Force-based Perception and Control Strategies for Human-Robot Shared Object Manipulation
To address the challenges, first, we propose an estimation method for identifying the human grasp position. We extend the conventional contact point estimation method by formulating a new identification model with the human applied torque as an unknown parameter and employing empirical conditions to estimate the human grasp position. The proposed method is compared with a conventional contact point estimation using the experimental data collected for various collaboration scenarios. Second, given the human grasp position, a control strategy is suggested to transport the object in all degrees of freedom, independently. We employ the concept of “the instantaneous center of zero velocity” to reduce the human effort by minimizing the exerted human force. The stability of the interaction is evaluated using a passivity-based analysis of the closed-loop system, including the object and the robotic manipulator. The performance of the proposed control scheme is validated through simulation of scenarios containing rotations and translations of the object.
Our study indicates that the exerted torque of the human has a significant effect on the human grasp position estimation. Besides, the knowledge of the human grasp position can be used in the control scheme design to avoid the translation/rotation problem and reduce the human effort.
human-robot interaction control
physical human-robot collaboration
Ramin Jaberzadeh Ansari
Chalmers, Elektroteknik, System- och reglerteknik, Mekatronik
Reducing the human effort for human-robot cooperative object manipulation via control design
IFAC-PapersOnLine,; Vol. 50(2017)p. 14922-14927
Paper i proceeding
Jaberzadeh Ansari R., Giordano G., Sjöberg J., Karayiannidis Y. - Human Grasp Position Estimation for Human-Robot Cooperative Object Manipulation
Innovation och entreprenörskap
Robotteknik och automation
Chalmers tekniska högskola
Room EB, Hörsalsvägen 11, Campus Johanneberg, Chalmers University of Technology.
Opponent: Martin Enqvist, Linköping University, Sweden