arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2008.00191cs.RO
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基于多触点优化的动态腿对球的操纵

Dynamic Legged Manipulation of a Ball Through Multi-Contact Optimization

University of California, Berkeley(加州大学伯克利分校)

Chenyu Yang, Bike Zhang, Jun Zeng, Ayush Agrawal, Koushil Sreenath

摘要:

机器人的脚通常用于设计运动策略,例如平衡,行走和跑步。然而,它们也具有执行操纵任务的巨大潜力。在本文中,我们提出了一个模型预测控制(MPC)框架的四足机器人动态平衡球,同时操纵它遵循各种轨迹,如直线,正弦曲线,圆和原地转弯。我们数值验证我们的控制器上的迷你猎豹机器人使用不同的步态,包括小跑,弹跳,和pronking球。

英文摘要:

The feet of robots are typically used to design locomotion strategies, such as balancing, walking, and running. However, they also have great potential to perform manipulation tasks. In this paper, we propose a model predictive control (MPC) framework for a quadrupedal robot to dynamically balance on a ball and simultaneously manipulate it to follow various trajectories such as straight lines, sinusoids, circles and in-place turning. We numerically validate our controller on the Mini Cheetah robot using different gaits including trotting, bounding, and pronking on the ball.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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