Combine Task And Motion Planner
Duong Le / August 2020 (78 Words, 1 Minutes)
Link To Paper: Interactive Search for Action and Motion Planning with Dynamics
This paper proposes an interactive search approach, termed INTERACT, which couples sampling-based motion planning with action planning in order to effectively solve the com- bined task- and motion-planning problem. INTERACT is geared toward scenarios involving a mobile robot operating in a fully-known environment consisting of static and movable objects. INTERACT makes it possible to specify a task in the planning-domain definition language (PDDL) and automatically computes a collision-free and dynamically-feasible trajectory that enables the robot to accomplish the task. The coupling of sampling-based motion planning with action planning is made possible by expanding a tree of feasible motions and partition- ing it into equivalence classes based on the task predicates. Action plans provide guidance as to which a equivalence class should be further expanded. Information gathered during the motion-tree expansion is used to adjust the action costs in order to effectively guide the expansion toward the goal. This interactive process of selecting an equivalence class, expand- ing the motion tree to implement its action plan, and updating the action costs and plans to reflect the progress made is repeated until a solution is found. Experimental validation is provided in simulation using a robotic vehicle to accomplish sophisticated pick-and-place tasks. Comparisons to previous work show significant improvements.
Task and Motion Planning: Robot moves object to corresponding room with rule (only 1 object in 1 room at a time)