Contact Simulation

Contact simulation aims to accurately model the interactions between objects, particularly in robotics and related fields, focusing on predicting forces and motions during contact. Current research emphasizes developing robust and efficient algorithms, including those based on neural networks, optimization techniques (like model predictive control and interior-point methods), and symbolic algebra systems, to handle complex scenarios involving deformable objects and multiple contact points. These advancements are crucial for improving robot control, particularly in manipulation tasks, and for creating more realistic simulations in various applications, from biomechanics to virtual reality.