Physical human-robot interaction (pHRI) integrates the benefits of human operator and a collaborative robot in tasks involving physical interaction, with the aim of increasing the task performance. However, the design of interaction controllers that achieve safe and transparent operations is challenging, mainly due to the contradicting nature of these objectives. Knowing that attaining perfect transparency is practically unachievable, controllers that allow better compromise between these objectives are desirable. In this article, we propose a multicriteria optimization framework, which jointly optimizes the stability robustness and transparency of a closed-loop pHRI system for a given interaction controller. In particular, we propose a Pareto optimization framework that allows the designer to make informed decisions by thoroughly studying the tradeoff between stability robustness and transparency. The proposed framework involves a search over the discretized controller parameter space to compute the Pareto front curve and a selection of controller parameters that yield maximum attainable transparency and stability robustness by studying this tradeoff curve. The proposed framework not only leads to the design of an optimal controller, but also enables a fair comparison among different interaction controllers. In order to demonstrate the practical use of the proposed approach, integer and fractional order admittance controllers are studied as a case study and compared both analytically and experimentally. The experimental results validate the proposed design framework and show that the achievable transparency under fractional order admittance controller is higher than that of integer order one, when both controllers are designed to ensure the same level of stability robustness.

中文翻译：

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用于物理人机交互的控制器设计的计算多准则优化方法

物理人机交互（pHRI）在涉及物理交互的任务中整合了人类操作员和协作机器人的优点，旨在提高任务性能。然而，实现安全和透明操作的交互控制器的设计具有挑战性，主要是由于这些目标的矛盾性质。知道实现完美的透明度实际上是无法实现的，因此需要在这些目标之间实现更好的折衷的控制器。在本文中，我们提出了一个多标准优化框架，该框架针对给定的交互控制器联合优化了闭环 pHRI 系统的稳定性鲁棒性和透明度。特别是，我们提出了一个帕累托优化框架，允许设计者通过彻底研究稳定性稳健性和透明度之间的权衡来做出明智的决定。所提出的框架涉及对离散化控制器参数空间的搜索以计算帕累托前沿曲线，以及通过研究此折衷曲线来选择产生最大可达到的透明度和稳定性鲁棒性的控制器参数。所提出的框架不仅可以设计出最佳控制器，还可以在不同的交互控制器之间进行公平的比较。为了证明所提出方法的实际使用，整数和分数阶导纳控制器作为案例研究，并通过分析和实验进行比较。