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Auction-based task allocation scheme for dynamic coalition formations in limited robotic swarms with heterogeneous capabilities

机译:基于拍卖的任务分配方案,用于有限机器人群的有限机器人群,具有异构功能

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Task allocation is one of the main issues to be addressed in the domain of multi-robot systems, in which it is determined which robot(s) should execute which task(s) so that overall system goal is achieved. Such collective decision making process is of great significance during complex task execution by swarm of simple robots with heterogeneous capabilities. This work targets the issue of coalition formations in a limited swarm of robots to perform a task requiring multiple single-task robots (ST-MR-IA) depending upon their heterogeneous capability conditions. Capabilities of individual robots may vary to different certain levels in a dynamic environment during task execution which can further affect the coalition formed to execute a specific complex task requiring certain level of collective/group capability. This study aims to suggest an algorithm for task allocations through auction mechanism to form a new or modify a coalition underway, where individual robots may gain or lose their task capabilities at certain time instants. Effectiveness of proposed algorithm in terms of task-execution time and utility of coalitions is analyzed through simulations.
机译:任务分配是多机器人系统领域中要解决的主要问题之一,其中确定了哪个机器人应该执行哪个任务,从而实现整体系统目标。这种集体决策过程在具有异构功能的简单机器人的复杂任务执行期间具有重要意义。这项工作的目标联合编队的问题在机器人的有限群执行需要根据它们的异构能力条件的多个单任务的机器人(ST-MR-IA)的任务。各个机器人的能力可能在任务执行期间的动态环境中的不同一定程度不同,这可以进一步影响形成的联盟以执行需要某些集体/组能力的特定复杂任务。本研究旨在通过拍卖机制来建议任务分配算法,以在进行中形成新的或修改联盟,其中各个机器人可以在某些时间瞬间获得或失去任务能力。通过模拟分析了在联盟的任务执行时间和效用方面所提出的算法的有效性。

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