Research on Positioning Algorithm of Indoor Mobile Robot Based on Vision/INS

2020 ◽  
pp. 1250-1255
Author(s):  
Tongqian Liu ◽  
Yong Zhang ◽  
Yuan Xu ◽  
Wanfeng Ma ◽  
Jidong Feng
Keyword(s):  
Mobile Robot ◽  
Indoor Mobile Robot ◽  
Positioning Algorithm

An Indoor Mobile Robot Positioning Algorithm Based on Adaptive Federated Kalman Filter

2021 ◽  
pp. 1-1
Author(s):  
Xiaobin Xu ◽  
Fenglin Pang ◽  
Yingying Ran ◽  
Yonghua Bai ◽  
Lei Zhang ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Mobile Robot ◽  
Indoor Mobile Robot ◽  
Robot Positioning ◽  
Federated Kalman Filter ◽  
Positioning Algorithm

scholarly journals A robust mobile robot indoor positioning system based on Wi-Fi

2020 ◽  
Vol 17 (1) ◽  
pp. 172988141989666 ◽  
Author(s):  
Wei Cui ◽  
Qingde Liu ◽  
Linhan Zhang ◽  
Haixia Wang ◽  
Xiao Lu ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Principal Component ◽  
Indoor Positioning ◽  
Positioning System ◽  
Infrared Sensors ◽  
Positioning Systems ◽  
Indoor Mobile Robot ◽  
Robot Positioning ◽  
Learning Machine ◽  
Noisy Measurements

Recently, most of the existing mobile robot indoor positioning systems (IPSs) use infrared sensors, cameras, and other extra infrastructures. They usually suffer from high cost and special hardware implementation. In order to address the above problems, this article proposes a Wi-Fi-based indoor mobile robot positioning system and designs and develops a robot positioning platform based on the commercial Wi-Fi devices, such as Wi-Fi routers. Furthermore, a robust principal component analysis-based extreme learning machine algorithm is proposed to address the issue of noisy measurements in IPSs. Real-world robot indoor positioning experiments are extensively carried out and the results verify the effectiveness and superiority of the proposed system.

scholarly journals Mobile Robot Indoor Positioning System Based on K-ELM

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Haixia Wang ◽  
Junliang Li ◽  
Wei Cui ◽  
Xiao Lu ◽  
Zhiguo Zhang ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Indoor Localization ◽  
Indoor Positioning ◽  
Positioning System ◽  
Positioning Accuracy ◽  
Positioning Method ◽  
Kernel Extreme Learning Machine ◽  
Learning Machine ◽  
Positioning Algorithm ◽  
Indoor Positioning System

Mobile Robot Indoor Positioning System has wide application in the industry and home automation field. Unfortunately, existing mobile robot indoor positioning methods often suffer from poor positioning accuracy, system instability, and need for extra installation efforts. In this paper, we propose a novel positioning system which applies the centralized positioning method into the mobile robot, in which real-time positioning is achieved via interactions between ARM and computer. We apply the Kernel extreme learning machine (K-ELM) algorithm as our positioning algorithm after comparing four different algorithms in simulation experiments. Real-world indoor localization experiments are conducted, and the results demonstrate that the proposed system can not only improve positioning accuracy but also greatly reduce the installation efforts since our system solely relies on Wi-Fi devices.

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