Safety-Aware Nonlinear Model Predictive Control for Physical Human-Robot Interaction

Artemiy Oleinikov; Sanzhar Kusdavletov; Almas Shintemirov; Matteo Rubagotti

RA-L 202125 citations

Safety-Aware Nonlinear Model Predictive Control for Physical Human-Robot Interaction

Artemiy Oleinikov, Sanzhar Kusdavletov, Almas Shintemirov, Matteo Rubagotti

Abstract

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.

BibTeX

@inproceedings{ral2021_safetyawarenonli,
  title = {Safety-Aware Nonlinear Model Predictive Control for Physical Human-Robot Interaction},
  author = {Artemiy Oleinikov and Sanzhar Kusdavletov and Almas Shintemirov and Matteo Rubagotti},
  booktitle = {RA-L 2021},
  year = {2021}
}