Achieving More with Less: Improved Surface Mobility Performance

The Mars Exploration Program ERNEST Autonomy task is developing a low-cost, extreme terrain rover capable of traversing rugged terrain on the moon and mid-latitude & polar regions on Mars. A novel kinematic configuration with a two-degrees-of-freedom active gimbaled suspension enables traverse over varied terrain types using gaits optimized for the terrain type. The ERNEST (Exploration Rover for Navigating Extreme Sloped Terrain) vehicle embodying this concept has been built under a previously funded effort. The focus of this task is to implement and demonstrate adaption to and traverse over several challenging terrain types using on-board autonomous algorithms that utilize perception and proprioceptive sensors to command the active suspension system and apply gaits optimized for the terrain type. We are investigating two alternative methods to implement autonomous control of active suspension: 1) Reinforcement Learning with training on a high-fidelity dynamics simulator then transferring to the physical rover, and 2) Motion planning with a model of the active suspension system and terrain. A demonstration of autonomous active-suspension mobility will be demonstrated over an obstacle course at JPL’s MarsYard.

The ERNEST vehicle configuration reduces cost and complexity of surface mobility while maximizing steep and rugged terrain ability. It enables exploration of currently inaccessible terrain, increases science return with shorter traverses over more difficult terrain, and demonstrates higher drive speeds for long traverse missions. The mobility algorithms being developed in this task will enable autonomous surface mobility operations over rugged terrain on Mars where long communication delays to Earth preclude ground-in-the-loop control.

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