This paper investigates, in a centralized manner, the motion planning problem for a team of unicycle-like mobile robots in a known environment. In particular, a multi-agent collision-free patrolling and formation control algorithm is presented, which combines outcomes of: (i) stability analysis of hybrid systems, (ii) algebraic geometry, and (iii) classical potential functions. The objective is achieved by designing a Lyapunov-based hybrid strategy that autonomously selects the navigation parameters. Tools borrowed from algebraic geometry are adopted to construct Lyapunov functions that guarantee the convergence to the desired formation and path, while classical potential functions are exploited to avoid collisions among agents and the fixed obstacles within the environment. The proposed navigation algorithm is tested in simulation and then validated by using the robots of a remote accessible robotic testbed.(c) 2022 Elsevier Ltd. All rights reserved.

Cheng, P., Indri, M., Possieri, C., Sassano, M., Sibona, F. (2023). Path planning in formation and collision avoidance for multi-agent systems. NONLINEAR ANALYSIS, 47 [10.1016/j.nahs.2022.101293].

Path planning in formation and collision avoidance for multi-agent systems

Possieri, C;Sassano, M;
2023-01-01

Abstract

This paper investigates, in a centralized manner, the motion planning problem for a team of unicycle-like mobile robots in a known environment. In particular, a multi-agent collision-free patrolling and formation control algorithm is presented, which combines outcomes of: (i) stability analysis of hybrid systems, (ii) algebraic geometry, and (iii) classical potential functions. The objective is achieved by designing a Lyapunov-based hybrid strategy that autonomously selects the navigation parameters. Tools borrowed from algebraic geometry are adopted to construct Lyapunov functions that guarantee the convergence to the desired formation and path, while classical potential functions are exploited to avoid collisions among agents and the fixed obstacles within the environment. The proposed navigation algorithm is tested in simulation and then validated by using the robots of a remote accessible robotic testbed.(c) 2022 Elsevier Ltd. All rights reserved.
2023
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-INF/04 - AUTOMATICA
English
Motion planning
Mobile robotics
Stability of hybrid systems
Lyapunov methods
Cheng, P., Indri, M., Possieri, C., Sassano, M., Sibona, F. (2023). Path planning in formation and collision avoidance for multi-agent systems. NONLINEAR ANALYSIS, 47 [10.1016/j.nahs.2022.101293].
Cheng, P; Indri, M; Possieri, C; Sassano, M; Sibona, F
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/308815
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