Attractor design and prediction-based adaption for a robot waltz dancer in physical human-robot interaction

Wang, Hongbo; Kosuge, Kazuhiro

doi:10.1109/wcica.2012.6359108

Cited by 6 publications

(5 citation statements)

References 17 publications

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“…This leads to different Nash equilibria which require control inputs different from (10) and (11). As the actual control input of the human, f , is measurable, the difference between f and f * in (11) can be used as a measure of conflict between the human's objective and that of the robot, i.e., eliminating the difference will realize the coordination of the human and the robot.…”

Section: Game Theorymentioning

confidence: 99%

“…By comparing (11) and (10), and considering (12), we obtain that u * is bounded, as well as P andṖ . Hence, r 2 is bounded according to (17), andz * andż * are bounded according to (13).…”

Section: Role Adaptation For Human-robot Coordinationmentioning

confidence: 99%

“…edu.sg methods in estimating and recognizing human intention (see e.g. [10], [11]) have been developed to provide more cues for the robot to react to, but the control philosophy remains the same, namely, human as leader and robot as follower. The rationale for fixing the roles distinctly is that humans have better cognitive abilities, such as situational awareness and decisionmaking skills, while robots have better physical abilities, such as precision and strength.…”

Section: Introductionmentioning

confidence: 99%

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Continuous Role Adaptation for Human–Robot Shared Control

et al. 2015

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Abstract-In this paper, we propose a role adaptation method for human-robot shared control. Game theory is employed for fundamental analysis of this two-agent system. An adaptation law is developed such that the robot is able to adjust its own role according to the human's intention to lead or follow, which is inferred through the measured interaction force. In the absence of human interaction forces, the adaptive scheme allows the robot to take the lead and complete the task by itself. On the other hand, when the human persistently exerts strong forces that signal an unambiguous intent to lead, the robot yields and becomes the follower. Additionally, the full spectrum of mixed roles between these extreme scenarios is afforded by continuous online update of the control that is shared between both agents. Theoretical analysis shows that the resulting shared control is optimal with respect to a two-agent coordination game. Experimental results illustrate better overall performance, in terms of both error and effort, compared to fixed-role interactions.

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Section: Game Theorymentioning

confidence: 99%

Section: Role Adaptation For Human-robot Coordinationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Continuous Role Adaptation for Human–Robot Shared Control

et al. 2015

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“…Suppose that the cost function of the human is also Γ as in (8). It indicates that both human and robot have a common objective, which is referred to as "coordination" [20], [21].…”

Section: B Adaptation Law: Towards Coordinationmentioning

confidence: 99%

“…Based on the fixed-role leader-follower paradigm, various recognition and estimation methods have been developed (see e.g. [7], [8]) to help the robot understand human intention and interact with its human partner. The underlying assumption of these fixed-role approaches is that humans, having better situational awareness and decision-making skills, should always lead, while robots should always yield and assist humans in tasks requiring high precision and strength.…”

Section: Introductionmentioning

confidence: 99%

Adaptive optimal control for coordination in physical human-robot interaction

Tee

Yan

et al. 2015

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-In this paper, a role adaptation method is developed for human-robot collaboration based on game theory. This role adaptation is engaged whenever the interaction force changes, causing the proportion of control sharing between human and robot to vary. In one boundary condition, the robot takes full control of the system when there is no human intervention. In the other boundary condition, it becomes a follower when the human exhibits strong intention to lead the task. Experimental results show that the proposed method yields better overall performance than fixed-role interactions.

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