Frequency-Aware Model Predictive Control
Frequency-Aware Model Predictive Control
复制标题
频率感知模型预测控制
DOI：
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发表时间：
2018
影响因子：
5.2
通讯作者：
Marco Hutter
中科院分区：
文献类型：
--
作者：
R. Grandia;Farbod Farshidian;Alexey Dosovitskiy;René Ranftl;Marco Hutter
将轨迹优化找到的解决方案应用于机器人硬件仍然是一项具有挑战性的任务。当优化充分利用所提供的模型来执行动态任务时，未建模的动力学的存在使得运动在实际系统中不可行。模型误差不仅是模型简化的结果，而且在将机器人部署在非结构化和不确定性环境中时也会自然产生。主要是，柔性触点和致动器动力学导致带宽限制。虽然经典的控制方法提供了对一类模型误差具有鲁棒性的综合控制器的工具，但在现代轨迹优化中却缺少这样的概念，这是在时域内解决的。我们提出了频率形成本函数来实现腿式机器人最优控制的鲁棒解。通过仿真和硬件实验表明，该运动方案可以与执行器和接触动力学设定的带宽限制相兼容。模型预测解的平滑性可以在不影响问题可行性的情况下连续调整。四足机器人ANYmal采用高柔性系列弹性致动器驱动，实验结果表明，该机器人对规划的运动轨迹、扭矩轨迹和力轨迹的跟踪性能显著提高，并能在未建模的柔度地形上稳健行走。
Transferring solutions found by trajectory optimization to robotic hardware remains a challenging task. When the optimization fully exploits the provided model to perform dynamic tasks, the presence of unmodeled dynamics renders the motion infeasible on the real system. Model errors cannot be only a result of model simplifications, but also naturally arise when deploying the robot in unstructured and nondeterministic environments. Predominantly, compliant contacts and actuator dynamics lead to bandwidth limitations. While classical control methods provide tools to synthesize controllers that are robust to a class of model errors, such a notion is missing in modern trajectory optimization, which is solved in the time domain. We propose frequency-shaped cost functions to achieve robust solutions in the context of optimal control for legged robots. Through simulation and hardware experiments we show that motion plans can be made compatible with bandwidth limits set by actuators and contact dynamics. The smoothness of the model predictive solutions can be continuously tuned without compromising the feasibility of the problem. Experiments with the quadrupedal robot ANYmal, which is driven by highly compliant series elastic actuators, showed significantly improved tracking performance of the planned motion, torque, and force trajectories and enabled the machine to walk robustly on terrain with unmodeled compliance.