5 October 2017 Control system of the inspection robots group applying auctions and multi-criteria analysis for task allocation
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Abstract
In the paper presented is a control system of a mobile robots group intended for carrying out inspection missions. The main research problem was to define such a control system in order to facilitate a cooperation of the robots resulting in realization of the committed inspection tasks. Many of the well-known control systems use auctions for tasks allocation, where a subject of an auction is a task to be allocated. It seems that in the case of missions characterized by much larger number of tasks than number of robots it will be better if robots (instead of tasks) are subjects of auctions. The second identified problem concerns the one-sided robot-to-task fitness evaluation. Simultaneous assessment of the robot-to-task fitness and task attractiveness for robot should affect positively for the overall effectiveness of the multi-robot system performance. The elaborated system allows to assign tasks to robots using various methods for evaluation of fitness between robots and tasks, and using some tasks allocation methods. There is proposed the method for multi-criteria analysis, which is composed of two assessments, i.e. robot’s concurrency position for task among other robots and task’s attractiveness for robot among other tasks. Furthermore, there are proposed methods for tasks allocation applying the mentioned multi-criteria analysis method. The verification of both the elaborated system and the proposed tasks’ allocation methods was carried out with the help of simulated experiments. The object under test was a group of inspection mobile robots being a virtual counterpart of the real mobile-robot group.
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Wawrzyniec Panfil, Wawrzyniec Panfil, Wojciech Moczulski, Wojciech Moczulski, } "Control system of the inspection robots group applying auctions and multi-criteria analysis for task allocation", Proc. SPIE 10441, Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies, 104410K (5 October 2017); doi: 10.1117/12.2278247; https://doi.org/10.1117/12.2278247
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