Simultaneous Action and Grasp Feasibility Prediction for Task and Motion Planning Through Multi-Task Learning
Smail Ait Bouhsain,Rachid Alami,Thierry Siméon,Smail Ait Bouhsain,Rachid Alami,Thierry Siméon
In this paper, we address task and motion plan-ning (TAMP) which is an important yet challenging robotics problem. It is known to suffer from the high combinatorial complexity of discrete search, often requiring a large number of geometric planning calls. We build upon recent works in TAMP by taking advantage of learning methods to provide action feasibility information as a heuristic to the symbo...
