MPC-Based Reference Governor Control for Self-Righting of Quadruped Robots: Preliminary Results

Aureo Guilherme Dobrikopf,Lucas Schulze, Douglas Widlgrube Bertol,Victor Barasuol

2022 Latin American Robotics Symposium (LARS), 2022 Brazilian Symposium on Robotics (SBR), and 2022 Workshop on Robotics in Education (WRE)(2022)

引用 0|浏览13
暂无评分
摘要
Even with the current efficient legged robots' control techniques, unexpected situations may occur, leading the system to a fall. For the robot to recover mobility, it must be capable of autonomously repositioning itself. The named Self-Righting task aims to solve the problem of robot mobility recovery with a set of reference poses. This work proposes using a Reference Governor Control (RGC) for a quadrupedal robot's stand-up sub-task in a closed-loop scheme. The RGC is composed of a predictive controller based on the robot's states and the constraints' forces obtained from its interaction with the environment. From the results, it is possible to observe that the proposed solution can reposition the robot to a fully recovered mobility state.
更多
查看译文
关键词
Reference Governor Control,Model Predictive Control,Self-Righting,Quadrupedal robots
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要