考虑通信状况的多机器人CSLAM问题综述

张国良; 汤文俊; 曾静; 徐君; 姚二亮

doi:10.3724/SP.J.1004.2014.02073

考虑通信状况的多机器人CSLAM问题综述

doi: 10.3724/SP.J.1004.2014.02073

1.
第二炮兵工程大学西安 710025

基金项目:

陕西省基金项目 (2012K06-45)资助

详细信息

作者简介:
张国良第二炮兵工程大学教授. 主要研究方向为机器人技术, 先进控制理论与应用. E-mail: zhgl@sohu.com

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- 被引次数: 0
出版历程
- 收稿日期: 2013-12-24
- 修回日期: 2014-05-01
- 刊出日期: 2014-10-20

An Overview on the Cooperative SLAM Problem of Multi-robot Systems Considering Communication Conditions

1.
Hi-Tech Institution of Xi'an, Xi'an 710025

Funds:

Supported by Fund Program of Shaanxi Province (2012K06-45)

摘要

摘要: 多机器人系统的通信状况能够直接影响协作同时定位与地图创建(Cooperative simultaneous localization and mapping, CSLAM)算法的设计和实现.根据对多机器人通信状况所作出假设的侧重点不同, 对多机器人CSLAM算法研究现状和进展进行综述.首先,简要介绍了基于完全连通通信条件的集中式CSLAM算法的特点和缺陷; 其次,结合多机器人系统初始相对位姿关系未知的情况,从地图配准、数据关联和地图融合等三个方面, 对基于通信范围或者带宽受限条件的分布式CSLAM算法的地图合并问题进行了分析和阐述; 进而重点对考虑稀疏动态通信状况的分布式CSLAM算法的最新研究成果进行了归纳总结. 最后指出多机器人CSLAM研究领域今后的研究方向.
- 多机器人系统通信网络 /
- 协作SLAM /
- 地图合并 /
- 地图配准 /
- 数据关联 /
- 地图融合
Abstract: The communication conditions can affect the design and realization of cooperative simultaneous localization and mapping (CSLAM) algorithms directly. According to the different focuses among the assumptions on the communication conditions of multi-robot systems, the state-of-the-art research advances of multi-robot CSLAM algorithms are presented in this paper. Firstly, the characters and drawbacks of the centralized CSLAM algorithm based on fully connected communication condition are introduced. Secondly, in the situation of unknown initial correspondence of the multi-robot system, the map merging issue of distributed CSLAM algorithm based on limited communication range and bandwidth is analyzed and defined in terms of map alignment, data association and map fusion. Furthermore, some of the latest research achievements on distributed CSLAM algorithm considering sparse-dynamic communication situation are also presented. Finally, the prospect of future research in the area of multi-robot CSLAM is summarized.
- Communication network of multi-robot system /
- cooperative simultaneous localization and mapping (Coop-erative SLAM) /
- map merging /
- map alignment /
- data association /
- map fusion

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