论文标题
双皮德机器人反应性计划的顺序MPC方法
A Sequential MPC Approach to Reactive Planning for Bipedal Robots
论文作者
论文摘要
本文提出了一种在动态环境中的双足机器人的反应性运动计划的顺序模型预测控制（MPC）方法。该方法依赖于自由空间的顺序多重分解，该分解提供了相互相交的无障碍物多面体和航路点的有序集合。随后，这些用于定义相应的MPC程序序列，该程序将系统驱动到避免静态和移动障碍的目标位置。这样，计划者将重点放在机器人附近的自由空间上，从而减轻了同时考虑所有障碍并减少计算时间的需求。我们使用双足机器人数字验证了方法在高保真模拟中的功效，在存在静态和移动障碍的情况下表明了强大的反应性计划。
This paper presents a sequential Model Predictive Control (MPC) approach to reactive motion planning for bipedal robots in dynamic environments. The approach relies on a sequential polytopic decomposition of the free space, which provides an ordered collection of mutually intersecting obstacle free polytopes and waypoints. These are subsequently used to define a corresponding sequence of MPC programs that drive the system to a goal location avoiding static and moving obstacles. This way, the planner focuses on the free space in the vicinity of the robot, thus alleviating the need to consider all the obstacles simultaneously and reducing computational time. We verify the efficacy of our approach in high-fidelity simulations with the bipedal robot Digit, demonstrating robust reactive planning in the presence of static and moving obstacles.
