Swarm Localization and Control via On-board Sensing and Computation
Python Files For Gazebo Drone Simulation-20190728T071323Z-001.zip
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AuthorsRajab, Fat-Hy Omar
AdvisorsShamma, Jeff S.
Permanent link to this recordhttp://hdl.handle.net/10754/656197
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AbstractMulti-agent robotic system have been proved to be more superior in undertaking functionalities, arduous or even impossible when performed by single agents. The increased e ciency in multi agent systems is achieved by the execution of the task in cooperative manner. But to achieve cooperation in multi agent systems, a good localization system is an important prerequisite. Currently, most of the multi-agent system rely on the use of the GPS to provide global positioning information which su ers great deterioration in performance in indoor applications, and also all to all communication between the agents will be required which is not e cient especially when the number of agents is large. In this regard, a real-time localization scheme is introduced which makes use of the robot's on-board sensors and computational capabilities to determine the states of other agents in the multi agent system. This algorithm also takes the advantage of the swarming behaviour of the robots in the estimation of the states. This localization algorithm was found to produce more accurate agent state estimates as compared to a similar localization algorithm that does not take into account the swarming behaviour of the agents in simulations and real experiment involving two Unmanned Aerial Vehicles.
CitationRajab, F.-H. O. (2019). Swarm Localization and Control via On-board Sensing and Computation. KAUST Research Repository. https://doi.org/10.25781/KAUST-NSP83
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