Simulation of contact and friction dynamics is an important basis for control- and learning-based algorithms. However, the numerical difficulties of contact interactions pose a challenge for robust and efficient simulators. A maximal-coordinate representation of the dynamics enables efficient solving algorithms, but current methods in maximal coordinates require constraint stabilization schemes. Therefore, we propose an interior-point algorithm for the numerically robust treatment of rigid-body dynamics with contact interactions in maximal coordinates. Additionally, we discretize the dynamics with a variational integrator to prevent constraint drift. Our algorithm achieves linear-time complexity both in the number of contact points and the number of bodies, which is shown theoretically and demonstrated with an implementation. Furthermore, we simulate two robotic systems to highlight the applicability of the proposed algorithm.
翻译:模拟接触和摩擦动态是基于控制和学习的算法的重要基础。然而,接触互动的数字困难对强健高效的模拟器提出了挑战。动态的最大协调代表性使得高效的解算法得以实现,但当前在最大坐标上采用的方法需要制约性稳定方案。因此,我们提出一个内部点算法,用于在最大坐标上以数字稳健的方式处理僵硬身体动态和接触互动。此外,我们将动态与一个变异集成器分解,以防止限制性漂移。我们的算法在联络点数目和机构数目方面都实现了线性时间的复杂性,从理论上看,并通过实施来证明这一点。此外,我们模拟了两个机器人系统,以突出拟议算法的适用性。