scholarly journals MONITORING AND POSITIONING METHOD OF INDOOR MOBILE ROBOT USING WIRELESS NETWORK

2020 ◽  
Vol i (8) ◽  
Keyword(s):  
Mobile Robot ◽  
Wireless Network ◽  
Indoor Mobile Robot ◽  
Positioning Method

BUILDING MAP AND POSITIONING SYSTEM FOR INDOOR ROBOT BASED ON PLAYER

2011 ◽  
Vol 08 (04) ◽  
pp. 281-290
Author(s):  
BIN WANG ◽  
WEI LU ◽  
BIN KONG
Keyword(s):  
Mobile Robot ◽  
Positioning System ◽  
Map Building ◽  
Adaptive Monte Carlo ◽  
Indoor Mobile Robot ◽  
Robot Positioning ◽  
Positioning Method ◽  
Dynamic Map ◽  
Slam Algorithm ◽  
Number Of Particles

In this paper, we have proposed a map-building and positioning method for an indoor mobile robot based on the open source platform Player. First, the DP-SLAM algorithm is transplanted to the Player and used to build the dynamic offline map. This would reduce the errors and constraints caused by manual map building. Second, the KLD-Sampling Adaptive Monte Carlo Locating (KLD-AMCL) algorithm is introduced to reduce the number of particles required in locating. Meanwhile, higher accuracy of localization is achieved through calculating the MLE and the real posterior KL distance. Finally, an indoor mobile robot positioning system is built by combining the Player platform, dynamic map building and KLD-AMCL algorithm. Experimental results show that the proposed system has better environmental adaptability and higher positioning accuracy.

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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