论文标题
通过水力弹性接触和ILQR的接触式轨迹优化
Contact-Implicit Trajectory Optimization with Hydroelastic Contact and iLQR
论文作者
论文摘要
接触式轨迹优化提供了一种吸引人的方法，可以自动生成用于机器人操纵和运动的复杂和接触型行为。但是，由于确保数值可靠性和物理现实主义的挑战，这种技术的可伸缩性受到限制。在本文中，我们提出了初步结果，表明迭代线性二次调节器（ILQR）算法以及最近提出的基于压力场的水力弹性接触模型可以通过接触实现可靠和物理上现实的轨迹优化。我们使用这种方法来综合富含接触的行为，例如四倍的运动和全臂操纵。此外，Kinova Gen3机器人臂上的开环播放表明了全臂操纵轨迹的身体准确性。代码可在https://bit.ly/ilqr_hc上找到，可以在https://youtu.be/iqxjkbm8_ms上找到视频。
Contact-implicit trajectory optimization offers an appealing method of automatically generating complex and contact-rich behaviors for robot manipulation and locomotion. The scalability of such techniques has been limited, however, by the challenge of ensuring both numerical reliability and physical realism. In this paper, we present preliminary results suggesting that the Iterative Linear Quadratic Regulator (iLQR) algorithm together with the recently proposed pressure-field-based hydroelastic contact model enables reliable and physically realistic trajectory optimization through contact. We use this approach to synthesize contact-rich behaviors like quadruped locomotion and whole-arm manipulation. Furthermore, open-loop playback on a Kinova Gen3 robot arm demonstrates the physical accuracy of the whole-arm manipulation trajectories. Code is available at https://bit.ly/ilqr_hc and videos can be found at https://youtu.be/IqxJKbM8_ms.
