Task Space Motion Planning Decomposition



Publication Details

Larkin, N., Short, A., Pan, Z. & van Duin, S. (2018). Task Space Motion Planning Decomposition. Proceedings - IEEE International Conference on Robotics and Automation (pp. 1688-1694). United States: IEEE.


In autonomous robotics there are many situations that require solving a motion planning problem to complete a task. A Task Space (T-Space), composed of parameters that define the task being performed, can be a more effective planning space for these problems, however, planning within a T-Space is often computationally challenging. In this paper, we present a novel method to analyse the relationship between T-Space parameters and the pose of manipulator bodies to create a dependency matrix. We then use this information to decompose the motion planning problem into sequential lower complexity sub-problems. We call this approach Task Space Motion Planning Decomposition (TSMPD). This paper introduces TSMPD and quantifies the improvement to planning efficiency on a challenging maze navigation problem and weld path planning problem.

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