An Autonomous Simultaneous Localization and Mapping Walker for Indoor Navigation

被引：0
|
作者：
Kashyap, Priyank [1 ]
Saleh, Mahmoud [2 ]
Shakhbulatov, Denisolt [2 ]
Dong, Ziqian [1 ]
机构：
[1] New York Inst Technol, Sch Engn & Comp Sci, Dept Elect & Comp Engn, New York, NY 10023 USA
[2] New York Inst Technol, Sch Engn & Comp Sci, Dept Comp Sci, New York, NY 10023 USA
来源：
2018 IEEE 39TH SARNOFF SYMPOSIUM | 2018年
关键词：
AMCL; Autonomous walker; SLAM; Gmapping; Hector; ROS; Voice Recognition;
D O I：
暂无
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
Walkers have been used to help the elderly and individuals with movement disorders as an assistive and rehabilitation tool. This study presents a smart walker, a system which guides the users to navigate in an indoor environment. The Walker can be controlled by voice commands to create location markers and navigate the user while avoiding obstacles. We evaluated three localization implementations, namely, Adaptive Monte Carlo Localization (AMCL), Gmapping and Hector Slam for this system and compared their navigation accuracy with an ideal path. We collected the data on the paths of AMCL, Gmapping and Hector Slam and applied statistical tests on the data. The results show that AMCL achieves the lowest mean absolute error while navigating to its goal with an error of 2.15% over the path distance, as compared to Gmapping and Hector in this implementation.
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页数：6
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