Online Dynamic Trajectory Optimization and Control for a Quadruped Robot
Online Dynamic Trajectory Optimization and Control for a Quadruped Robot
复制标题
四足机器人在线动态轨迹优化与控制
DOI：
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发表时间：
2020
期刊：
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通讯作者：
M. Mistry
中科院分区：
文献类型：
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作者：
Oguzhan Cebe;Carlo Tiseo;Guiyang Xin;Hsiu;Joshua Smith;M. Mistry
腿式机器人的运动需要规划稳定的参考轨迹，特别是在穿越不平坦的地形时。所提出的轨迹优化框架能够生成多步幅动态稳定的基步幅轨迹和步幅轨迹。运动任务可以定义为接触位置，基础运动或两者兼而有之，使算法适用于多种场景（例如，存在移动障碍物）。规划器使用简化的基于动量的机器人动力学任务空间模型，使得计算时间足够快，可以在线重新规划。这种快速的规划能力也使四足动物能够适应漂移和环境变化。该算法在模拟和真实机器人上进行了多种场景的测试，包括不平坦的地形、楼梯和移动的障碍物。结果表明，即使在实际机器人的路径前最后时刻放置一个15厘米高的盒子，该规划器也能生成稳定的轨迹。
Legged robot locomotion requires the planning of stable reference trajectories, especially while traversing uneven terrain. The proposed trajectory optimization framework is capable of generating dynamically stable base and footstep trajectories for multiple steps. The locomotion task can be defined with contact locations, base motion or both, making the algorithm suitable for multiple scenarios (e.g., presence of moving obstacles). The planner uses a simplified momentum-based task space model for the robot dynamics, allowing computation times that are fast enough for online replanning. This fast planning capability also enables the quadruped to accommodate for drift and environmental changes. The algorithm is tested on simulation and a real robot across multiple scenarios, which includes uneven terrain, stairs and moving obstacles. The results show that the planner is capable of generating stable trajectories in the real robot even when a box of 15 cm height is placed in front of its path at the last moment.