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 the7-dof KUKA LWR manipulator.
Task Priority Matrix at the Acceleration Level: Collision Avoidance Under Relaxed Constraints / Khatib, Maram; Al Khudir, Khaled; De Luca, Alessandro. - In: IEEE ROBOTICS AND AUTOMATION LETTERS. - ISSN 2377-3766. - 5:3(2020), pp. 4970-4977. [10.1109/LRA.2020.3004771]
Task Priority Matrix at the Acceleration Level: Collision Avoidance Under Relaxed Constraints
Khatib, Maram;Al Khudir, Khaled;De Luca, Alessandro
2020
Abstract
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 the7-dof KUKA LWR manipulator.File | Dimensione | Formato | |
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