Robust Safety-Critical Control for Dynamic Robotics
Robust Safety-Critical Control for Dynamic Robotics
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DOI：
10.1109/tac.2021.3059156
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发表时间：
2022-03
影响因子：
6.8
通讯作者：
Quan Nguyen;K. Sreenath
中科院分区：
文献类型：
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作者：
Quan Nguyen;K. Sreenath
我们提出了一种新的最优鲁棒控制方法，该方法通过二次规划提供跟踪稳定性，同时受输入和基于状态的约束以及存在模型不确定性的非线性动态机器人系统的安全关键约束。该方法通过鲁棒控制Lyapunov函数和barrier函数来保证模型存在不确定性时的稳定性和安全性。我们评估了我们提出的五连杆平面双足机器人在接触力约束下的动态行走控制设计，以及在垫脚石上安全关键的精确脚位，所有这些都受到模型不确定性的影响。在不同类型的模型不确定性和扰动下，我们对所提出的控制器在直线弹簧车系统上进行了初步的实验验证。
We present a novel method of optimal robust control through quadratic programs that offers tracking stability while subject to input and state-based constraints as well as safety-critical constraints for nonlinear dynamical robotic systems in the presence of model uncertainty. The proposed method formulates robust control Lyapunov and barrier functions to provide guarantees of stability and safety in the presence of model uncertainty. We evaluate our proposed control design on dynamic walking of a five-link planar bipedal robot subject to contact force constraints as well as safety-critical precise foot placements on stepping stones, all while subject to model uncertainty. We conduct preliminary experimental validation of the proposed controller on a rectilinear spring-cart system under different types of model uncertainty and perturbations.