Contact-implicit trajectory optimization using variational integrators
Contact-implicit trajectory optimization using variational integrators
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DOI：
10.1177/0278364919849235
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发表时间：
2019-10-01
影响因子：
9.2
通讯作者：
Kuindersma, Scott
中科院分区：
文献类型：
--
作者：
Manchester, Zachary;Doshi, Neel;Kuindersma, Scott
接触约束是许多机器人规划问题中自然产生的问题。近年来，各种隐式接触轨迹优化算法已经被开发出来，它们通过同时优化状态、输入和接触力轨迹来避免模式预指定的缺陷。然而，它们对一阶积分器的依赖导致了优化问题规模和规划精度之间的线性权衡。为了解决这一局限性，我们提出了一类新的轨迹优化算法，该算法利用离散变分力学的思想来推导Stewart和Trinkle的经典时间推进方法的高阶推广。通过将这些动力学公式作为直接轨迹优化算法中的约束条件，可以以显著更高的精度执行接触隐式轨迹优化。具体来说，我们推导了一种二阶方法，并用几个模拟的刚体系统进行了评估，包括一个欠驱动的两足动物和一个四足动物。此外，我们使用这种二阶方法来规划复杂的四足微机器人的运动轨迹。计划的轨迹在物理平台上进行评估，并导致许多性能改进。
Contact constraints arise naturally in many robot planning problems. In recent years, a variety of contact-implicit trajectory optimization algorithms have been developed that avoid the pitfalls of mode pre-specification by simultaneously optimizing state, input, and contact force trajectories. However, their reliance on first-order integrators leads to a linear tradeoff between optimization problem size and plan accuracy. To address this limitation, we propose a new family of trajectory optimization algorithms that leverage ideas from discrete variational mechanics to derive higher-order generalizations of the classic time-stepping method of Stewart and Trinkle. By using these dynamics formulations as constraints in direct trajectory optimization algorithms, it is possible to perform contact-implicit trajectory optimization with significantly higher accuracy. For concreteness, we derive a second-order method and evaluate it using several simulated rigid-body systems, including an underactuated biped and a quadruped. In addition, we use this second-order method to plan locomotion trajectories for a complex quadrupedal microrobot. The planned trajectories are evaluated on the physical platform and result in a number of performance improvements.