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首页 > 过刊浏览>2020年第31卷第9期 >2678-2690. DOI:10.13328/j.cnki.jos.005937
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扫地机器人增强位姿融合的Cartographer算法及系统实现
作者:
作者简介:

张亮(1975-),男,博士,副教授,CCF专业会员,主要研究领域为嵌入式多核系统,机器人语义SLAM,深度学习和计算机视觉,三维场景语义分割,手势识别,图像处理;蒋得志(1994-),男,硕士,主要研究领域为语义SLAM;刘智宇(1993-),男,硕士生,主要研究领域为机器人同步定位与建图;梅林(1975-),男,博士,研究员,主要研究领域为计算机视觉,人工智能,物联网应用,大数据处理;曹晶瑛(1984-),男,学士,主要研究领域为分布计算,可信计算与信息安全;朱光明(1975-),男,博士,讲师,CCF专业会员,主要研究领域为深度学习,手势识别;沈沛意(1975-),男,博士,教授,CCF专业会员,主要研究领域为计算机视觉,语义结构图,大数据;苗启广(1972-),男,博士,教授,博士生导师,CCF杰出会员,主要研究领域为计算机视觉,机器学习,大数据分析.

通讯作者:

沈沛意,E-mail:pyshen@xidian.edu.cn

基金项目:

国家自然科学基金（61401324，61305109）；陕西省重点研发计划（2018ZDXM-GY-36）


Cartographer Algorithm and System Implementation Based on Enhanced Pose Fusion of Sweeping Robot
Author:
Fund Project:

National Natural Science Foundation of China (61401324, 61305109); Shaanxi Province Key Research and Development Program (2018ZDXM-GY-36)

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    摘要:

    Cartographer是谷歌在2016年开源的一个可以在多传感器配置下实现低计算资源消耗的SLAM算法框架.针对原有Cartographer中位姿融合不准确、存在延迟的问题，首先设计了一种基于位姿增量的多传感器位姿融合方法；随后，针对扫地机器人Player平台，设计并实现了基于增强Cartographer算法的多模块SLAM系统；最后，通过Cartographer数据集的实验分析和真实场景的实际测试，验证了增强Cartographer算法的有效性以及SLAM系统在Player机器人平台上的可用性.

    Abstract:

    Cartographer is Google's 2016 open source SLAM algorithm framework for low computational resource consumption in multi-sensor configurations. In this study, due to the inaccurate middle posture fusion and delay of the original Cartographer, a multi- sensor posture fusion method based on posture increment was designed. Subsequently, the multi-module SLAM system based on enhanced Cartographer algorithm was designed and implemented for the cleaning robot Player platform. Finally, the effectiveness of the enhanced Cartographer algorithm and the usability of the SLAM system on the Player robot platform were verified by the experimental analysis of the Cartographer data set and the actual test of the real scenario.

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张亮,刘智宇,曹晶瑛,沈沛意,蒋得志,梅林,朱光明,苗启广.扫地机器人增强位姿融合的Cartographer算法及系统实现.软件学报,2020,31(9):2678-2690

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  • 收稿日期:2019-06-27
  • 最后修改日期:2019-08-18
  • 在线发布日期: 2020-01-17
  • 出版日期: 2020-09-06
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