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Distributed Range-Based Relative Localization of Robot Swarms

机译:基于范围的基于范围的机器人群相对定位

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This paper studies the problem of having mobile robots in a multi-robot system maintain an estimate of the relative position and relative orientation of nearby robots in the environment. This problem is studied in the context of large swarms of simple robots which are capable of measuring only the distance to near-by robots. We compare two distributed localization algorithms with different trade-offs between their computational complexity and their coordination requirements. The first algorithm does not require the robots to coordinate their motion. It relies on a non-linear least squares based strategy to allow robots to compute the relative pose of nearby robots. The second algorithm borrows tools from distributed computing theory to coordinate which robots must remain stationary and which robots are allowed to move. This coordination allows the robots to use standard trilateration techniques to compute the relative pose of near-by robots. Both algorithms are analyzed theoretically and validated through simulations.
机译:本文研究了在多机器人系统中具有移动机器人的问题,维持环境中附近机器人的相对位置和相对取向的问题。在大型群的简单机器人的背景下研究了这个问题,这是能够仅测量与接近机器人的距离。我们比较两个分布式定位算法,其计算复杂性与其协调要求之间的不同权衡。第一算法不需要机器人协调其运动。它依赖于基于非线性最小二乘性的策略,以允许机器人计算附近机器人的相对姿势。第二种算法借用来自分布式计算理论的工具,以协调一个机器人必须保持静止,并且允许移动机器人移动。这种协调允许机器人使用标准三边技术来计算近乎机器人的相对姿势。理论上分析了这两种算法并通过模拟验证。

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