Test a rover’s navigation as a pipeline, not as one feature. A reliable sequence is: establish a known software and hardware baseline, verify coordinate frames and timing, validate sensors and odometry, confirm localization and map or costmap data, test path planning, test path following, and then exercise obstacle avoidance in controlled scenarios. This order tells you whether a failure starts in perception, state estimation, planning, control, or the recovery behavior that connects them.
Begin in an empty, repeatable environment and record every result. Then add static obstacles, constrained passages, and—when the sensor and operating area permit—obstacles introduced while the rover is moving. Simulation can make these cases repeatable, but only supervised physical trials reveal mounting errors, drivetrain behavior, latency, traction, and other platform-specific effects.
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Understand the navigation pipeline before changing parameters
A typical ROS 2 navigation stack coordinates several functions. Sensors produce observations; transforms place those observations in a common coordinate system; odometry and localization estimate the rover’s pose; a map and costmaps represent free space and hazards; a planner generates a route; a controller converts that route into motion commands; and a behavior tree coordinates planning, control, and recovery.
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Debug in dependency order. Do not tune velocity limits while sensor messages have incorrect frame IDs, and do not judge obstacle avoidance until the obstacle is visible in the costmap at the correct position.
Establish a known baseline
Record the exact configuration before each test session. This turns a vague “it worked yesterday” report into a reproducible experiment and makes a later change attributable.
| Item to record | Why it matters |
|---|---|
| Rover model, dimensions and wheel configuration | Footprint, turning behavior and actuator limits depend on the physical platform. |
| ROS 2 distribution and Nav2 branch or version | Parameter names, lifecycle behavior and example configurations can vary by release. |
| Simulator and world, if used | World geometry, physics and sensor plugins affect repeatability. |
| Sensor hardware, driver versions and mounting locations | Range, update rate, field of view, latency and frame transforms are hardware-specific. |
| Map, map metadata and launch parameters | A different map or parameter file can change route availability and obstacle inflation. |
| Controller, planner, costmap and recovery parameters | These settings determine how paths are generated, followed and abandoned. |
| Test surface, battery state and payload | Traction, motor response and stopping behavior can change with physical conditions. |
The current Nav2 first-time setup documentation uses Gazebo Harmonic or newer and ROS 2 Jazzy or newer for its examples. Treat that as the guide’s stated context, not as proof that every other simulator or ROS 2 distribution is unsupported; use instructions matching your actual versions.
Verify robot description, coordinate frames and timing
Coordinate-frame errors are among the fastest ways to make navigation look irrational. Nav2’s minimum documented chain is map → odom → base_link → sensor frames. Every transform in that chain must exist, have the expected direction, and update with usable timestamps.
- Check the robot model. Confirm that the description matches the rover’s wheelbase, body outline, sensor height and sensor orientation. An incorrect model can make a clear path appear to collide or make the costmap underestimate clearance.
- Inspect the complete transform tree. Follow the chain from
maptoodom, then tobase_link, and from there to each camera, depth and ranging frame. Look for disconnected frames, reversed axes, unexpected rotations or transforms that stop updating. - Compare message frame IDs. The frame named in each sensor message must be the frame that is physically producing the data. A correct transform is useless if a driver publishes a different frame name.
- Check timestamps and clock behavior. Sensor data, transforms and odometry need compatible times. Delayed or future-dated messages can be rejected or projected into the wrong pose, especially while the rover is turning.
- Confirm transform ownership. In one documented Rover Robotics workflow, robot localization supplies
base_link→odom, while Slam Toolbox suppliesodom→map. That assignment is an example for that project, not a universal Nav2 rule; your stack must have one coherent source for each required transform.
When a sensor cloud or scan appears shifted relative to the rover or map, fix mounting transforms, frame IDs and timing before changing planner settings. Also verify range limits and the configured footprint, because either can create an apparently misplaced obstacle.
Validate sensors, odometry and localization separately
Sensor sanity checks
- Place a known object at a measured distance and verify that the displayed range and bearing are plausible.
- Rotate the rover in place and confirm that the sensor view rotates around the intended mounting point rather than orbiting from an incorrect offset.
- Move an object through the field of view and check that observations arrive at the expected rate without long gaps.
- Compare live observations with the robot model and map. Persistent offsets usually indicate a transform, timestamp or mounting problem.
Odometry checks
Command a short straight motion and then a controlled turn. Wheel odometry should change in the correct direction and at a scale consistent with the distance traveled. Check left-right sign conventions, wheel radius, wheel separation and encoder counts. If the estimated pose drifts dramatically during a short test, do not compensate by loosening goal tolerances; first correct the odometry source or its calibration.
Localization checks
Watch whether localization follows the rover smoothly as it moves through recognizable map features. Sudden jumps, a pose that freezes, or a pose that slowly slides away from the physical rover can invalidate both global planning and local obstacle placement. Compare the estimated pose with visual landmarks or measured floor distances, and record when the error appears: at startup, after a turn, after sensor occlusion, or when the rover crosses a feature-poor area.
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Nav2 does not require lidar. Its documented state-estimation guidance allows vision- or depth-based positioning and other collision-avoidance sensors when they are integrated correctly. Test the modality actually installed on the rover rather than assuming a lidar-specific procedure.
Check the map, footprint and costmaps
A planner can only avoid what the environmental representation contains. Verify that the static map is the intended map and that its origin, resolution and orientation agree with the physical test area. In the Rover Robotics example, the Nav2 map configuration uses an absolute map path without an extension and expects the related Slam Toolbox map files to be available; those conventions belong to that project and should not be generalized to every installation.
Inspect both global and local costmaps while the rover is stationary and while it moves:
- Is a known wall or box represented at the correct position?
- Does the obstacle persist for the expected time, or does it disappear because of clearing or sensor-range settings?
- Does inflation leave a clearance margin appropriate for the rover’s actual body, not just its wheel centers?
- Does the local costmap cover enough distance for the rover’s speed and stopping time?
- When a previously blocked area becomes clear, does the representation update and allow replanning?
If the costmap shows an obstacle in the wrong place, stop there. Planner and controller tuning cannot reliably fix a geometric representation error.
Separate planning failures from control failures
Test path generation first
Use a clear, simple environment and a reachable goal. Observe whether a global path is produced and whether it stays in free space. If no path appears, or the path crosses an occupied area, investigate map and costmap inputs, the robot footprint, planner configuration and the availability of the required transforms. A goal outside the mapped or permitted area may be invalid even when the rover is operating correctly.
Then test path following
With a plausible path visible, watch the rover’s actual motion. It should advance in the commanded direction, make turns without sustained oscillation, and stop within the configured goal tolerance. If the path looks reasonable but the rover stalls, veers, oscillates or overshoots, inspect the controller, odometry, footprint, velocity and acceleration limits, and the mapping from velocity commands to motor output.
Use new goals and replanning to expose state errors
Send goals in different directions after the rover has moved. A rover that follows the first path but fails after a turn may have accumulated odometry error or a transform timing problem. A rover that reaches the goal but cannot accept the next one may have a lifecycle, localization or recovery-state issue rather than a path-following problem.
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Nav2 divides navigation into planners, controllers, environmental representation and execution coordinated by behavior trees. Use that division as a diagnostic map, while remembering that a single symptom can have several causes.
Exercise obstacle avoidance with a controlled test course
Build a course that can be reset to the same starting pose and obstacle locations. Record the rover’s speed, sensor modality, goal, route choice, clearance and recovery result for each run. The following cases isolate progressively harder behaviors.
Case 1: Empty route
Place no obstacle between the start and a reachable goal. Confirm that the rover plans a route, follows it without unnecessary detours and stops within the configured tolerance. This establishes that obstacle behavior is not being confused with a basic planning or control failure.
Case 2: Static obstacle on the direct route
Put a box or barrier directly between the rover and the goal. Confirm all of the following:
- The obstacle appears in the relevant costmap at the correct location.
- The global or local path changes rather than continuing through the occupied cells.
- The rover maintains clearance around the obstacle based on its real footprint.
- The rover resumes progress after passing the obstacle instead of circling indefinitely.
Case 3: Narrow but passable passage
Use a corridor with known clearance. The rover should reject a passage that is physically too narrow, and it should use a safe route when the measured clearance exceeds the configured footprint and margin. This case exposes an undersized footprint, excessive inflation, poor localization or controller turning limits.
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Surround the goal or block every available corridor. The correct result is not an increasingly aggressive maneuver. The rover should stop, declare that progress is unavailable, or invoke a configured recovery behavior. Record whether it waits safely, backs away only when that motion is permitted, and becomes ready for a new goal after the obstruction is removed.
Case 5: Obstacle introduced during motion
If the sensor and operating context support it, place an object into the rover’s path while it is moving. Check detection latency, braking or stopping behavior, local replanning, and the response to an object that moves across the planned path. Nav2 requirements describe avoiding moving objects that intercept the robot’s path, but those requirements do not prove that a particular rover meets them. Set acceptance limits for your platform before running this test.
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Case 6: Keepout and speed-restricted areas
Mark an area that must not be entered and another where speed must be reduced. Nav2 system-test examples include keepout and speed-restricted zones. Verify that the rover respects the representation, plans around prohibited cells, and changes speed where the restriction applies.
Use layered tests instead of only end-to-end runs
Nav2 system testing illustrates three useful levels: component, subsystem and full-system integration. Run them in that order so a failure has a narrow search area.
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| Level | What to isolate | Example evidence |
|---|---|---|
| Component | One driver, transform source, odometry source, planner or controller | Messages arrive with correct frame IDs and timing; a planner produces a path for a fixed map and pose. |
| Subsystem | Coupled functions such as localization plus mapping, or costmap plus sensor input | A known obstacle appears in the correct place and remains synchronized with rover motion. |
| Full system | Localization, mapping, planning, control and recovery together | Pose navigation, waypoint following, generated path planning and lifecycle transitions complete safely. |
Use the same start pose, goal, map and obstacle arrangement when comparing software changes. A test that changes several variables at once may demonstrate a different outcome without explaining why.
Move from simulation to supervised rover trials
Gazebo and RViz examples in the Nav2 setup documentation provide a practical starting point for repeatable integration checks. Simulation is especially useful for lifecycle transitions, waypoint sequences, generated paths, keepout zones and repeatable obstacle placement. It lets you replay the same geometry while inspecting transforms, maps and plans.
Simulation does not establish that the physical rover will behave identically. Real trials add wheel slip, uneven floors, motor dead zones, sensor vibration, lighting changes, wireless delays, mechanical flex and differences between the modeled and actual footprint. Repeat the most important simulated cases on the real rover in a controlled, supervised area.
- Limit speed and energy, and keep an emergency stop within reach.
- Run first with no bystanders and with a clear boundary around the test area.
- Begin with the empty route, then add one static obstacle before attempting dynamic cases.
- Have a person ready to remove power or stop motion if the rover leaves the expected corridor.
- Repeat a scenario after every hardware, driver, transform or parameter change.
The available documentation provides example scenarios, not a universal pass threshold or proof of simulation-to-reality equivalence. Define stopping distance, minimum clearance, localization error, route-completion and recovery criteria for your own rover.
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Choose a sensor approach by integration, not by assumption
Lidar is one possible input for mapping, localization and collision avoidance, but it is optional in Nav2. Vision, depth and other sensors can support the same functions when their drivers, frames, timestamps, range limits and failure behavior are appropriate.
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| Decision factor | Questions to answer |
|---|---|
| Operating conditions | Does the modality work in the lighting, texture, dust, weather and range found in the test area? |
| Geometry | Is the field of view wide enough, and is the mounting position protected from vibration and occlusion? |
| ROS integration | Does a maintained driver publish the required message type, frame ID, timestamps and diagnostics for your ROS 2 distribution? |
| Navigation role | Will the sensor provide localization, mapping, local obstacle data, or more than one of these? |
| Failure behavior | Can the rover detect missing, stale or degraded data and stop or recover safely? |
Do not select a sensor solely because it is common on another rover. Compatibility with the robot description, mounting, driver and navigation configuration matters more than the category name.
Record evidence and diagnose by symptom
For every run, save the software versions, parameter set, map, start pose, goal, obstacle layout, battery state, speed limit and outcome. Capture synchronized views of the rover model, transforms, sensor data, global path, local path and costmaps. Note the first moment the behavior diverges from expectation; later symptoms may only be consequences.
| Observed symptom | First checks |
|---|---|
| No path to an apparently reachable goal | Map bounds, costmap occupancy, footprint, goal frame, required transforms and planner configuration. |
| Path crosses a visible obstacle | Sensor frame and timestamp, costmap update and clearing, obstacle range limits, map alignment and inflation. |
| Rover follows a good path but oscillates | Controller settings, odometry direction and scale, velocity limits, actuator mapping and footprint. |
| Rover stops far from the goal | Goal tolerance, localization estimate, controller output and whether the goal is expressed in the expected frame. |
| Pose jumps or slowly drifts | Wheel calibration, localization inputs, transform timing, sensor mounting and map-to-odom consistency. |
| Obstacle is detected late or not at all | Sensor health, field of view, frame ID, timestamps, range limits, update rate and local-costmap coverage. |
| Rover cannot recover after a blocked route | Behavior-tree state, lifecycle state, recovery configuration, available free space and whether a new goal resets the relevant state. |
Change one related setting at a time, rerun the same scenario and keep the previous result. A parameter change that improves one corridor but causes unsafe clearance elsewhere is not a complete fix.
Define safety acceptance criteria before declaring success
“It reached the goal once” is not enough. Write criteria that match the rover and environment, such as:
- Every required transform remains available and timely for the entire run.
- Localization stays within a specified positional and angular error for the test area.
- The rover maintains a defined minimum clearance from static and moving obstacles.
- The rover stops within a defined distance when no safe path exists or an obstacle appears.
- Goals, waypoints, keepout zones and speed restrictions produce the expected behavior.
- A sensor outage, stale message or localization failure leads to a safe state rather than uncontrolled motion.
- The result is repeatable across a stated number of runs, surfaces and battery conditions.
These are project acceptance criteria, not published universal Nav2 benchmarks. State the measurement method and test conditions beside each limit so another operator can reproduce them.
A compact debugging workflow
- Freeze the baseline: save versions, maps, parameters, hardware details and the exact scenario.
- Prove the frame chain: verify
map→odom→base_link→ sensor frames, message IDs and timestamps. - Prove perception and state: validate sensor geometry, odometry direction and localization continuity.
- Prove representation: confirm maps, footprints and costmaps match measured reality.
- Prove planning: generate a path to a reachable goal in a clear environment.
- Prove control: follow that path, turn, stop and accept a new goal.
- Prove avoidance: run static, narrow-passage, blocked-route and appropriate dynamic-obstacle cases.
- Repeat physically: reproduce the key simulations on the rover under supervision and compare evidence, not assumptions.
This sequence minimizes guesswork: each stage establishes the inputs required by the next one, and each failure points to a smaller set of causes.
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