In this paper we present an asynchronous distributed mechanism for allocating tasks in a team of robots. Tasks to be allocated are dynamically perceived from the environment and can be tied by execution constraints. Conflicts among team mates arise when an uncontrolled number of robots execute the same task, resulting in waste of effort and spatial conflicts. The critical aspect of task allocation in Multi Robot Systems is related to conflicts generated by limited and noisy perception capabilities of real robots. This requires significant extensions to the task allocation techniques developed for software agents. The proposed approach is able to successfully allocate roles to robots avoiding conflicts among team mates and maintaining low communication overhead. We implemented our method on AIBO robots and performed quantitative analysis in a simulated environment. ©2005 IEEE.
Task assignment with dynamic perception and constrained tasks in a multi-robot system / A., Farinelli; Iocchi, Luca; Nardi, Daniele; Ziparo, VITTORIO AMOS. - 2005:(2005), pp. 1523-1528. (Intervento presentato al convegno IEEE International Conference on Robotics and Automation (ICRA) tenutosi a Barcelona; Spain nel APR 18-22, 2005) [10.1109/robot.2005.1570330].
Task assignment with dynamic perception and constrained tasks in a multi-robot system
IOCCHI, Luca;NARDI, Daniele;ZIPARO, VITTORIO AMOS
2005
Abstract
In this paper we present an asynchronous distributed mechanism for allocating tasks in a team of robots. Tasks to be allocated are dynamically perceived from the environment and can be tied by execution constraints. Conflicts among team mates arise when an uncontrolled number of robots execute the same task, resulting in waste of effort and spatial conflicts. The critical aspect of task allocation in Multi Robot Systems is related to conflicts generated by limited and noisy perception capabilities of real robots. This requires significant extensions to the task allocation techniques developed for software agents. The proposed approach is able to successfully allocate roles to robots avoiding conflicts among team mates and maintaining low communication overhead. We implemented our method on AIBO robots and performed quantitative analysis in a simulated environment. ©2005 IEEE.File | Dimensione | Formato | |
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