Robots are used by humans not only as tools but also to interactively assist and cooperate with humans, thereby forming physical human-robot interactions. In these interactions, there is a risk that a feedback loop causes unstable force interaction, in which force escalation exposes a human to danger. Previous studies have analyzed the stability of voluntary interaction but have neglected involuntary behavior in the interaction. In contrast to the previous studies, this study considered the involuntary behavior: a human's force reproduction bias for discrete-event human-robot force interaction. We derived an asymptotic stability condition based on a mathematical bias model and found that the bias asymptotically stabilizes a human's implicit equilibrium point far from the implicit equilibrium point and destabilizes the point near the point. The bias model, convergence of the interaction toward the implicit equilibrium point, and divergence around the point were consistently verified via behavioral experiments under three kinds of interactions using three different body parts: a hand finger, wrist, and foot. Our results imply that humans implicitly secure a stable and close relationship between themselves and robots with their involuntary behavior.
翻译:机器人不仅被人类用作工具,还被用来与人类进行互动性协助与合作,从而形成人体-机器人相互作用。在这些相互作用中,存在一种风险,即反馈循环会导致不稳定的武力互动,使人类面临危险。以前的研究分析了自愿互动的稳定性,但忽视了互动中的非自愿行为。与以往的研究相比,本研究考虑了非自愿行为:人类对离散事件人体-机器人相互作用的强制生殖偏向。我们根据数学偏差模型得出了一种无药可依的稳定条件,发现这种偏差使人类隐含的平衡点远离隐含的平衡点,并动摇了点附近的平衡点。偏差模式、相互作用与隐含的平衡点的趋同以及点周围的分歧,通过三种不同身体部分:手指、手腕和脚的动作实验得到了一致的验证。我们的结果表明,人类隐含着自己和机器人之间与其非自愿行为之间的稳定和密切关系。