Particle swarm-based olfactory guided search
Autonomous Robots
WSEAS TRANSACTIONS on SYSTEMS
Robotics and Autonomous Systems
Multi-robot based chemical plume tracing with virtual odor-source-probability sensor
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
IEEE Computational Intelligence Magazine
Moth-inspired chemical plume tracing on an autonomous underwater vehicle
IEEE Transactions on Robotics
Plume mapping via hidden Markov methods
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Chemical Plume Source Localization
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Design of a digital management system for the sintering material ground
International Journal of Automation and Computing
| Hi-index | 0.00 |
This paper is concerned with the problem of odor source localization using multi-robot system. A learning particle swarm optimization algorithm, which can coordinate a multi-robot system to locate the odor source, is proposed. First, in order to develop the proposed algorithm, a source probability map for a robot is built and updated by using concentration magnitude information, wind information, and swarm information. Based on the source probability map, the new position of the robot can be generated. Second, a distributed coordination architecture, by which the proposed algorithm can run on the multi-robot system, is designed. Specifically, the proposed algorithm is used on the group level to generate a new position for the robot. A consensus algorithm is then adopted on the robot level in order to control the robot to move from the current position to the new position. Finally, the effectiveness of the proposed algorithm is illustrated for the odor source localization problem.