期刊
IEEE ROBOTICS AND AUTOMATION LETTERS
卷 7, 期 2, 页码 3138-3145出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LRA.2022.3145987
关键词
Multi-robot systems; task planning; manipulation planning
类别
资金
- European Union's Horizon 2020 Research and Innovation Program [73273, 101017274]
- Italian Ministry of Education, and Research (MIUR) through CrossLab Project (Departments of Excellence)
Multi-robot systems are gaining popularity in warehouses and factories due to their ability to provide more efficient and complex task solutions. This article introduces a method based on a hierarchical planning framework to address the complexity in multi-robot systems, and validates the effectiveness of the method through experiments.
Multi-robot systems are becoming increasingly popular in warehouses and factories, since they potentially enable the development of more versatile and robust systems than single robots. Multiple robots allow performing complex tasks with greater efficiency. However, this leads to increased complexity in planning and dispatching actions to robots. In this letter, we tackle such complexity using a hierarchical planning framework: the task is first planned at an abstract level and then refined by local motion planning. We propose a framework based on a state-transition system formalism that abstracts the problem by removing unnecessary details and, hence, considerably reduces planning space complexity. Forward search from an initial state allows the robot to find a sequence of actions to accomplish the assigned task. These actions can be planned at a lower level employing any motion planning technique available in the literature. The proposed method is validated through experiments in several operating conditions and scenarios.
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