Human Intention-Aware Motion Planning and Adaptive Fuzzy Control for a Collaborative Robot With Flexible Joints

Xiaoqian Ren, Zhijun Li, Meng Chu Zhou, Yingbai Hu

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

This article presents a framework to enable a human and robot to perform collaborative tasks safely and efficiently. It consists of three functions. First, human motion is predicted by utilizing Gaussian mixture regression. Second, the motion planning of an online robot is performed such that the robot can appropriately react to a human coworker while executing a task. In our proposed framework, the predicted human motion is transferred to a virtual force acting on a robot's end effector. Its initial trajectory is modified so as to avoid any collisions with the human. To obtain a smooth, collision-free, and energy-minimized trajectory, a constrained optimization problem is formulated. A neural dynamics optimization algorithm is then adopted to solve it. Third, an adaptive fuzzy controller is proposed to track the robot's desired trajectory with uncertain dynamics parameters. We provide the rigorous proof of stability for the proposed methods. The physical experiments are conducted to demonstrate the effectiveness of the proposed collaborative strategy.

Original languageEnglish (US)
Pages (from-to)2375-2388
Number of pages14
JournalIEEE Transactions on Fuzzy Systems
Volume31
Issue number7
DOIs
StatePublished - Jul 1 2023

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Applied Mathematics
  • Control and Systems Engineering
  • Computational Theory and Mathematics

Keywords

  • Adaptive control
  • collision avoidance
  • flexible-joint robot (FJR)
  • human intent prediction
  • human-robot interaction
  • robot motion planning

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