Multi-Layered Safety for Legged Robots via Control Barrier Functions and Model Predictive Control
Multi-Layered Safety for Legged Robots via Control Barrier Functions and Model Predictive Control
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DOI：
10.1109/icra48506.2021.9561510
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发表时间：
2020-10
期刊：
影响因子：
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通讯作者：
R. Grandia;Andrew J. Taylor;A. Ames;Marco Hutter
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文献类型：
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作者：
R. Grandia;Andrew J. Taylor;A. Ames;Marco Hutter
在崎岖地形上的动态运动的问题，既需要准确的脚放置在一起的动态稳定性的重点。现有的解决这个问题的方法优先考虑直接安全的脚放置在长期的动态稳定性的考虑，或降级的脚放置和动态稳定性的启发式方法的协调。我们提出了一个多层次的运动框架，统一控制障碍函数（CBFs）与模型预测控制（MPC），同时实现安全的脚放置和动态稳定性。我们的方法采用CBF为基础的安全约束，在低频kinodynamic MPC制定和高频逆动力学跟踪控制器。这确保了在较长时间范围内优化运动时考虑安全关键执行。我们验证了所提出的方法在一个3D的垫脚石的情况下，在模拟和实验上的ANYmal四足动物平台。
The problem of dynamic locomotion over rough terrain requires both accurate foot placement together with an emphasis on dynamic stability. Existing approaches to this problem prioritize immediate safe foot placement over longer term dynamic stability considerations, or relegate the coordination of foot placement and dynamic stability to heuristic methods. We propose a multi-layered locomotion framework that unifies Control Barrier Functions (CBFs) with Model Predictive Control (MPC) to simultaneously achieve safe foot placement and dynamic stability. Our approach incorporates CBF based safety constraints both in a low frequency kinodynamic MPC formulation and a high frequency inverse dynamics tracking controller. This ensures that safety-critical execution is considered when optimizing locomotion over a longer horizon. We validate the proposed method in a 3D stepping-stone scenario in simulation and experimentally on the ANYmal quadruped platform.