TY - GEN
T1 - Vision Based Collision Avoidance For Multi-Agent Systems Using Avoidance Functions
AU - Amrouche, Massinissa
AU - Marinho, Thiago
AU - Stipanovic, Dusan
N1 - Publisher Copyright:
© 2020 EUCA.
PY - 2020/5
Y1 - 2020/5
N2 - In this paper, a methodology for designing control strategies that guarantee collision avoidance for multi-agent systems without the information about the relative distances among the agents, is provided. The controllers are designed using avoidance functions that rely only on the visual information, that is, times-to-collision and line-of-sight angle. This method is particularly suitable to low-cost and/or small robotic systems that are not equipped with range measurement devices like radars and lidars. Finally, the collision avoidance is guaranteed using Lyapunov analysis type of technical arguments and illustrated using simulations.
AB - In this paper, a methodology for designing control strategies that guarantee collision avoidance for multi-agent systems without the information about the relative distances among the agents, is provided. The controllers are designed using avoidance functions that rely only on the visual information, that is, times-to-collision and line-of-sight angle. This method is particularly suitable to low-cost and/or small robotic systems that are not equipped with range measurement devices like radars and lidars. Finally, the collision avoidance is guaranteed using Lyapunov analysis type of technical arguments and illustrated using simulations.
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M3 - Conference contribution
AN - SCOPUS:85090143582
T3 - European Control Conference 2020, ECC 2020
SP - 1683
EP - 1688
BT - European Control Conference 2020, ECC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th European Control Conference, ECC 2020
Y2 - 12 May 2020 through 15 May 2020
ER -