Set-Valued Rigid Body Dynamics for Simultaneous, Inelastic, Frictional Impacts
Mathew Halm, Michael Posa

TL;DR
This paper introduces a set-valued rigid-body model for accurately predicting outcomes of nearly-simultaneous, inelastic, frictional impacts in robotic manipulation and locomotion, addressing limitations of existing simulators.
Contribution
It extends Routh's impact model to multiple impacts via differential inclusions, ensuring finite-time impact resolution and continuous-time evolution, with a novel LCP-based simulation approach.
Findings
The model captures a broad set of physically plausible impact outcomes.
The LCP-based simulation provides tight approximations with probabilistic guarantees.
Demonstrations show improved accuracy in manipulation and legged locomotion scenarios.
Abstract
Robotic manipulation and locomotion often entail nearly-simultaneous collisions -- such as heel and toe strikes during a foot step -- with outcomes that are extremely sensitive to the order in which impacts occur. Robotic simulators commonly lack the accuracy to predict this ordering, and instead pick one with a heuristic. This discrepancy degrades performance when model-based controllers and policies learned in simulation are placed on a real robot. We reconcile this issue with a set-valued rigid-body model which generates a broad set of physically reasonable outcomes of simultaneous frictional impacts. We first extend Routh's impact model to multiple impacts by reformulating it as a differential inclusion (DI), and show that any solution will resolve all impacts in finite time. By considering time as a state, we embed this model into another DI which captures the continuous-time…
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Taxonomy
TopicsRobotic Locomotion and Control · Formal Methods in Verification · Reinforcement Learning in Robotics
