Extending Task and Motion Planning with Feasibility Prediction: Towards Multi-Robot Manipulation Planning of Realistic Objects

Abstract

The hybrid discrete/continuous nature of task and motion planning (TAMP) results often in a combinatorial explosion. This challenge is even more pronounced in multi-robot TAMP problems due to the increase in dimensionality of the action space. Previous works use action feasibility prediction as a heuristic to accelerate TAMP. However, these methods are limited to box-shaped objects and specific single or dual robot settings. In this paper, we propose a feasibility-enabled multi-robot TAMP algorithm capable of tackling complex multi-robot manipulation problems. Also, we expand on our previous work on action and grasp feasibility prediction [1] by extending its use to mesh-shaped objects. We demonstrate the performance of our method compared to a non feasibility-informed baseline, and show its ability to handle TAMP problems requiring the collaboration of multiple robots.