Learning to Predict Action Feasibility for Task and Motion Planning in 3D Environments
Smail Ait Bouhsain,Rachid Alami,Thierry Siméon,Smail Ait Bouhsain,Rachid Alami,Thierry Siméon
In Task and motion planning (TAMP), symbolic search is combined with continuous geometric planning. A task planner finds an action sequence while a motion planner checks its feasibility and plans the corresponding sequence of motions. However, due to the high combinatorial complexity of discrete search, the number of calls to the geometric planner can be very large. Previous works [1] [2] leverage...
