Path planning for smart AGV with UWB positioning systems

Autonomous robotic control has been becoming more and more popular in recent years and navigation is one of the popular areas. One of the significant components of navigation is localization. There are many localization technologies being studied and developed. Among them, Ultra-wideband (UWB) commu...

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Bibliographic Details
Main Author: Zhang, Yihang
Other Authors: Xie Lihua
Format: Final Year Project
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/75817
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Institution: Nanyang Technological University
Language: English
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Summary:Autonomous robotic control has been becoming more and more popular in recent years and navigation is one of the popular areas. One of the significant components of navigation is localization. There are many localization technologies being studied and developed. Among them, Ultra-wideband (UWB) communication technology is a reliable choice with the fact that UWB is one of the most promising ranging measurement sensors. With the accurate distance measurements, UWB is able to give a reliable localization. This project is motivated by this concern and the main objective of the project is to implement UWB localization system into a path planning of an automated guided vehicle (AGV). To achieve the objective, the UWB ranging and localization algorithm based on graph optimization are studied and tested. The output of localization becomes one of the inputs of a designed path planning algorithm with obstacle avoidance using point cloud data. Experiments were conducted to test the performance of the UWB localization system and its implementation on the path planning algorithm. The result showed that UWB localization system can give a reliable and accurate positioning of the AGV with an error within 10 centimeters. Also, the path planning algorithm was tested, and finally, the AGV can give a successful navigation. Future works in this topic could focus on improving robustness of UWB localization algorithm and enhancing flexibility of path planning algorithm in more complicated environment.