Soft robots can safely interact with environments because of their mechanical compliance. Self-collision is also employed in the modern design of soft robots to enhance their performance during different tasks. However, developing an efficient and reliable simulator that can handle the collision response well, is still a challenging task in the research of soft robotics. This paper presents a collision-aware simulator based on geometric optimization, in which we develop a highly efficient and realistic collision checking / response model incorporating a hyperelastic material property. Both actuated deformation and collision response for soft robots are formulated as geometry-based objectives. The collision-free body of a soft robot can be obtained by minimizing the geometry-based objective function. Unlike the FEA-based physical simulation, the proposed pipeline performs a much lower computational cost. Moreover, adaptive remeshing is applied to achieve the improvement of the convergence when dealing with soft robots that have large volume variations. Experimental tests are conducted on different soft robots to verify the performance of our approach.
翻译:软机器人能够安全地与环境互动,因为其机械性能符合要求。软机器人的现代设计中也采用了自熔法,以提高其在不同任务中的性能。然而,开发一个高效和可靠的模拟器,能够很好地处理碰撞反应,这仍然是软机器人研究的一项艰巨任务。本文展示了一个基于几何优化的碰撞感应模拟器,在这个模拟器中,我们开发了一个高效和现实的碰撞检查/反应模型,其中含有超弹性物质特性。软机器人的启动变形和碰撞反应都作为基于几何目标制定。软机器人的无碰撞体可以通过尽量减少基于几何目标的功能获得。与基于FEA的物理模拟不同,拟议管道的计算成本要低得多。此外,适应性再扫描用于在与具有大容量变异的软机器人打交道时改进趋同。对不同的软机器人进行了实验性测试,以核查我们的方法的性能。