Research/ PLANETARY ROBOTICS
Efficient Arm Motion Planning with Reduced Viapoints for Mars Rover Operations
Justin T. Huang, Valen Yamamoto, Ana Warner
Motion Planning & NavigationOpenAlex topic: Robotic Path Planning Algorithms · Learning-based MethodsOpenAlex topic: Reinforcement Learning in Robotics
Perseverance (Mars 2020)named in abstract, keywords
This paper describes additions and enhancements we made to the standard RRT-Connect motion planning algorithm to suit the unique needs of operating the robotic arm on the Perseverance Mars Rover. One constraint we have is to maintain a minimum distance between the terrain and any part of the arm hardware. Another goal specific to rover planning is to minimize the number of viapoints in our motion plans. These algorithms should also run efficiently so that rover planners can generate arm motion sequences in time for uplink windows. We applied the RRT-Connect algorithm to the rover’s robotic arm and tested its performance, and we found that it could be used successfully for rover planning with a few changes. First, we implemented the terrain clearance requirement using a software tool called Proximeter. Second, we simplify the paths computed by RRT-Connect to minimize the number of viapoints in a motion plan. Third, we leverage Proximeter to reduce the number of expensive terrain collision checks done by the algorithm, speeding up motion planning.