A Multi-Task Velocity-Based Redundancy Resolution Strategy for Unmanned Aerial Manipulators

Abstract

Unmanned aerial manipulators (UAMs) provide a remarkable level of dexterity on performing complex aerial manipulation tasks thanks to their high number of degrees of freedom (DOFs). By taking advantage of this redundancy, in this paper, a multi-task online redundancy resolution strategy is proposed to accomplish multiple UAM tasks while satisfying additional constraints such as joint angle limit and obstacle avoidance. The proposed approach is computationally inexpensive to run online, allowing UAM to dynamically react to unforeseen events by modifying its configuration during the execution of the primary task. In addition, the proposed approach incorporates the maximization of the manipulability measure into the objective function of the redundancy resolution framework. Moreover, in order to ensure the motion smoothness and satisfy the robot physical constraints the task relaxation approach for aerial manipulation is presented. Extensive simulation studies in ROS-Gazebo environment are performed to validate the performance of the proposed approach.