Implementation of Mobile Robot Localisation and Path Planning for Navigation in Known Map

Authors

  • S. Gunasagaran School of Mechatronic Engineering, Universiti Malaysia Perlis, Pauh Putra Campus, Arau, Perlis, Malaysia.
  • K. Kamarudin School of Mechatronic Engineering, Universiti Malaysia Perlis, Pauh Putra Campus, Arau, Perlis, Malaysia. Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis, Arau, Perlis, Malaysia.
  • A.S.A. Yeon Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis, Arau, Perlis, Malaysia.
  • R. Visvanathan Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis, Arau, Perlis, Malaysia.
  • S.M. Mamduh Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis, Arau, Perlis, Malaysia.
  • A. Zakaria School of Mechatronic Engineering, Universiti Malaysia Perlis, Pauh Putra Campus, Arau, Perlis, Malaysia. Centre of Excellence for Advanced Sensor Technology (CEASTech), Universiti Malaysia Perlis, Arau, Perlis, Malaysia.

Keywords:

AMCL, Laser Scanner, Robotics, ROS, SLAM,

Abstract

This paper describes the implementation of a laser scanner to localise a mobile robot in a known map and navigate to a pinpointed location while avoiding any obstacles within the path. The ability to successfully localise itself is a key requirement for any mobile robot. The Turtlebot Create is used as the platform part to test the localisation. The probabilistic localisation method, the Adaptive Monte Carlo Localization (AMCL) technique is used for the purpose. The approach is experimentation driven due to unique and unanticipated challenges present in the environment. As for obstacle avoidance and path planning, the Dynamic Window Approach (DWA) and Dijkstra’s algorithm is used respectively. The implementation is done using Robot Operating System (ROS) framework and thus is reusable in any future projects with both, simulated and real platforms. The experiments were run in CEASTech and UniMAP Solutions, and it was observed that the robot was able to firstly map the two environments, localise itself in the known map and manoeuvre to the pinpointed locations without any collision.

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Published

2018-05-30

How to Cite

Gunasagaran, S., Kamarudin, K., Yeon, A., Visvanathan, R., Mamduh, S., & Zakaria, A. (2018). Implementation of Mobile Robot Localisation and Path Planning for Navigation in Known Map. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1-15), 67–73. Retrieved from https://jtec.utem.edu.my/jtec/article/view/4049

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