The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Decentralized control of cooperative robotic vehicles: theory and application
Abstract
Describes how decentralized control theory can be used to analyze the control of multiple cooperative robotic vehicles. Models of cooperation are discussed and related to the input/output reachability, structural observability, and controllability of the entire system. Whereas decentralized control research in the past has concentrated on using decentralized controllers to partition complex physically interconnected systems, this work uses decentralized methods to connect otherwise independent nontouching robotic vehicles so that they behave in a stable, coordinated fashion. A vector Liapunov method is used to prove stability of two examples: the controlled motion of multiple vehicles along a line and the controlled motion of multiple vehicles in formation. Also presented are three applications of this theory: controlling a formation, guarding a perimeter, and surrounding a facility.
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Cites
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Modeling and control of formations of nonholonomic mobile robots
Desai, J. P., Ostrowski, J. P., & Kumar, V. (2001) · IEEE Transactions on Robotics and Automation · doi:10.1109/70.976023 · Cited by 1,158
Controlling formations of multiple mobile robots
Desai, J. P., Ostrowski, J., & Kumar, V. (2002) · Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146) · doi:10.1109/robot.1998.680621 · Cited by 686
Decentralized overlapping control of a platoon of vehicles
Stanković, S., Stanojević, M. J., & Šiljak, D. D. (2000) · IEEE Transactions on Control Systems Technology · doi:10.1109/87.865854 · Cited by 629
Robot control: the task function approach
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Cooperative mobile robotics: antecedents and directions
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Cited by
Local Control Strategies for Groups of Mobile Autonomous Agents
Lin, Z., Broucke, M., & Francis, B. (2004) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2004.825639 · Cited by 850
A framework of space–time continuous models for algorithm design in swarm robotics
Hamann, H., & Wörn, H. (2008) · Swarm Intelligence · doi:10.1007/s11721-008-0015-3 · Cited by 134
Lyapunov-Based Reinforcement Learning for Decentralized Multi-agent Control
Zhang, Q., Dong, H., & Pan, W. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-64096-5_5 · Cited by 18
Metadata
- Authors
- Feddema, J. T., Lewis, C., & Schoenwald, D. A.
- Venue
- IEEE Transactions on Robotics and Automation
- Published
- 2002-10
- Volume
- 18
- Issue
- 5
- Pages
- 852-864
- ISSN
- 1042-296X (ISSN-L)
- OpenAlex
- W2103171634
- Cited by
- 256
- References
- 22
- FWCI
- 15.17
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
