Task Priority Matrix at the acceleration level: Collision avoidance under relaxed constraints

Maram Khatib, Khaled Al Khudir, Alessandro De Luca

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


We propose a new approach for executing the main Cartesian tasks assigned to a redundant robot while guaranteeing whole-body collision avoidance. The robot degrees of freedom are fully utilized by introducing relaxed constraints in the definition of operational and collision avoidance tasks. Desired priorities for each task are assigned using the so-called Task Priority Matrix (TPM) method [1], which is independent from the redundancy resolution law and handles efficiently switching of priorities. To ensure smooth motion during such task reordering, a control scheme with a suitable task allocation algorithm is developed at the acceleration level. The proposed approach is validated with MATLAB simulations and an experimental evaluation using the 7-dof KUKA LWR manipulator.
Original languageEnglish
Article number9126194
Pages (from-to)4970-4977
Number of pages8
Journal IEEE Robotics and Automation Letters
Issue number3
Publication statusPublished - 25 Jun 2020
Externally publishedYes


  • Motion control
  • collision avoidance
  • redundant robots

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence


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