⚠ Official Notice: www.ijisrt.com is the official website of the International Journal of Innovative Science and Research Technology (IJISRT) Journal for research paper submission and publication. Please beware of fake or duplicate websites using the IJISRT name.



Investigation of Steering Angle Influence on the Velocities of Four Independently Driven Wheels for a Mobile Robot


Authors : Le Quoc Chuan; Pham Quoc Phong; Thach Minh Trong

Volume/Issue : Volume 11 - 2026, Issue 5 - May


Google Scholar : https://tinyurl.com/mr2vkryz

Scribd : https://tinyurl.com/8w3nwbys

DOI : https://doi.org/10.38124/ijisrt/26May1953

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.


Abstract : Independent velocity coordination at each wheel is a key factor in governing the kinematics and trajectory control of omnidirectional mobile robot configurations. This study investigates the design and experimental validation of an electronic differential system that distributes reference velocities based on the steering input for a four-wheel independent steering and four-wheel independent drive mobile robot. Utilizing the geometric principles of an expanded Ackermann steering model, an inverse kinematic framework is established to map the mathematical constraints between the global linear velocity and localized steering angles, aiming to minimize geometric synchronization mismatches during cornering maneuvers. For the physical validation, a mechatronic prototype intended for baseline algorithm verification was constructed, integrating an Arduino Mega microcontroller, self-locking worm-gear steering mechanisms, and brushless direct current hub motors regulated by four independent drives. To isolate the core actuation performance from stochastic ground-interaction variables, a no-load bench-testing configuration was utilized.

Keywords : Mobile Robot; Brushless DC Motor; Electronic Differential System; Four-Wheel Independent Drive; MATLAB/Simulink.

References :

  1. Leong JSL, Teo KTK, Yoong HP. Four wheeled mobile robots: A review. 2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET). Kota Kinabalu, Malaysia: IEEE; 2022. p.1-6. https://doi.org/10.1109/IICAIET55139.2022.9936855.
  2. Pham QP, Huynh DL, Duong VK. Design and experiment of independent Four-Wheel Drive system for electric vehicles. The University of Danang - Journal of Science and Technology. 2026; 24(1):1-6. https://doi.org/10.31130/ud-jst.2026.24(1).616E.
  3. Zhu S, Lyu C. Distributed Drive Control Technology of Hub Motor. Singapore: Springer Nature Singapore; 2025. https://doi.org/10.1007/978-981-97-2922-7 1.
  4. Maknickas A, Ardatov O, Bogdevičius M, Kačianauskas R. Modelling the interac-tion between a laterally deflected car tyre and a road surface. Applied Sciences. 2022; 12(22):11332. https://doi.org/10.3390/app122211332.
  5. Darsh P, Nishi P, Aakash R, Manisha C, Neeraj Kumar GPJ, Cho W. A review on autonomous vehicles: Progress, methods and challenges. Electronics. 2022; 11(14):2162. https://doi.org/10.3390/electronics11142162.
  6. Yin D, Shan D, Hu JS. A study on the control performance of electronic differential system for four-wheel drive electric vehicles. Applied Sciences. 2017; 7(1):74. https://doi.org/10.3390/app7010074.
  7. Yin H, Yi W, Wu J, Wang K, Guan J. Adaptive fuzzy neural network PID algorithm for BLDCM speed control system. Mathematics. 2022; 10(1):118. https://doi.org/10.3390/math10010118.
  8. Yin H, Yi W, Wang K, Guan J, Wu J. Research on brushless DC motor control system based on fuzzy parameter adaptive PI algorithm. AIP Advances. 2020; 10(10):105208. https://doi.org/10.1063/5.0025000.
  9. Trinh TKL, Nguyen HT, Luu TP. Design of neural network-PID controller for trajectory tracking of differential drive mobile robot. Vietnam Journal of Science and Technology. 2024; 62(2):374-386. https://doi.org/10.15625/2525-2518/18066.
  10. Thai NH, Ly TTK, Thien H, Dzung LQ. Trajectory tracking control for differential drive mobile robot by a variable parameter PID controller. International Journal of Mechanical Engineering and Robotics Research. 2022; 11(8):614-621. https://doi.org/10.18178/ijmerr.11.8.614-621.
  11. Kang YH, Pang DC, Zeng YC. Optimal dimensional synthesis of Ackermann steering mechanisms for three-axle, six-wheeled vehicles. Applied Sciences. 2025; 15(2):800. https://doi.org/10.3390/app15020800.
  12. Zheng H, Yang S, Li B. Optimization control for 4WIS electric vehicle based on the coincidence degree of wheel steering centers. SAE International Journal of Vehicle Dynamics, Stability, and NVH. 2018; 2(3):169-184. https://doi.org/10.4271/10-02-03-0011.
  13. Gamit P. Simulation of BLDC motor control using conventional PI controller in MATLAB Simulink. Journal of Electrical Systems. 2024; 20(3):8051-8061. https://doi.org/10.52783/JES.7807.
  14. Dwivedi A. Speed control analysis of BLDC motor drive using PI controller. International Journal of Electrical, Electronics & Communication Engineering. 2013; 3(10):457-462. https://doi.org/10.13140/RG.2.2.35602.96960.
  15. Mahmud SMA, Motakabber SMA, Alam AHMZ, Nordin AN, Habib AKMA. Modeling and performance analysis of an adaptive PID speed controller for the BLDC motor. International Journal of Advanced Computer Science and Applications. 2020; 11(7):1-8. https://doi.org/10.14569/IJACSA.2020.0110736.

Independent velocity coordination at each wheel is a key factor in governing the kinematics and trajectory control of omnidirectional mobile robot configurations. This study investigates the design and experimental validation of an electronic differential system that distributes reference velocities based on the steering input for a four-wheel independent steering and four-wheel independent drive mobile robot. Utilizing the geometric principles of an expanded Ackermann steering model, an inverse kinematic framework is established to map the mathematical constraints between the global linear velocity and localized steering angles, aiming to minimize geometric synchronization mismatches during cornering maneuvers. For the physical validation, a mechatronic prototype intended for baseline algorithm verification was constructed, integrating an Arduino Mega microcontroller, self-locking worm-gear steering mechanisms, and brushless direct current hub motors regulated by four independent drives. To isolate the core actuation performance from stochastic ground-interaction variables, a no-load bench-testing configuration was utilized.

Keywords : Mobile Robot; Brushless DC Motor; Electronic Differential System; Four-Wheel Independent Drive; MATLAB/Simulink.

Paper Submission Last Date
30 - June - 2026

SUBMIT YOUR PAPER CALL FOR PAPERS
Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe