Efficient Obstacle Rearrangement for Object Manipulation Tasks in Cluttered Environments
This addresses the challenge of performing manipulation tasks like retrieving objects from shelves or fridges in service domains, though it appears incremental as it adapts existing collision avoidance schemes.
The paper tackles the problem of efficiently planning obstacle rearrangement for robotic manipulation in cluttered environments, where no collision-free path exists, and shows that their method improves execution time by up to 31% compared to competitors in simulations.
We present an algorithm that produces a plan for relocating obstacles in order to grasp a target in clutter by a robotic manipulator without collisions. We consider configurations where objects are densely populated in a constrained and confined space. Thus, there exists no collision-free path for the manipulator without relocating obstacles. Since the problem of planning for object rearrangement has shown to be NP-hard, it is difficult to perform manipulation tasks efficiently which could frequently happen in service domains (e.g., taking out a target from a shelf or a fridge). Our proposed planner employs a collision avoidance scheme which has been widely used in mobile robot navigation. The planner determines an obstacle to be removed quickly in real time. It also can deal with dynamic changes in the configuration (e.g., changes in object poses). Our method is shown to be complete and runs in polynomial time. Experimental results in a realistic simulated environment show that our method improves up to 31% of the execution time compared to other competitors.