Frictional Contact
Frictional contact, the interaction between surfaces in relative motion, is a crucial area of research impacting robotics, simulation, and material science. Current research focuses on developing accurate and efficient models for frictional contact, encompassing diverse approaches such as incremental potential contact methods, limit surface theory, and physics-infused neural networks, often within differentiable physics engines to enable gradient-based optimization. These advancements aim to improve the realism and computational efficiency of simulations, leading to better robot control, more accurate predictions of material behavior, and enhanced design of robotic systems and actuators. The ultimate goal is to create robust and reliable systems capable of handling complex contact interactions in dynamic environments.
Papers
Learning Dynamics of a Ball with Differentiable Factor Graph and Roto-Translational Invariant Representations
Qingyu Xiao, Zixuan Wu, Matthew Gombolay
Embedded IPC: Fast and Intersection-free Simulation in Reduced Subspace for Robot Manipulation
Wenxin Du, Chang Yu, Siyu Ma, Ying Jiang, Zeshun Zong, Yin Yang, Joe Masterjohn, Alejandro Castro, Xuchen Han, Chenfanfu Jiang