论文标题
使用反馈MPC框架的高维机器人系统的触觉近距离运行
Haptic Teleoperation of High-dimensional Robotic Systems Using a Feedback MPC Framework
论文作者
论文摘要
模型预测控制（MPC）方案已证明它们在控制高自由度（DOF）复杂机器人系统方面的效率。但是，它们的计算成本很高，更新速度约为数十万。这种相对缓慢的更新速率阻碍了此类系统稳定的触觉远距离播种的可能性，因为缓慢的反馈回路可能会导致对操作员的不稳定性和透明度的丧失。这项工作为MPC控制的复杂机器人系统的透明近距离介绍了一个新颖的框架。特别是，我们采用反馈MPC方法并利用其结构来以快速速率计算运营商输入，该速度与MPC循环本身的更新率无关。我们在移动操纵器平台上演示了我们的框架，并表明它可以显着提高触觉远程流动的透明度和稳定性。我们还强调，所提出的反馈结构是令人满意的，并且不违反最佳控制问题中定义的任何约束。据我们所知，这项工作是使用全身MPC框架的双边手动操纵器双边远程操作的首次实现。
Model Predictive Control (MPC) schemes have proven their efficiency in controlling high degree-of-freedom (DoF) complex robotic systems. However, they come at a high computational cost and an update rate of about tens of hertz. This relatively slow update rate hinders the possibility of stable haptic teleoperation of such systems since the slow feedback loops can cause instabilities and loss of transparency to the operator. This work presents a novel framework for transparent teleoperation of MPC-controlled complex robotic systems. In particular, we employ a feedback MPC approach and exploit its structure to account for the operator input at a fast rate which is independent of the update rate of the MPC loop itself. We demonstrate our framework on a mobile manipulator platform and show that it significantly improves haptic teleoperation's transparency and stability. We also highlight that the proposed feedback structure is constraint satisfactory and does not violate any constraints defined in the optimal control problem. To the best of our knowledge, this work is the first realization of the bilateral teleoperation of a legged manipulator using a whole-body MPC framework.
