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Engineers plan a Mars rover’s route in layers: people on Earth choose the destination, science stops, broad path, and no-go areas; the rover then uses stereo cameras, terrain maps, localization sensors, and onboard software to avoid hazards that could not be resolved from orbit. Because Mars is too far away for practical joystick control, commands are prepared, tested, and transmitted ahead of time.
That division of labor is the key to safe driving. Orbital images support the long-range plan, while the rover’s own cameras and computers make local adjustments around rocks, slopes, sand, wheel-drop hazards, and ground that could strike the underside.
What route planning has to accomplish
A route is not simply the shortest line between the rover and a landmark. It must advance the mission’s science objectives while keeping the vehicle within its mobility limits and preserving opportunities to stop, inspect rocks, drill, or collect samples. A route may therefore include deliberate detours to a geologically valuable outcrop or a safe position for an instrument.
Ground teams work from Earth because the communication delay between the planets prevents continuous manual steering. They build a sequence of activities and driving commands, send it to Mars, and wait for telemetry and images showing what happened. The rover can react locally during a drive, but it does not independently choose the mission’s destination or science priorities.
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NASA’s descriptions of Curiosity and Perseverance show a layered system:
- Human planning: select destinations, science targets, broad corridors, waypoints, and keep-out zones.
- Orbital mapping: provide the regional view of slopes, surface patterns, and possible routes.
- Rover perception: use stereo navigation cameras to build a close-range, three-dimensional view.
- Onboard navigation: score candidate paths, avoid hazards, and adjust the local trajectory.
- Verification on Earth: test the command sequence and check telemetry limits before uplink.
Each layer covers a different uncertainty. A high-resolution orbital image can reveal a promising valley but cannot reliably show every small rock or depression that could stop a wheel. Conversely, the rover can see a nearby obstacle but cannot use its local map to plan an entire expedition without the strategic choices made by the ground team.
Step 1: Choose the destination and science stops
Route design begins with the reason for driving. Scientists and engineers identify a feature worth examining, a sampling location, or a position that enables the next phase of the mission. The planning team then asks whether the rover can reach it with acceptable risk and whether the approach provides useful intermediate stops.
Science changes the route
A technically easy route may be rejected if it bypasses the most valuable geology. A more difficult route can be worthwhile when it reaches an outcrop or preserves a sampling opportunity. The plan therefore combines science activities, instrument pointing, communications, energy use, and mobility rather than treating driving as an isolated task.
Humans define the strategic boundary
Mission specialists decide which broad corridor to follow and which areas are forbidden. Onboard autonomy is designed to execute and refine those decisions, not to replace them with an unsupervised choice of mission objective.
Step 2: Build a terrain picture from orbit and from the rover
Long-range planning starts with orbital observations. For NASA’s December 2025 Perseverance generative-AI route-planning demonstration, the inputs included high-resolution HiRISE imagery from the Mars Reconnaissance Orbiter and slope information derived from digital elevation models. Those data helped identify bedrock, outcrops, boulder fields, and sand ripples before a drive was commanded.
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Orbital data are valuable because they cover much more ground than the rover can see. They also have limits: image resolution, viewing angle, shadows, and the inability to expose every small step or loose patch mean that a route can look safe from above and still require a local detour.
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Navigation cameras take images from separated viewpoints. Software matches features between the images to estimate depth and construct a local digital elevation model. Perseverance uses this three-dimensional representation to evaluate possible paths around obstacles while it drives. Curiosity likewise uses stereo images to identify large vertical steps, steep slopes, and excessive roughness.
This is why a rover does not rely on a single map. Orbital maps support the regional route; rover imagery supplies the close-range evidence needed to commit each wheel to a particular patch of ground.
Step 3: Convert the route into waypoints and constraints
Human planners express a broad drive as a sequence of waypoints and constraints. NASA reports that conventional rover plans usually place waypoints no more than 330 feet (100 meters) apart. The spacing gives the rover a series of intended positions while leaving room for onboard navigation to adjust the path between them.
Keep-out zones and approach limits
Planners can mark areas that the rover must not enter, such as steep terrain, suspected sand, a boulder field, or a region where the underside could touch the ground. A waypoint can also define a safe approach to a science target rather than requiring the rover to drive directly to the feature’s center.
Why a waypoint is not a railroad track
A waypoint specifies the intended destination, not every turn of the wheels. Between waypoints, the rover evaluates the terrain it can actually see. If a newly detected rock or drop makes the nominal line unsafe, local navigation can choose another path that still makes progress toward the assigned goal.
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Step 4: Check the hazards that can stop or damage a rover
Safe planning has to account for more than conspicuous boulders. The hazard model includes the shape of the ground, the rover’s geometry, and how the wheels interact with the surface.
Slope and roughness
Steep slopes can exceed a rover’s mobility limits or create a rollover risk. Rough, uneven terrain can impose shocks and twists even when no single rock looks large. Curiosity’s autonomous checks identify steep slopes and excessive roughness from stereo imagery.
Vertical steps and wheel drops
A ledge may be climbable from one direction but dangerous from another. A wheel drop occurs when a wheel descends into a depression or over an edge beyond the vehicle’s permitted geometry. In NASA’s AutoNav animation for a July 15, 2023 Perseverance drive, candidate paths were flagged when a wheel drop exceeded 14 inches (35 centimeters).
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Rocks can block a wheel, damage hardware, or force a turn into a worse hazard. Sand ripples may look smooth but can reduce traction or trap a vehicle. Boulder fields create a combination of narrow passages, uneven wheel contacts, and limited sight lines. The rover’s local map evaluates these features together rather than treating “rock detected” as the only failure condition.
Belly-pan clearance
A path can be unacceptable even when all six wheels appear able to pass. If a ridge or rock comes too close to the rover’s underside, the belly pan may contact the terrain. The same Perseverance animation distinguishes paths with a belly-pan-clearance concern from those with excessive wheel drop.
How a rover avoids a rock while driving
- Acquire images: navigation cameras capture stereo views of the ground ahead.
- Build a local 3D map: onboard software estimates elevations and identifies surfaces, edges, rocks, and depressions.
- Generate candidate paths: the navigation system considers alternatives toward the current waypoint.
- Score safety: paths are evaluated for slope, roughness, vertical steps, wheel drops, obstacle clearance, and belly-pan clearance.
- Drive a validated segment: the rover moves only as far as the command sequence and local checks allow.
- Replan when necessary: if a new image reveals an unsafe obstacle, the rover selects a safer local path while continuing toward the human-assigned destination.
Perseverance’s AutoNav is described by NASA as capable of creating three-dimensional maps and rerouting around obstacles during a drive. The documented example involved navigating around a 14-inch (35-centimeter) rock, showing why local autonomy matters even after a route has been planned on Earth.
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How the rover knows whether it really moved
Planning a path is only half the problem. Wheels can rotate without producing the expected forward motion when they slip on loose or uneven ground. Curiosity combines gyroscope and accelerometer measurements with wheel rotations, then uses visual odometry to compare successive images and estimate the rover’s actual motion.
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Visual odometry can reveal that the rover has traveled a different distance or direction than wheel rotations imply. The navigation system can then account for the error instead of continuing to trust a false position. JPL reports that Curiosity uses visual odometry on more than 90% of drives. After a mission software update, the method converged successfully in 99.6% of 20,682 attempts; the JPL page does not state a publication date for those figures.
Curiosity and Perseverance: two approaches to local autonomy
Both rovers combine human route planning with onboard hazard avoidance, but their driving workflows differ.
| Comparison point | Curiosity | Perseverance |
|---|---|---|
| Image-processing rhythm | JPL describes a stop-and-image behavior in which the rover pauses to gather and process images for hazard avoidance. | NASA describes faster cameras and a dedicated vision-compute element that support more continuous local navigation. |
| Local terrain assessment | Uses stereo images to detect large vertical steps, steep slopes, and excessive roughness. | Builds 3D terrain maps and evaluates alternative paths around obstacles while driving. |
| Localization | Combines inertial sensors and wheel rotations with visual odometry to detect wheel slip and estimate motion. | Uses onboard visual perception and navigation computing to adjust its local path toward a selected destination. |
| Human versus onboard decisions | Ground teams choose the broad route; the rover handles defined local hazard checks. | Ground teams choose destinations and science activities; AutoNav can reroute locally between waypoints. |
| Demonstrated autonomy scope | Visual-odometry performance is documented across thousands of attempts. | NASA has demonstrated obstacle avoidance and reported a separate generative-AI route-planning trial, but not replacement of routine human mission planning. |
What the 2025 generative-AI demonstration actually showed
NASA reported a generative-AI route-planning demonstration for Perseverance on mission sols 1,707 and 1,709. The system processed orbital imagery and slope data, produced continuous paths with waypoints, and the rover drove 689 feet (210 meters) on one drive and 807 feet (246 meters) on the other.
Before transmission, engineers ran the commands through a digital twin and checked more than 500,000 telemetry variables. That validation step matters: an AI-generated path still has to satisfy the rover’s engineering limits and the mission’s command and telemetry checks before it can be sent to Mars.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsThe demonstration should be understood as an engineering trial, not evidence that Perseverance routinely operates without human route planners. NASA has described kilometer-scale AI-assisted drives as a future direction. Human teams still select the destination, science objectives, and operational constraints.
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Vandi Verma, a JPL space roboticist and member of the Perseverance engineering team, summarized the potential role of generative AI as improving “perception (seeing the rocks and ripples), localization (knowing where we are, and planning and control (deciding and executing the safest path).” The practical value is faster preparation and better handling of complex terrain, provided the resulting commands remain verifiable.
How commands are tested before uplink
- Assemble the activity plan: combine driving, science observations, instrument use, communications, and power constraints for the planned sol.
- Check route geometry: confirm waypoints, keep-out zones, slopes, clearances, and expected drive segments.
- Simulate the rover: execute the sequence in a digital twin or equivalent ground test environment.
- Review telemetry limits: verify that the command sequence cannot create an out-of-family temperature, power, motion, or instrument state.
- Inspect predicted outcomes: compare expected position, camera views, and science opportunities with the team’s objectives.
- Uplink and monitor: transmit the approved commands, then use returned telemetry and imagery to update the next plan.
For the December 2025 AI demonstration, the digital-twin review included more than 500,000 telemetry variables before the commands were sent. This illustrates the difference between generating a route and approving one for flight: the latter requires a broad engineering verification process.
Who “drives” a Mars rover?
Rover drivers are engineers and scientists on Earth who design command sequences rather than steer in real time. They select the destination, science stops, waypoints, and restrictions, then rely on the rover’s autonomy to handle small-scale uncertainty during execution.
Perseverance’s ability to “think while driving,” as Vandi Verma described it, means the rover can interpret new local imagery and adjust its path. It does not mean the rover has chosen its own mission. The ground team remains responsible for the strategic route and for deciding which observations are worth the risk and time of reaching them.
Route planning versus landing navigation
Surface route planning should not be confused with Terrain-Relative Navigation used during landing. Landing navigation helps select or refine a safe landing location while the spacecraft is descending. Rover route planning begins after landing and concerns movement across the surface, science objectives, waypoints, local hazards, and drive verification. They use related ideas—maps, terrain analysis, and autonomous decisions—but solve different problems at different mission phases.
What can make a planned route fail?
- Orbital detail is insufficient: a small rock, depression, or loose patch may be invisible or ambiguous from orbit. The rover’s stereo map must take precedence locally.
- Wheel slip changes the position estimate: visual odometry and inertial measurements are needed to detect disagreement between wheel rotation and actual motion.
- A safe-looking line threatens the underside: belly-pan clearance can reject a path even when wheel drops are acceptable.
- A route is technically passable but scientifically poor: planners may revise it to reach a better outcrop or sampling position.
- Autonomy encounters an unresolvable hazard: the rover can stop or choose a conservative alternative, after which Earth-based planners can create a new command sequence using the returned data.
These failure modes explain why mission teams use repeated planning cycles. Every drive produces new imagery, position information, and engineering data that improve the next route decision.
The essential idea
A safe Mars-rover route is a negotiated path between human intent and machine perception. People decide where the mission should go and what science matters; orbital maps provide the regional context; onboard cameras and navigation software protect the rover from hazards that become visible only at close range; and ground verification makes sure the resulting commands are safe to transmit. Autonomy makes driving more adaptable, but it operates inside goals and constraints established by the mission team.
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