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Inverse ACO Applied for Exploration and Surveillance in Unknown Environments

机译:逆ACO应用于未知环境中的探索和监视

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This paper focuses on a distributed strategy proposed to coordinate a multiple robot system applied to exploration and surveillance tasks. The strategy is based on the artificial ant system theory. According to it robots are guided to unexplored or not recently explored regions. The main features of the strategy are, among others: low computation cost; and independence of the number of robots. Results from preceding investigations confirm the strategy is able to emerge a cooperative robot behavior, that is, the exploration and surveillance tasks are synergistically executed. This paper concerns specifically the robustness of the coordination strategy regarding to the environment structure. Two metrics are adopted for evaluation: needed time to conclude the exploration task, and time between two consecutive senses on a same region. Simulation results show that the coordination strategy is able to establish effective trajectories, that is, robots are guided to explore the environment and to sense repeatedly and completely the environment.
机译:本文重点介绍了分布式策略建议,协调多机器人系统应用于勘探和监视任务。该战略是基于人工蚂蚁系统理论。根据它的机器人被引导到未开发的或最近没有探索的区域。该战略的主要特点,其中包括:低计算成本;和机器人的数量的独立性。从前面的调查结果证实了策略,能够涌现出合作的机器人的行为,也就是探索和监视任务协同执行。本文特别关注有关环境结构的协调策略的稳健性。两个指标都通过了评估:需要时间来完成关于同一区域两个连续的感官之间的探索任务和时间。仿真结果表明,该协调策略能够建立有效的轨迹,也就是说,机器人被引导到探索环境和反复,完全感知环境。

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