  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.
