Purpose

To promote the intuitiveness of collaborative tasks, the negotiation ability of humans with each other has inspired a large amount of studies aimed at reproducing the capacity in physical human-robot interaction (pHRI). This paper aims to promote mutual adaptation in negotiation when both parties possess incomplete information.

Design/methodology/approach

This paper introduces virtual fixtures into the traditional negotiation mechanism, locally regulating tracking trajectory and impedance parameters in the negotiating phase until the final plan integrates bilateral intentions well. In the strategy, robots convey its task information to humans and offer groups of guide plans for them to choose, on the premise of maximizing the robot’s own profits.

Findings

Compared with traditional negotiation strategies, humans adapt to robots easily and show lower cognitive load in the method, while the satisfied plan shows better performance for the whole human-robot system.

Originality/value

In this study, this paper proposes a novel negotiation strategy to facilitate the mutual adaptation of humans and robots in complicated shared tasks, especially when both parties possess incomplete information of tasks.

中文翻译：

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使用自适应虚拟夹具促进触觉协商中的相互适应

目的

为了提高协作任务的直观性，人与人之间的谈判能力激发了大量旨在再现人机交互（pHRI）能力的研究。本文旨在促进双方在信息不完整的情况下在谈判中相互适应。

设计/方法/方法

本文将虚拟夹具引入到传统的谈判机制中，在谈判阶段局部调节跟踪轨迹和阻抗参数，直到最终方案很好地融合了双边意图。在该策略中，机器人将其任务信息传达给人类，并在最大化机器人自身利润的前提下，提供成组的引导计划供人类选择。

发现

与传统的谈判策略相比，人类更容易适应机器人，在该方法中表现出较低的认知负荷，而满意的计划在整个人机系统中表现出更好的性能。

原创性/价值

在这项研究中，本文提出了一种新颖的协商策略，以促进人类和机器人在复杂的共享任务中相互适应，特别是当双方都拥有不完整的任务信息时。