Improving Redundancy Availability: Dynamic Subtasks Modulation for Robots with Redundancy Insufficiency
This work is significant for robotics researchers and practitioners dealing with complex robot applications where the number of constraints often exceeds the robot's redundant degrees of freedom.
This paper addresses the challenge of robots performing complex tasks with multiple constraints despite having insufficient redundancy. The authors propose a novel subtask merging strategy that dynamically modulates a virtual secondary task, incorporating task status and soft priority, to improve the overall efficiency of redundancy resolution.
This work presents an approach for robots to suitably carry out complex applications characterized by the presence of multiple additional constraints or subtasks (e.g. obstacle and self-collision avoidance) but subject to redundancy insufficiency. The proposed approach, based on a novel subtask merging strategy, enforces all subtasks in due course by dynamically modulating a virtual secondary task, where the task status and soft priority are incorporated to improve the overall efficiency of redundancy resolution. The proposed approach greatly improves the redundancy availability by unitizing and deploying subtasks in a fine-grained and compact manner. We build up our control framework on the null space projection, which guarantees the execution of subtasks does not interfere with the primary task. Experimental results on two case studies are presented to show the performance of our approach.