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Distributed collaborative localization for a heterogeneous multi-robot system

机译:异构多机器人系统的分布式协作本地化

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This paper studies the problem of collaborative localization for a heterogeneous multi-robotic system (MRS), particularly an MRS with one or more robots with accurate self-localization capabilities (leader) and several robots with little or no such capabilities (child). Finite-range sensing is one of the major limitation in the collaboration of an MRS when the child robots rely on inter-robot relative measurements (IRRM) between themselves and the leader robot for localization. This study proposes a collaborative localization (CL) scheme, which has the ability to localize child robots even when they operate beyond the field of view (FOV) of the leader robots. A distributed sensor fusion architecture is introduced in order to reduce the communication bandwidth, processing power, and memory usage requirements for the leader robot. Thus, the resulting implementation is scalable in terms of the number of robots in the team. The performance of the proposed localization scheme was evaluated in Monte Carlo simulations and a series of experiments using a team of six mobile robots. Both the experiment and the simulation results demonstrated that the proposed CL scheme is capable of establishing a localization for child robots with 1∼10 cm positional accuracy and 0.01∼0.1 rad orientational accuracy, even when they operate beyond the FOV of the leader robot.
机译:本文研究了异构多机器人系统(MRS)的协作定位问题,特别是具有一个或多个具有准确自我定位功能的机器人(领导者)和几个具有很少或没有这种能力的机器人(子代)的MRS。当子机器人依靠自身与领导者机器人之间的机器人间相对测量值(IRRM)进行定位时,有限距离感测是MRS协作中的主要限制之一。这项研究提出了一种协作式定位(CL)方案,该方案具有对子机器人进行定位的能力,即使它们超出了领导者机器人的视野(FOV)。为了减少领导者机器人的通信带宽,处理能力和内存使用要求,引入了分布式传感器融合架构。因此,根据团队中机器人的数量,最终的实现是可伸缩的。使用六个移动机器人团队,在蒙特卡洛模拟和一系列实验中评估了所建议的定位方案的性能。实验和仿真结果均表明,所提出的CL方案即使在超前机器人的视野范围之外也能以1〜10 cm的位置精度和0.01〜0.1 rad的方向精度为儿童机器人建立定位。

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