Author:
Norzam W.A.S,Hawari H.F.,Kamarudin K.
Abstract
Abstract
Mapping is one of the elemental application of the mobile robot. The map is created using the mobile robot by employing sensors such as camera, sonar and laser sensor. One of the most popular mapping methods is the Simultaneous Localization and Mapping (SLAM). SLAM allows the map to be created while localizing the robot location in the map at the same time. GMapping is one of the widely used algorithms in SLAM which will be used in this project. The mobile robot is equipped with a Hokuyo Laser Range Finder sensor and netbook. The router is used for wireless communication between the mobile robot and the user. The GMapping is done in two different locations of different lab size and amount of features in the area. Three trial is conducted to investigate the effects of different parameters such as robot speed, mapping delay and particle filter on the mapping quality. The results show a significant difference in terms of mapping accuracy and the time taken to complete the process as the parameter changed from the three trial. As a result, the parameter used in the second trial, robot speed 0.1333m/s, mapping delay 1s and particle filter 30 is considered as the best based on the time taken and the map accuracy.
Reference12 articles.
1. Research on a Panoramic Mobile Robot for Autonomous Navigation;Gao;Proc. of the 3rd Int. Conf. on Mechatronics Engineering and Information Technology,2019
2. Deep Reinforcement Learning Robot for Search and Rescue Applications: Exploration in Unknown Cluttered Environments;Niroui;IEEE Robotics and Automation Letters,2019
3. Review on simultaneous localization and mapping (SLAM);Khairuddin,2015
4. Hector Open Source Modules for Autonomous Mapping and Navigation with Rescue Robots;Kohlbrecher;RoboCup 2013: Robot World Cup XVII,2014
Cited by
26 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献