A Distributed Dynamic Framework to Allocate Collaborative Tasks Based on Capability Matching in Heterogeneous Multirobot Systems
- Resource Type
- Periodical
- Authors
- Lee, H.; Zhou, P.; Zhang, B.; Qiu, L.; Fan, B.; Duan, A.; Tang, J.; Lam, T.L.; Navarro-Alarcon, D.
- Source
- IEEE Transactions on Cognitive and Developmental Systems IEEE Trans. Cogn. Dev. Syst. Cognitive and Developmental Systems, IEEE Transactions on. 16(1):251-265 Feb, 2024
- Subject
- Computing and Processing
Signal Processing and Analysis
Robots
Task analysis
Robot kinematics
Collaboration
Resource management
Hardware
Robot sensing systems
Capability modeling
cognitive systems
multi-robot systems (MRSs)
resource allocation
task allocation
- Language
- ISSN
- 2379-8920
2379-8939
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.