Learning Modules for Visual-Based Position Tracking and Path Controlling of Autonomous Robots Using Pure Pursuit

  • Supod KaewkornEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1134)


In the field of automatic control system, autonomous movement and its applications, such as intelligent vehicles and auto-steering tractors, are widely studied. This article presents two learning modules to help students better understand visual-based position tracking and path controlling of autonomous robots. Firstly, in the experimental design module, students will receive hands-on training from the construction of hardware and learn how to apply various theories in visual-based control system and autonomous path controlling. The learning points in the experimental module includes camera and lighting installation, image processing using Raspberry Pi3 B+ board, RF data transmission, PID speed control and PWM position control, determination of robot’s position and heading direction, introductory Python coding, and Pure Pursuit algorithm. Secondly, the simulation module aims to aid the students to see how changing a certain running parameter of a robot affects its running behavior on the desired path. Furthermore, this module provides an introductory course on Python 2D simulation and the basic math model use to derive and obtain the simulation program.


Pure Pursuit Image processing Position tracking Autonomous path controlling 2D simulation 



This project has been supported and funded by King Mongkut University of Technology (KMUTNB). Special gratitude towards all dedicated students and fellow researchers at College of Industrial Technology (CIT) at KMUTNB for hardware installation, software implementation, and data acquisition.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.King Mongkut’s University of North BangkokBangkokThailand

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