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arXiv · 2411.10935

Exciting Contact Modes in Differentiable Simulations for Robot Learning

Hrishikesh Sathyanarayan·Ian Abraham
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Abstract

In this paper, we explore an approach to actively plan and excite contact modes in differentiable simulators as a means to tighten the sim-to-real gap. We propose an optimal experimental design approach derived from information-theoretic methods to identify and search for information-rich contact modes through the use of contact-implicit optimization. We demonstrate our approach on a robot parameter estimation problem with unknown inertial and kinematic parameters which actively seeks contacts with a nearby surface. We show that our approach improves the identification of unknown parameter estimates over experimental runs by an estimate error reduction of at least $\sim 84\%$ when compared to a random sampling baseline, with significantly higher information gains.

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Hrishikesh Sathyanarayan, Ian Abraham. 2024-11-17. Exciting Contact Modes in Differentiable Simulations for Robot Learning. https://arxiv.org/abs/2411.10935

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