论文标题
通过计划原始图表在腿部机器人上的强大运动
Robust Locomotion on Legged Robots through Planning on Motion Primitive Graphs
论文作者
论文摘要
机器人系统的功能需求通常需要在干扰或不确定环境的影响下完成各种任务或行为。越来越多的兴趣是动态机器人的自主权，例如多电动器，汽车和腿部平台。在这里，干扰和环境条件可能会对单个动态行为的成功表现产生重大影响，该行为称为“运动原语”。尽管如此，可以通过合适的运动原语通过切换和过渡来实现鲁棒性。本文通过提出运动原始动力学的抽象和相应的“运动原始传递函数”来贡献这种方法。由此，构建了混合的离散和连续的“运动原始图”，并详细介绍了能够在线搜索此图的算法。结果是一个能够实现动态系统的整体鲁棒性的框架。这是在四足动物机器人上的一组运动原语的实验证明，但要受到各种环境和故意干扰。
The functional demands of robotic systems often require completing various tasks or behaviors under the effect of disturbances or uncertain environments. Of increasing interest is the autonomy for dynamic robots, such as multirotors, motor vehicles, and legged platforms. Here, disturbances and environmental conditions can have significant impact on the successful performance of the individual dynamic behaviors, referred to as "motion primitives". Despite this, robustness can be achieved by switching to and transitioning through suitable motion primitives. This paper contributes such a method by presenting an abstraction of the motion primitive dynamics and a corresponding "motion primitive transfer function". From this, a mixed discrete and continuous "motion primitive graph" is constructed, and an algorithm capable of online search of this graph is detailed. The result is a framework capable of realizing holistic robustness on dynamic systems. This is experimentally demonstrated for a set of motion primitives on a quadrupedal robot, subject to various environmental and intentional disturbances.
