TY - GEN
T1 - Continuum Deformation Coordination of Multi-Agent Systems Using Cooperative Localization
AU - Rastgoftar, Hossein
AU - Nersesov, Sergey
AU - Ashrafiuon, Hashem
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - This paper studies the problem of decentralized continuum deformation coordination of multi-agent systems aided by cooperative localization. We treat agents as particles inside a triangular continuum (deformable body) in a 2-D motion space and let the continuum deformation coordination be defined by three leaders located at vertices of a triangle, called the leading triangle. The leaders' desired trajectories are assigned as the solution of a constrained optimal control problem such that safety requirements are satisfied in the presence of disturbance and measurement noise. Followers distributed inside the leading triangle acquire continuum deformation in a decentralized fashion by integrating cooperative localization and local communication. Specifically, cooperative localization estimates the global positions of all agents using relative position measurements based primarily on proximity of agents. Simulation results are presented for a network of ten agents.
AB - This paper studies the problem of decentralized continuum deformation coordination of multi-agent systems aided by cooperative localization. We treat agents as particles inside a triangular continuum (deformable body) in a 2-D motion space and let the continuum deformation coordination be defined by three leaders located at vertices of a triangle, called the leading triangle. The leaders' desired trajectories are assigned as the solution of a constrained optimal control problem such that safety requirements are satisfied in the presence of disturbance and measurement noise. Followers distributed inside the leading triangle acquire continuum deformation in a decentralized fashion by integrating cooperative localization and local communication. Specifically, cooperative localization estimates the global positions of all agents using relative position measurements based primarily on proximity of agents. Simulation results are presented for a network of ten agents.
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U2 - 10.1109/CCTA48906.2021.9659176
DO - 10.1109/CCTA48906.2021.9659176
M3 - Conference contribution
AN - SCOPUS:85124795264
T3 - CCTA 2021 - 5th IEEE Conference on Control Technology and Applications
SP - 90
EP - 96
BT - CCTA 2021 - 5th IEEE Conference on Control Technology and Applications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE Conference on Control Technology and Applications, CCTA 2021
Y2 - 8 August 2021 through 11 August 2021
ER -