Autonomous Proprioceptive Terrain Detection for Compliant Rovers
Project Description
The initial phase of the project will focus on the identification and adaptation of suitable pseudo-soft or reconfigurable mobility systems (e.g., ARC's SUPERball v2, JPL's PUFFER). In the second phase, we will define a sensor fusion (e.g. UKF) and machine learning algorithm (e.g. MPC, RL) able to characterize terrain features (e.g. slope, substrate, barriers) and evaluate robot performance (e.g. speed, slip, stability) using distributed proprioceptive sensors. As a final step, our terrain detection algorithm will be integrated with existing locomotion control policies and JPL's TARMAC (Terrain Adaptive Reconfiguration of Mobility by Automatic Control) path-planning algorithm to enable autonomous crossing of adverse terrains.
More »Anticipated Benefits
Potential stakeholders that could benefit from this research include NASA SMD (e.g., Cryosphere program), USGS, and DOD. This type of technology may also be appropriate for other compliant and reconfigurable structures that we are already investigating for earth and space applications, such as deployable heat shields, morphing wings, and other lightweight systems.
More »Primary U.S. Work Locations and Key Partners
| Organizations Performing Work | Role | Type | Location |
|---|---|---|---|
Ames Research Center
(ARC)
|
Lead Organization | NASA Center | Moffett Field, California |
Primary U.S. Work Locations
-
California
