Complementary Stability and Loop Shaping for Improved Human–Robot Interaction

Buerger, Stephen; Hogan, Neville

doi:10.1109/tro.2007.892229

Cited by 239 publications

(203 citation statements)

References 23 publications

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“…For instance, although the dynamics of human arm changes over time, human arm impedance vary in a limited range [6], [7]. Knowing that human arm impedance is bounded, Buerger and Hogan [8] propose a complementary stability approach, and design a controller which robustly maintains stability in this bounded range. This approach relaxes the conservative constraints of the passivity approach.…”

Section: A Physical Human Robot Interactionmentioning

confidence: 99%

Fractional order admittance control for physical human-robot interaction

Aydın

Tokatlı

Patoğlu

et al. 2017

2017 IEEE World Haptics Conference (WHC)

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Abstract-In physical human-robot interaction (pHRI), the cognitive skill of a human is combined with the accuracy, repeatability and strength of a robot. While the promises and potential outcomes of pHRI are glamorous, the control of such coupled systems is challenging in many aspects. In this paper, we propose a new controller, fractional order admittance controller, for pHRI systems. The stability analysis of the new control system with human in-the-loop is performed and the interaction performance is investigated experimentally with 10 subjects during a task imitating a contact with a stiff environment. The results show that the fractional order controller is more robust than the standard admittance controller and helps to reduce the human effort in task execution.

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Section: A Physical Human Robot Interactionmentioning

confidence: 99%

Fractional order admittance control for physical human-robot interaction

Aydın

Tokatlı

Patoğlu

et al. 2017

2017 IEEE World Haptics Conference (WHC)

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“…The impedance parameters of the human arm C H and K H are assumed to be diagonal, and their values are determined from [28]: ( T . In order to obtain different role allocations of human and robot, different sets of Q and R in Equ.…”

Section: A Parametersmentioning

confidence: 99%

Shared control of human and robot by approximate dynamic programming

Tee

Yan

et al. 2015

2015 American Control Conference (ACC)

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Abstract-This paper aims at proposing a general framework of human-robot shared control for a natural and effective interface. A typical human-robot collaboration scenario is investigated, and a framework of shared control is developed based on finding the solution to an optimization problem. Human dynamics are taken into account in the analysis of the coupled human-robot system, and objectives of both human and robot are considered. Approximate dynamic programming is employed to solve the optimization problem in the presence of unknown human and robot dynamics. The validity of the proposed method is verified through simulation studies.

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“…Early research effort has been made on tracking a given impedance model with a fixed reference trajectory in the presence of unknown robot model and uncertainties, e.g., [6], [7], [8]. In many situations, to impose a fixed impedance model to the robot is too conservative and the knowledge of the environment dynamics is required to specify a target impedance model [9], [10]. In recent studies, how to obtain an impedance model and a reference trajectory that result in desired interaction performance has attracted much attention.…”

Section: Introductionmentioning

confidence: 99%

Reference Adaptation for Robots in Physical Interactions With Unknown Environments

Wang

et al. 2017

IEEE Trans. Cybern.

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Abstract-In this paper, we propose a method of reference adaptation for robots in physical interactions with unknown environments. A cost function is constructed to describe the interaction performance, which combines trajectory tracking error and interaction force between the robot and the environment. It is minimized by the proposed reference adaptation based on trajectory parametrization and iterative learning. An adaptive impedance control is developed to make the robot be governed by the target impedance model. Simulation and experiment studies are conducted to verify the effectiveness of the proposed method.

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Complementary Stability and Loop Shaping for Improved Human–Robot Interaction

Cited by 239 publications

References 23 publications

Fractional order admittance control for physical human-robot interaction

Fractional order admittance control for physical human-robot interaction

Shared control of human and robot by approximate dynamic programming

Reference Adaptation for Robots in Physical Interactions With Unknown Environments

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