Efficient Obstacle Rearrangement for Object Manipulation Tasks in Cluttered Environments
| Autor: | Younggil Cho, Changjoo Nam, Changhwan Kim, Jinhwi Lee, Jong Hyeon Park |
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| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
0209 industrial biotechnology Collision avoidance (spacecraft) Computer science business.industry GRASP Robot manipulator 02 engineering and technology Robot end effector Object (computer science) Mobile robot navigation law.invention Computer Science - Robotics 020901 industrial engineering & automation law Obstacle Path (graph theory) 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence Manipulator business Robotics (cs.RO) |
| Zdroj: | ICRA |
| DOI: | 10.48550/arxiv.1902.06907 |
| Popis: | 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. Comment: Accepted for presentation at IEEE ICRA 2019 |
| Databáze: | OpenAIRE |
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