On the Similarities and Differences Among Contact Models in Robot Simulation

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Abstract
Over the past several decades, as affordable computational power has increased, simulation has become increasingly important in robot analysis, planning, and control. Smooth robot dynamics can be simulated efficiently and accurately and therefore readily used in model-based control schemes. However, some of the most difficult and important problems in robotics, such as running, grasping, and parts assembly, involve intermittent frictional contacts, which introduce extreme nonlinearities into the dynamics. Numerous approaches have been developed to simulate contact dynamics. Even though real bodies are not rigid, idealized rigid contact models have been used widely and productively for decades. However, the resulting non-smooth dynamics can be computationally difficult to solve or use in model-based planning and control, motivating researchers to propose various relaxations of the idealized contact models. The varied origins and formulations of these approaches can obscure their similarities and differences. In this paper, we identify and explain differences between four contact models. We present the models in the context of one solver that is applicable to all of them, namely Projected Gauss-Seidel, in order to highlight their common structure and to avoid confounding their comparison with differences in the solution methods. Simulation results from sliding, wedging, grasping, and stacking experiments illustrate consequences of the differences. The results can help inform roboticists when comparing and selecting models for their specific applications.
Funding Information
  • NSF (IIS-1537023, EFRI-1832795)

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