A Distributed Dynamic Framework to Allocate Collaborative Tasks Based on Capability Matching in Heterogeneous Multirobot Systems

Collaboration among a group of robots with heterogeneous capabilities is an important research problem that enables to combine different robot functionalities, and thus, conducts complex tasks that may be difficult to achieve by a single robot with limited resources. In this article, we propose a ne...

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Bibliographic Details
Published in:IEEE transactions on cognitive and developmental systems 2024-02, Vol.16 (1), p.251-265
Main Authors: Lee, Hoi-Yin, Zhou, Peng, Zhang, Bin, Qiu, Liuming, Fan, Bowen, Duan, Anqing, Tang, Jingtao, Lam, Tin Lun, Navarro-Alarcon, David
Format: Article
Language:English
Subjects:
Algorithms
Capability modeling
cognitive systems
Collaboration
Hardware
Knowledge representation
Matching
Motion planning
multi-robot systems (MRSs)
Multiple robots
resource allocation
Resource management
Resource utilization
Robot kinematics
Robot sensing systems
Robots
task allocation
Task analysis
Task complexity
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Summary:Collaboration among a group of robots with heterogeneous capabilities is an important research problem that enables to combine different robot functionalities, and thus, conducts complex tasks that may be difficult to achieve by a single robot with limited resources. In this article, we propose a new distributed task allocation framework based on the capability matching of heterogeneous robots. The framework is composed of an ontological dynamic knowledge graph model and a hardware control scheme to model the capability and optimize resource utilization for collaborative tasks. We introduce an intuitive hardware control scheme based on a dynamic knowledge graph that resolves possible conflicts between the hardware control of different types of robots. Action sequences are produced by a task and motion planning algorithm to collaboratively perform the assigned task. The performance of the proposed methodology is evaluated by both simulations and hardware experiments.
ISSN:2379-8920
2379-8939
DOI:10.1109/TCDS.2023.3264034