Safety-Aware Nonlinear Model Predictive Control for Physical Human-Robot Interaction
Oleinikov A. Kusdavletov S. Shintemirov A. Rubagotti M.
July 2021Institute of Electrical and Electronics Engineers Inc.
IEEE Robotics and Automation Letters
2021#6Issue 35665 - 5672 pp.
This letter proposes a nonlinear model predictive control (NMPC) approach for real-time planning of point-to-point motions of serial robot manipulators that share their workspace with a human. The NMPC law solves a nonlinear program online, based on a kinematic model, and guarantees safety by constraining the robot speed within the time-varying bounds determined by the speed-and-separation-monitoring (SSM) principle. Closed-loop stability is proven in detail, and the performance (in terms of productivity) of the proposed method is tested against standard SSM schemes via experiments on a Kinova Gen3 robot.
human-aware motion planning , nonlinear model predictive control , Optimization and optimal control , physical human-robot interaction , speed and separation monitoring
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Department of Robotics and Mechatronics, School of Engineering and Digital Sciences, Nazarbayev University, Nur-Sultan, Kazakhstan
Department of Robotics and Mechatronics
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