Efficient Obstacle Rearrangement for Object Manipulation Tasks in Cluttered Environments
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Abstract (arXiv)
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.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Feb 2019.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 4; 2024: 1.
7 papers.
- 2023SG-Bot: Object Rearrangement via Coarse-to-Fine Robotic Imagination on Scene Graphscited by 24
- 2023Learning Environment-Aware Affordance for 3D Articulated Object Manipulation under Occlusionscited by 23
- 2024PreAfford: Universal Affordance-Based Pre-Grasping for Diverse Objects and Environmentscited by 11
- 2021Efficient and High-quality Prehensile Rearrangement in Cluttered and Confined Spacescited by 5
- 2021Semi-Autonomous Teleoperation via Learning Non-Prehensile Manipulation Skillscited by 2
- 2023Planning for Manipulation among Movable Objects: Deciding Which Objects Go Where, in What Order, and Howcited by 2
- 2023Planning for Complex Non-prehensile Manipulation Among Movable Objects by Interleaving Multi-Agent Pathfinding and Physics-Based Simulationcited by 0
- 2024PreAfford: Universal Affordance-Based Pre-Grasping for Diverse Objects and Environments4 Apr 2024
- 2023SG-Bot: Object Rearrangement via Coarse-to-Fine Robotic Imagination on Scene Graphs21 Sep 2023
- 2023Learning Environment-Aware Affordance for 3D Articulated Object Manipulation under Occlusions14 Sep 2023
- 2023Planning for Manipulation among Movable Objects: Deciding Which Objects Go Where, in What Order, and How23 Mar 2023
- 2023Planning for Complex Non-prehensile Manipulation Among Movable Objects by Interleaving Multi-Agent Pathfinding and Physics-Based Simulation23 Mar 2023
- 2021Efficient and High-quality Prehensile Rearrangement in Cluttered and Confined Spaces6 Oct 2021
- 2021Semi-Autonomous Teleoperation via Learning Non-Prehensile Manipulation Skills27 Sep 2021