = saltybot_bringup.vo_drift_node:main',
         ],
     },
 )
diff --git a/jetson/ros2_ws/src/saltybot_bringup/test/test_vo_drift.py b/jetson/ros2_ws/src/saltybot_bringup/test/test_vo_drift.py
new file mode 100644
index 0000000..d89f2bb
--- /dev/null
+++ b/jetson/ros2_ws/src/saltybot_bringup/test/test_vo_drift.py
@@ -0,0 +1,297 @@
+"""
+test_vo_drift.py — Unit tests for VO drift detector helpers (no ROS2 required).
+
+Covers:
+  OdomBuffer:
+    - push/len
+    - window returns only samples within cutoff
+    - old samples are evicted beyond max_age_s
+    - clear empties the buffer
+    - window on empty buffer returns empty list
+
+  _path_length (via compute_drift with crafted samples):
+    - stationary source → path = 0
+    - straight-line motion → path = total distance
+    - L-shaped path → path = sum of two legs
+
+  compute_drift:
+    - both empty → DriftResult with zeros, is_drifting=False
+    - one buffer < 2 samples → zero drift
+    - both move same distance → drift ≈ 0, not drifting
+    - VO moves 1m, wheel moves 0.5m → drift = 0.5m
+    - drift == threshold → is_drifting=True (>=)
+    - drift < threshold → is_drifting=False
+    - drift > threshold → is_drifting=True
+    - path lengths in result match expectation
+    - n_vo / n_wheel counts correct
+    - samples outside window ignored
+    - window_s in result reflects actual data span
+"""
+
+import sys
+import os
+import math
+
+import pytest
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))
+
+from saltybot_bringup._vo_drift import (
+    OdomSample,
+    OdomBuffer,
+    DriftResult,
+    compute_drift,
+    _path_length,
+)
+
+
+# ── Helpers ───────────────────────────────────────────────────────────────────
+
+def _s(t, x, y) -> OdomSample:
+    return OdomSample(t=t, x=x, y=y)
+
+
+def _straight_buf(n=5, speed=0.1, t_start=0.0, dt=1.0,
+                  max_age_s=30.0) -> OdomBuffer:
+    """n samples moving along +x at `speed` m/s."""
+    buf = OdomBuffer(max_age_s=max_age_s)
+    for i in range(n):
+        buf.push(_s(t_start + i * dt, x=i * speed * dt, y=0.0))
+    return buf
+
+
+def _stationary_buf(n=5, t_start=0.0, dt=1.0,
+                    max_age_s=30.0) -> OdomBuffer:
+    buf = OdomBuffer(max_age_s=max_age_s)
+    for i in range(n):
+        buf.push(_s(t_start + i * dt, x=0.0, y=0.0))
+    return buf
+
+
+# ── OdomBuffer ────────────────────────────────────────────────────────────────
+
+class TestOdomBuffer:
+
+    def test_push_increases_len(self):
+        buf = OdomBuffer()
+        assert len(buf) == 0
+        buf.push(_s(0.0, 0.0, 0.0))
+        assert len(buf) == 1
+
+    def test_window_returns_all_within_cutoff(self):
+        buf = OdomBuffer(max_age_s=30.0)
+        for t in [0.0, 5.0, 10.0]:
+            buf.push(_s(t, 0.0, 0.0))
+        samples = buf.window(window_s=10.0, now=10.0)
+        assert len(samples) == 3
+
+    def test_window_excludes_old_samples(self):
+        buf = OdomBuffer(max_age_s=30.0)
+        for t in [0.0, 5.0, 15.0]:
+            buf.push(_s(t, 0.0, 0.0))
+        # window=5s from now=15 → only t=15 qualifies (t>=10)
+        samples = buf.window(window_s=5.0, now=15.0)
+        assert len(samples) == 1
+        assert samples[0].t == 15.0
+
+    def test_evicts_samples_beyond_max_age(self):
+        buf = OdomBuffer(max_age_s=5.0)
+        buf.push(_s(0.0, 0.0, 0.0))
+        buf.push(_s(10.0, 1.0, 0.0))  # now=10 → t=0 is 10s old > 5s max
+        assert len(buf) == 1
+
+    def test_clear_empties_buffer(self):
+        buf = _straight_buf(n=5)
+        buf.clear()
+        assert len(buf) == 0
+
+    def test_window_on_empty_buffer(self):
+        buf = OdomBuffer()
+        assert buf.window(window_s=10.0, now=100.0) == []
+
+    def test_window_boundary_inclusive(self):
+        """Sample exactly at window cutoff (t == now - window_s) is included."""
+        buf = OdomBuffer(max_age_s=30.0)
+        buf.push(_s(0.0, 0.0, 0.0))
+        # window=10, now=10 → cutoff=0.0, sample at t=0.0 should be included
+        samples = buf.window(window_s=10.0, now=10.0)
+        assert len(samples) == 1
+
+
+# ── _path_length ──────────────────────────────────────────────────────────────
+
+class TestPathLength:
+
+    def test_stationary_path_zero(self):
+        samples = [_s(i, 0.0, 0.0) for i in range(5)]
+        assert _path_length(samples) == pytest.approx(0.0)
+
+    def test_unit_step_path(self):
+        samples = [_s(0, 0.0, 0.0), _s(1, 1.0, 0.0)]
+        assert _path_length(samples) == pytest.approx(1.0)
+
+    def test_two_unit_steps(self):
+        samples = [_s(0, 0.0, 0.0), _s(1, 1.0, 0.0), _s(2, 2.0, 0.0)]
+        assert _path_length(samples) == pytest.approx(2.0)
+
+    def test_diagonal_step(self):
+        # (0,0) → (1,1): distance = sqrt(2)
+        samples = [_s(0, 0.0, 0.0), _s(1, 1.0, 1.0)]
+        assert _path_length(samples) == pytest.approx(math.sqrt(2))
+
+    def test_l_shaped_path(self):
+        # Right 3m then up 4m → total path = 7m (not hypotenuse)
+        samples = [_s(0, 0.0, 0.0), _s(1, 3.0, 0.0), _s(2, 3.0, 4.0)]
+        assert _path_length(samples) == pytest.approx(7.0)
+
+    def test_single_sample_returns_zero(self):
+        assert _path_length([_s(0, 5.0, 5.0)]) == pytest.approx(0.0)
+
+    def test_empty_returns_zero(self):
+        assert _path_length([]) == pytest.approx(0.0)
+
+
+# ── compute_drift ─────────────────────────────────────────────────────────────
+
+class TestComputeDrift:
+
+    def test_both_empty_returns_zero_drift(self):
+        result = compute_drift(
+            OdomBuffer(), OdomBuffer(),
+            window_s=10.0, drift_threshold_m=0.5, now=10.0)
+        assert result.drift_m == pytest.approx(0.0)
+        assert not result.is_drifting
+
+    def test_one_buffer_empty_returns_zero(self):
+        vo = _straight_buf(n=5, speed=0.1)
+        result = compute_drift(
+            vo, OdomBuffer(),
+            window_s=10.0, drift_threshold_m=0.5, now=5.0)
+        assert result.drift_m == pytest.approx(0.0)
+        assert not result.is_drifting
+
+    def test_one_buffer_single_sample_returns_zero(self):
+        vo    = _straight_buf(n=5, speed=0.1)
+        wheel = OdomBuffer()
+        wheel.push(_s(0.0, 0.0, 0.0))   # only 1 sample
+        result = compute_drift(
+            vo, wheel,
+            window_s=10.0, drift_threshold_m=0.5, now=5.0)
+        assert result.drift_m == pytest.approx(0.0)
+        assert not result.is_drifting
+
+    def test_both_move_same_distance_zero_drift(self):
+        # Both move 0.1 m/s for 4 steps → 0.4 m each
+        vo    = _straight_buf(n=5, speed=0.1, dt=1.0)
+        wheel = _straight_buf(n=5, speed=0.1, dt=1.0)
+        result = compute_drift(
+            vo, wheel,
+            window_s=10.0, drift_threshold_m=0.5, now=5.0)
+        assert result.drift_m == pytest.approx(0.0, abs=1e-9)
+        assert not result.is_drifting
+
+    def test_both_stationary_zero_drift(self):
+        vo    = _stationary_buf(n=5)
+        wheel = _stationary_buf(n=5)
+        result = compute_drift(
+            vo, wheel,
+            window_s=10.0, drift_threshold_m=0.5, now=5.0)
+        assert result.drift_m == pytest.approx(0.0)
+        assert not result.is_drifting
+
+    def test_drift_equals_path_length_difference(self):
+        # VO moves 1.0 m total, wheel moves 0.5 m total
+        vo    = _straight_buf(n=11, speed=0.1, dt=1.0)   # 10 steps × 0.1 = 1.0m
+        wheel = _straight_buf(n=11, speed=0.05, dt=1.0)  # 10 steps × 0.05 = 0.5m
+        result = compute_drift(
+            vo, wheel,
+            window_s=15.0, drift_threshold_m=0.5, now=11.0)
+        assert result.vo_path_m    == pytest.approx(1.0, abs=1e-9)
+        assert result.wheel_path_m == pytest.approx(0.5, abs=1e-9)
+        assert result.drift_m      == pytest.approx(0.5, abs=1e-9)
+
+    def test_drift_at_threshold_is_drifting(self):
+        # drift == 0.5 → is_drifting = True  (>= threshold)
+        vo    = _straight_buf(n=11, speed=0.1,  dt=1.0)
+        wheel = _straight_buf(n=11, speed=0.05, dt=1.0)
+        result = compute_drift(
+            vo, wheel,
+            window_s=15.0, drift_threshold_m=0.5, now=11.0)
+        assert result.is_drifting
+
+    def test_drift_below_threshold_not_drifting(self):
+        vo    = _straight_buf(n=11, speed=0.1,  dt=1.0)
+        wheel = _straight_buf(n=11, speed=0.08, dt=1.0)
+        result = compute_drift(
+            vo, wheel,
+            window_s=15.0, drift_threshold_m=0.5, now=11.0)
+        # drift = |1.0 - 0.8| = 0.2
+        assert result.drift_m == pytest.approx(0.2, abs=1e-9)
+        assert not result.is_drifting
+
+    def test_drift_above_threshold_is_drifting(self):
+        vo    = _straight_buf(n=11, speed=0.1,  dt=1.0)
+        wheel = _stationary_buf(n=11, dt=1.0)
+        result = compute_drift(
+            vo, wheel,
+            window_s=15.0, drift_threshold_m=0.5, now=11.0)
+        # drift = |1.0 - 0.0| = 1.0 > 0.5
+        assert result.drift_m > 0.5
+        assert result.is_drifting
+
+    def test_n_vo_n_wheel_counts(self):
+        vo    = _straight_buf(n=8, dt=1.0)
+        wheel = _straight_buf(n=5, dt=1.0)
+        result = compute_drift(
+            vo, wheel,
+            window_s=15.0, drift_threshold_m=0.5, now=8.0)
+        assert result.n_vo    == 8
+        assert result.n_wheel == 5
+
+    def test_samples_outside_window_ignored(self):
+        # Push old samples far in the past; should not contribute to window
+        vo    = OdomBuffer(max_age_s=60.0)
+        wheel = OdomBuffer(max_age_s=60.0)
+        # Old samples outside window (t=0..4, window is last 3s from now=10)
+        for t in range(5):
+            vo.push(_s(float(t), x=float(t), y=0.0))
+            wheel.push(_s(float(t), x=float(t), y=0.0))
+        # Recent samples inside window (t=7..10)
+        for t in range(7, 11):
+            vo.push(_s(float(t), x=float(t) * 0.1, y=0.0))
+            wheel.push(_s(float(t), x=float(t) * 0.1, y=0.0))
+
+        result = compute_drift(
+            vo, wheel,
+            window_s=3.0, drift_threshold_m=0.5, now=10.0)
+        # Both sources move identically inside window → zero drift
+        assert result.drift_m == pytest.approx(0.0, abs=1e-9)
+        # Only the 4 recent samples (t=7,8,9,10) in window
+        assert result.n_vo    == 4
+        assert result.n_wheel == 4
+
+    def test_result_is_namedtuple(self):
+        result = compute_drift(
+            _straight_buf(), _straight_buf(),
+            window_s=10.0, drift_threshold_m=0.5, now=5.0)
+        assert hasattr(result, 'drift_m')
+        assert hasattr(result, 'vo_path_m')
+        assert hasattr(result, 'wheel_path_m')
+        assert hasattr(result, 'is_drifting')
+        assert hasattr(result, 'window_s')
+        assert hasattr(result, 'n_vo')
+        assert hasattr(result, 'n_wheel')
+
+    def test_wheel_faster_than_vo_still_drifts(self):
+        """Drift is absolute difference — direction doesn't matter."""
+        vo    = _stationary_buf(n=11, dt=1.0)
+        wheel = _straight_buf(n=11, speed=0.1, dt=1.0)
+        result = compute_drift(
+            vo, wheel,
+            window_s=15.0, drift_threshold_m=0.5, now=11.0)
+        assert result.drift_m == pytest.approx(1.0, abs=1e-9)
+        assert result.is_drifting
+
+
+if __name__ == '__main__':
+    pytest.main([__file__, '-v'])