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.

Path planning in formation and collision avoidance for multi-agent systems / CEN CHENG, PANGCHENG DAVID; Indri, Marina; Possieri, Corrado; Sassano, Mario; Sibona, Fiorella. - In: NONLINEAR ANALYSIS. - ISSN 1751-570X. - STAMPA. - 47:(2023), p. 101293. [10.1016/j.nahs.2022.101293]

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

Pangcheng David Cen Cheng;Marina Indri;Corrado Possieri;Fiorella Sibona
2023

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2972192