Variable impedance control with regard to working process for man-machine cooperation-work system

Tsumugiwa, Toru; Yokogawa, Ryuichi; Hara, Kei

doi:10.1109/iros.2001.977202

Cited by 44 publications

(21 citation statements)

References 7 publications

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“…For example, variable impedance control is necessary in human-robot collaboration Tsumugiwa et al (2001Tsumugiwa et al ( , 2002 and explosive movement Braun et al (2012a,b). Although the methods discussed in Tsumugiwa et al (2001Tsumugiwa et al ( , 2002 provide a better control performance in the sense of more efficient human-robot collaboration, the resulted impedance parameters (mass, damping and stiffness) are obtained in a heuristical way and cannot be easily extended to other applications. To cope with this problem, iterative learning has been studied to obtain impedance parameters subject to unknown environments in an analytic way.…”

Section: Introductionmentioning

confidence: 99%

Impedance adaptation for optimal robot–environment interaction

Wang

2013

International Journal of Control

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In this paper, impedance adaptation is investigated for robots interacting with unknown environments. Impedance control is employed for the physical interaction between robots and environments, subject to unknown and uncertain environments dynamics. The unknown environments are described as linear systems with unknown dynamics, based on which the desired impedance model is obtained. A cost function that measures the tracking error and interaction force is defined, and the critical impedance parameters are found to minimize it. Without requiring the information of the environments dynamics, the proposed impedance adaptation is feasible in a large number of applications where robots physically interact with unknown environments. The validity of the proposed method is verified through simulation studies.

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Section: Introductionmentioning

confidence: 99%

Impedance adaptation for optimal robot–environment interaction

Wang

2013

International Journal of Control

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“…State-of-the-art systems based on impedance control [1] provides interesting bricks in understanding what could probably be sub-modules of the overall solution. Many implementation show interesting performances [2], [3], [4], [5], [6], yet they affix the robot a pure follower role. Though one may say that, to some extent, a robot can perform simple collaborative tasks, it certainly is unable to negotiate them with their human partners.…”

Section: Introductionmentioning

confidence: 99%

Teaching physical collaborative tasks: object-lifting case study with a humanoid

Evrard

Gribovskaya²,

Calinon

et al. 2009

2009 9th IEEE-RAS International Conference on Humanoid Robots

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Abstract-This paper presents the application of a statistical framework that allows to endow a humanoid robot with the ability to perform a collaborative manipulation task with a human operator. We investigate to what extent the dynamics of the motion and the haptic communication process that takes place during physical collaborative tasks can be encapsulated by the probabilistic model. This framework encodes the dataset in a Gaussian Mixture Model, which components represent the local correlations across the variables that characterize the task. A set of demonstrations is performed using a bilateral coupling teleoperation setup; then the statistical model is trained in a pure follower/leader role distribution mode between the human and robot alternatively. The task is reproduced using Gaussian Mixture Regression. We present the probabilistic model and the experimental results obtained on the humanoid platform HRP-2; preliminary results assess our theory on switching behavior modes in dyad collaborative tasks: when reproduced with users which were not instructed to behave in either a follower or a leader mode, the robot switched automatically between the learned leader and follower behaviors.

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“…Velocity control is used here, as chosen previously [28][29][30] and later explained: 31 with position control, the IAD would be attracted to a given reference position that does not represent the desired human behavior. Figure 1 presents the control scheme, in which the velocity controller used in the experiments is of the proportional type.…”

Section: Modeling Physical Interactionmentioning

confidence: 99%

Modeling of physical human–robot interaction

Campeau-Lecours

Otis

Gosselin

2016

International Journal of Advanced Robotic Systems

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Enhancement of human performance using an intelligent assist device is becoming more common. In order to achieve effective augmentation of human capacity, cooperation between human and robot must be safe and very intuitive. Ensuring such collaboration remains a challenge, especially when admittance control is used. This paper addresses the issues of transparency and human perception coming from vibration in admittance control schemes. Simulation results obtained with our suggested improved model using an admittance controller are presented, then four models using transfer functions are discussed in detail and evaluated as a means of simulating physical human-robot interaction using admittance control. The simulation and experimental results are then compared in order to assess the validity and limitations of the proposed models in the case of a four-degree-of-freedom intelligent assist device designed for large payload.

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Variable impedance control with regard to working process for man-machine cooperation-work system

Cited by 44 publications

References 7 publications

Impedance adaptation for optimal robot–environment interaction

Impedance adaptation for optimal robot–environment interaction

Teaching physical collaborative tasks: object-lifting case study with a humanoid

Modeling of physical human–robot interaction

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