From Impact to Insight: Dynamics-Aware Proprioceptive Terrain Sensing on Granular Media
The research investigated how robots interact with granular terrain during high-speed hopping using only onboard sensing. They found that traditional methods fail because acceleration-dependent effects, like grain entrainment, dominate force responses rather than simple velocity drag. A new framework using a momentum observer and an acceleration-aware weighted regression successfully recovers accurate granular resistance values that match ground truth, proving explicit treatment of these dynamics is necessary for reliable terrain characterization.