ICRA 2026poster0 citations

Enhanced Autonomous Navigation on the Perseverance Mars Rover (I)

Olivier Toupet, Masahiro Ono, Tyler Del Sesto, Mark Maimone, Michael McHenry

Abstract

This paper presents Enhanced Autonomous Navigation, or ENav, the autonomous driving algorithm of NASA's Mars rover Perseverance. A unique challenge for the autonomous driving of Perseverance is to meet strict safety and performance requirements in a highly uncertain environment with only a single-core CPU with extremely limited computing resources. ENav overcame this challenge with a novel two-stage path selection approach that balances the path optimality and computational efficiency, combined with a unique collision checking algorithm that conservatively approximates computationally expensive kinematic settling. In addition, ENav provides robustness against slip by expanding the bounding boxes for wheels used by the collision check. These new features, together with FPGA-accelerated vision processing, enabled Perseverance to autonomously drive on substantially more rock-dense terrains and increased the average daily driving distance by an order of magnitude compared to its predecessors, the Curiosity, Spirit, and Opportunity rovers. Perseverance has set several new records for autonomous driving on Mars, breaking those previously held by the Opportunity rover. As of the 1312th Martian day since landing, or 28 October 2024 on the Earth calendar, ~90 of the 32.1 km of driving has used ENav to evaluate the terrain. This paper provides detailed documentation of the ENav algorithm, as well as its implementation, testing, deployment, and driving results on Mars.

Space Robotics and AutomationMotion and Path PlanningAutonomous Vehicle Navigation