双足步行的自适应步长:非线性约束的鲁棒方法

N. Bohorquez, Pierre-Brice Wieber
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引用次数: 11

摘要

当双足机器人在人群中行走时,能够调整步幅是避免碰撞的关键因素。模型预测控制(MPC)方案通常采用固定的步长,因为对其进行调整会导致非线性问题。非线性求解器不能保证每次迭代都满足非线性约束,这可能会给机器人的实时运行带来问题。我们借鉴鲁棒控制的概念,提出了一种确保所有迭代都满足非线性约束的方法:使问题在一定范围内对非线性具有鲁棒性。这些边界对于问题的变量是线性的,并且可以在线调整。
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Adaptive step duration in biped walking: A robust approach to nonlinear constraints
When a biped robot is walking in a crowd, being able to adapt the duration of steps is a key element to avoid collisions. Model Predictive Control (MPC) schemes for biped walking usually assume a fixed step duration since adapting it leads to a nonlinear problem, in general. Nonlinear solvers do not guarantee the satisfaction of nonlinear constraints at every iterate and this can be problematic for the real-time operation of robots. We propose a method to make sure that all iterates satisfy the nonlinear constraints by borrowing concepts from robust control: we make the problem robust to nonlinearities within some bounds. These bounds are linear with respect to the variables of the problem and can be adapted online.
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