A cooperative approach to Range-Only SLAM with undelayed initialization

IF 5.2 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Lorenzo Bianchi, Francesco Martinelli
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引用次数: 0

Abstract

A 2D cooperative Range-Only SLAM problem is considered in this paper. In addition to odometry, available through noisy encoder readings on the actuated wheels, the robots measure the distances to a set of landmarks in unknown positions within the environment, as well as to other robots. Inter-landmark distances are not assumed to be available. The robots start at unknown locations, with their relative positions also assumed unknown. A Multi-Hypotheses Extended Kalman Filter, endowed with a Federated Information Sharing mechanism, is proposed to solve the problem in a computationally efficient way, without any delay in the initialization of landmark and robot position estimates. Simulation and experimental results are reported in the paper to demonstrate the effectiveness of the proposed approach, showing significant improvements in both steady-state and transient performance compared to the single-robot scenario.
一种无延迟初始化的全距离SLAM协同方法
研究了二维协同距离SLAM问题。除了里程表(通过驱动车轮上的噪声编码器读数)之外,机器人还可以测量到环境中未知位置的一组地标的距离,以及与其他机器人的距离。不假设地标间距离是可用的。机器人从未知的位置开始,它们的相对位置也假设为未知。提出了一种具有联邦信息共享机制的多假设扩展卡尔曼滤波器,在不延迟地标初始化和机器人位置估计的情况下,以高效的计算方式解决了该问题。仿真和实验结果证明了该方法的有效性,与单机器人场景相比,该方法在稳态和瞬态性能方面都有显著改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Robotics and Autonomous Systems
Robotics and Autonomous Systems 工程技术-机器人学
CiteScore
9.00
自引率
7.00%
发文量
164
审稿时长
4.5 months
期刊介绍: Robotics and Autonomous Systems will carry articles describing fundamental developments in the field of robotics, with special emphasis on autonomous systems. An important goal of this journal is to extend the state of the art in both symbolic and sensory based robot control and learning in the context of autonomous systems. Robotics and Autonomous Systems will carry articles on the theoretical, computational and experimental aspects of autonomous systems, or modules of such systems.
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