Division of labor in a group of robots inspired by ants' foraging behavior
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Multi-robot learning with particle swarm optimization
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Distributed Adaptation in Multi-robot Search Using Particle Swarm Optimization
SAB '08 Proceedings of the 10th international conference on Simulation of Adaptive Behavior: From Animals to Animats
Engineering Applications of Artificial Intelligence
AntNet: distributed stigmergetic control for communications networks
Journal of Artificial Intelligence Research
Coordinated multi-robot exploration
IEEE Transactions on Robotics
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This paper presents a particle swarm optimization (PSO)-inspired multi-robot search application based on an innovative software system for collaborative robotic applications. The system has a multi-layer architecture which provides low- and high-level interfaces to the robots, resource (robots) management, security policies and concurrent robot access. The main result is the successful testing of the PSO-inspired algorithm on real-world experiments, using Khepera III and e-puck robots. Simulated results obtained in other studies are therefore validated by the real-world experiments. Differences between simulation and real-world experiments are presented and discussed critically.