A Novel Decentralized Leader–follower Control Scheme for Centroid and Formation Tracking
(2025) In IEEE Transactions on Control of Network Systems- Abstract
This paper deals with the centroid and formation control problem of multi–agent robotic systems. The proposed solution is based on a leader–follower scheme, where only a subset of agents, i.e., the leaders, knows the desired trajectories for the centroid and the formation of the system, while the other agents, i.e., the followers, are required to estimate them through a dynamic consensus scheme. The leaders perform trajectory scaling in order to cope with velocity limits of the single robots. Once the trajectories for the centroid and the formation are estimated, each agent can compute its own reference trajectory and a local control loop is designed to track it. An approach to map the velocity constraints of each agent to the velocity... (More)
This paper deals with the centroid and formation control problem of multi–agent robotic systems. The proposed solution is based on a leader–follower scheme, where only a subset of agents, i.e., the leaders, knows the desired trajectories for the centroid and the formation of the system, while the other agents, i.e., the followers, are required to estimate them through a dynamic consensus scheme. The leaders perform trajectory scaling in order to cope with velocity limits of the single robots. Once the trajectories for the centroid and the formation are estimated, each agent can compute its own reference trajectory and a local control loop is designed to track it. An approach to map the velocity constraints of each agent to the velocity limits at the task level is developed. Then, a trajectory scaling algorithm is adopted to ensure velocity constraints fulfillment. The stability and performance properties are rigorously analyzed under two different assumptions about the planned trajectories. Finally, both simulation and experiments are run on Robotarium platform to show the effectiveness of the approach and the effect of parameter tuning on the achieved performance.
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- author
- Sileo, Monica
; Karayiannidis, Yiannis
LU
; Pierri, Francesco and Caccavale, Fabrizio
- organization
- publishing date
- 2025
- type
- Contribution to journal
- publication status
- in press
- subject
- keywords
- decentralized estimation and control, Multi–agent systems, multi–robot systems, networked systems
- in
- IEEE Transactions on Control of Network Systems
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- external identifiers
-
- scopus:105001171992
- ISSN
- 2325-5870
- DOI
- 10.1109/TCNS.2025.3552377
- project
- Hand-arm coordination control for robotic interaction tasks
- RobotLab LTH
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2014 IEEE.
- id
- 916589fd-3413-4a21-9c91-60d5f75f892b
- date added to LUP
- 2025-04-09 19:45:58
- date last changed
- 2025-05-13 14:54:45
@article{916589fd-3413-4a21-9c91-60d5f75f892b, abstract = {{<p>This paper deals with the centroid and formation control problem of multi–agent robotic systems. The proposed solution is based on a leader–follower scheme, where only a subset of agents, i.e., the leaders, knows the desired trajectories for the centroid and the formation of the system, while the other agents, i.e., the followers, are required to estimate them through a dynamic consensus scheme. The leaders perform trajectory scaling in order to cope with velocity limits of the single robots. Once the trajectories for the centroid and the formation are estimated, each agent can compute its own reference trajectory and a local control loop is designed to track it. An approach to map the velocity constraints of each agent to the velocity limits at the task level is developed. Then, a trajectory scaling algorithm is adopted to ensure velocity constraints fulfillment. The stability and performance properties are rigorously analyzed under two different assumptions about the planned trajectories. Finally, both simulation and experiments are run on Robotarium platform to show the effectiveness of the approach and the effect of parameter tuning on the achieved performance.</p>}}, author = {{Sileo, Monica and Karayiannidis, Yiannis and Pierri, Francesco and Caccavale, Fabrizio}}, issn = {{2325-5870}}, keywords = {{decentralized estimation and control; Multi–agent systems; multi–robot systems; networked systems}}, language = {{eng}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, series = {{IEEE Transactions on Control of Network Systems}}, title = {{A Novel Decentralized Leader–follower Control Scheme for Centroid and Formation Tracking}}, url = {{http://dx.doi.org/10.1109/TCNS.2025.3552377}}, doi = {{10.1109/TCNS.2025.3552377}}, year = {{2025}}, }