Adaptive impedance control for natural human-robot collaboration

Authors:
Yanan Li;Shuzhi Sam Ge;Keng Peng Tee
Affiliations:
National University of Singapore;National University of Singapore;A*STAR
Venue:
Proceedings of the Workshop at SIGGRAPH Asia
Year:
2012

Citing 9
Cited 0

On the adaptive control of robot manipulators

International Journal of Robotics Research
Force tracking in impedance control

International Journal of Robotics Research
Adaptive Neural Network Control of Robotic Manipulators

Adaptive Neural Network Control of Robotic Manipulators
An HMM approach to realistic haptic human-robot interaction

WHC '09 Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems
Impedance learning for robotic contact tasks using natural actor-critic algorithm

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Human-intent detection and physically interactive control of a robot without force sensors

IEEE Transactions on Robotics
Learning variable impedance control

International Journal of Robotics Research
Adjusting the parameters of the mechanical impedance for velocity, impact and force control

Robotica
Motion synchronization for human-robot collaboration

ICSR'12 Proceedings of the 4th international conference on Social Robotics

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, adaptive impedance control is developed for natural human-robot collaboration. In order to make the robot collaborate with its human partner efficiently, neural networks are employed to estimate the unknown desired trajectory of the human partner and zero force tracking is achieved under impedance control. The control performance of the collaboration system are discussed through the rigorous analysis. The validity of the proposed method is verified through simulation studies.