Reproduce “Adaptive Locomotion on Mud through Proprioceptive Sensing of Substrate Properties” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Shipeng Liu, Jiaze Tang, Siyuan Meng, Feifei Qian
A mudskipper-inspired robot employs proprioceptive sensing from its direct-drive motors to estimate intrinsic mud properties, including penetration resistance, shear strength, and extraction resistance, in real time. This capability allows the robot to dynamically adapt its gait, which enables robust and continuous locomotion across terrains with varying mud conditions.
Key insights
- Direct-drive motors offer high force transparency, enabling accurate proprioceptive sensing of external forces from motor current and position without requiring additional external sensors.
- Principles from Granular Resistive Force Theory (RFT), traditionally applied to dry granular media, can be effectively adapted to model and estimate intrinsic mechanical properties of cohesive materials like mud.
- Accurate real-time terrain property estimation during continuous robot locomotion requires careful compensation for robot-body interactions, such as body drag, to refine force interpretation.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.