RVSP
Initialism of Rover Sequencing and Visualization Program, a tool that helps engineers plan the Curiosity rover's drives, modeling pebbles and bumps in the terrain.
RVSP: Mars rover path planning software from JPL
RVSP is mission planning software developed at NASA's Jet Propulsion Laboratory to compute safe drive routes for the Curiosity rover on Mars. It takes orbital imagery and topographic data, then models the terrain in three dimensions to predict how the rover's wheels and suspension will respond to actual ground obstacles. Engineers use it before uploading drive commands to Mars, where communication delays make real-time course correction impossible.
The core function is terrain simulation. RVSP builds a digital model of rocks, slopes, and soil properties from satellite data, then runs the rover's kinematics through that model to check for high-centering, tip-over risk, or excessive wheel slip. It visualizes the rover's orientation and clearance at every point along a proposed path, flagging hazards that might not be obvious from overhead imagery alone. This is essential because Curiosity's ground clearance is measured in tens of centimeters, and a boulder hidden in shadow on a rover-cam photo can disable the vehicle.
The software originated from the need to operate Curiosity safely across Gale Crater's rough terrain without line-of-sight control from Earth. Unlike terrestrial rovers that can stop and back up when an operator sees danger, Mars rovers execute pre-planned drives that may take hours to complete. RVSP compresses the human decision-making into a single planning phase before command upload, running dozens of trajectory simulations to find the safest route toward the science target.
In practice, mission planners receive rover imagery from the previous Martian day, spend 24 to 48 Earth hours analyzing terrain and computing drives in RVSP, then uplink commands that execute on Mars' next favorable communication window. The tool has proved durable across Curiosity's decade-long mission, with periodic updates to refine terrain assumptions as the rover accumulates real-world drive data and engineers learn which obstacle classes the simulation handles well and which ones require more conservative margins.