Foraging constitutes one of the main benchmarks in robotic problems. It is known as the act of searching for objects/tokens and, when found, transport them to one or multiple locations. Swarm intelligence based algorithms have been widely used in foraging problem. The ambient light sensors technology in nowadays robots makes easy using and implementing luminous swarm intelligence-based algorithms such as the Firefly and the Glow-worm algorithms. In this paper, we propose a swarm intelligence-based foraging algorithm called Lévy walk and Firefly Foraging Algorithm (LFFA) which is a hybridizing of the two algorithms Lévy Walk and Firefly Algorithm. Numerical experiments to test the performances are conducted on the ARGoS robotic simulator.
A lévy walk and firefly based multi-robots foraging algorithm
Fortino G.
2019-01-01
Abstract
Foraging constitutes one of the main benchmarks in robotic problems. It is known as the act of searching for objects/tokens and, when found, transport them to one or multiple locations. Swarm intelligence based algorithms have been widely used in foraging problem. The ambient light sensors technology in nowadays robots makes easy using and implementing luminous swarm intelligence-based algorithms such as the Firefly and the Glow-worm algorithms. In this paper, we propose a swarm intelligence-based foraging algorithm called Lévy walk and Firefly Foraging Algorithm (LFFA) which is a hybridizing of the two algorithms Lévy Walk and Firefly Algorithm. Numerical experiments to test the performances are conducted on the ARGoS robotic simulator.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
