Multi-Sensor Fusion for A Brain-Inspired SLAM System

被引：0
|
作者：
Zhang, Houzhan [1 ]
Tang, Huajin [1 ]
Yan, Rui [1 ]
机构：
[1] Sichuan Univ, Coll Comp Sci, Neuromorph Comp Res Ctr, Chengdu, Peoples R China
来源：
CONFERENCE PROCEEDINGS OF 2019 5TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND ROBOTICS (ICCAR) | 2019年
关键词：
simultaneous localization and mapping; multi-sensor fusion; RatSLAM; cognitive map; PATH-INTEGRATION; MAP;
D O I：
10.1109/iccar.2019.8813400
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A brain-inspired simultaneous localization and mapping (SLAM) system, called RatSLAM, that requires information of odometry and visual scenes traveled before, is used to construct a cognitive map for a mobile robot. While existing RatSLAM systems, that use raw odometry, easily suffer from the problem of low accuracy of maps in complex environments. In this paper, we employ a multi-sensor fusion method to provide better odometry for RatSLAM system. Experiment results demonstrate that the proposed system, based on multi-sensor fusion, show significant improvements on the cognitive mapping results. Thus, the proposed system is able to construct more precise cognitive maps.
引用
收藏
页码：619 / 623
页数：5
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