1
College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq
(mohammed.rabeea@uoanbar.edu.iq)
2
Computer Science Department, Al-Maarif University Collage, Ramadi, Anbar, Iraq
(alsaadi.m@uoa.edu.iq)
3
College of Computer Science and Information Technology; University of Anbar, Ramadi, Anbar, Iraq
(ruqayah85@uoanbar.edu.iq)
4
Computer Science Department, Al-Maarif University Collage, Ramadi, Anbar, Iraq
(salah_eng1996@uoanbar.edu.iq)
Abstract :
The Pure Pursuit Algorithm (PPA) is used in this paper to explain how a car with four wheels moves. The MATLAB environment has extensive simulation capabilities that can accurately represent complex robotic behaviors. It was these that were deployed for an extended analysis of the robot’s operational dynamics. In the MATLAB/Simulink framework, waypoints obtained from different algorithms define robot trajectory. An odometer sensor helped to localize the robot thus giving accurate real-time information on its position. After critically evaluating several performance indices, it became clear just how well this control algorithm worked because it smoothly moved the robot from its initial state to its target with almost no oscillations at all. The findings of the simulation confirmed that if an appropriate lookahead distance is selected then the robot can effectively track waypoints and maintain optimal path along a trajectory up until reaching the target point at last
Keywords :
quad-wheel mobile robot; Pure Pursuit Algorithm (PPA); lookahead distance
References :
[1] F. V. and C. L.-A. F. Rubio, ‘A review of mobile robots: Concepts, methods, theoretical framework, and applications’, Int. J. Adv. Robot. Syst., vol. 16, no. 2, 2019.
[2] T. and Y. Y. Namba, ‘Risks of deep reinforcement learning applied to fall prevention assist by autonomous mobile robots in the hospital’, Big Data and Cognitive Computing, vol. 2, no. 2, p. 13, 2018.
[3] G. and D. K. R. and S. F. and S. J. O. Fragapane, ‘Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda’, Eur J Oper Res, vol. 294, pp. 405–426, 2021.
[4] X. and L. J. and F. L. and Z. Q. and Y. K. and W. J. and S. C. and H. L. and W. Z. Gao, ‘Review of wheeled mobile robots’ navigation problems and application prospects in agriculture’, IEEE access, vol. 6, pp. 49248–49268, 2018.
[5] S. and G. G. and O. M. and P. A. and others Mellah, ‘Actuator Health State Monitoring amp; Degradation Impact Study on a 4-Mecanum Wheeled Mobile Robot Behaviour’, in 2021 29th Mediterranean Conference on Control and Automation (MED), 2021, pp. 1076–1081.
[6] R. R. and A.-D. M. R. H. and J. M. H. Al-Dahhan, ‘Target seeking and obstacle avoidance of omni robot in an unknown environment’, in 2020 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), 2020, pp. 1–7.
[7] A. and V. P. T. and K. V. and P. K. L. Stefek, ‘Energy comparison of controllers used for a differential drive wheeled mobile robot’, IEEE Access, vol. 8, pp. 170915–170927, 2020.
[8] R. P. M. and S. K. A. and H. C. R. Chan, ‘Review of modelling and control of two-wheeled robots’, Annu Rev Control, vol. 37, no. 1, pp. 89–103, 2013.
[9] M. R. H. , A.-D. R. R. , & R. A. T. Al-Dahhan, ‘Multi-layer perceptron neural network mobile robot navigator in unknown environment’, Indonesian Journal of Electrical Engineering and Computer Science , vol. 31, pp. 725–733, 2023.
[10] M. and B. D. W. and M. N. A. Begnini, ‘A robust adaptive fuzzy variable structure tracking control for the wheeled mobile robot: Simulation and experimental results’, Control Eng Pract, vol. 64, pp. 27–43, 2017.
[11] P. and G. V. Petrov, ‘Adaptive Velocity Control for a Differential Drive Mobile Robot’, in 2018 20th International Symposium on Electrical Apparatus and Technologies (SIELA), 2018, pp. 1–4.
[12] M. R. H. and A. M. M. Al-Dahhan, ‘Path tracking control of a mobile robot using fuzzy logic’, in 2016 13th International Multi-Conference on Systems, Signals \& Devices (SSD), 2016, pp. 82–88.
[13] R. and L. Y. and F. J. and W. T. and C. X. Wang, ‘A Novel Pure Pursuit Algorithm for Autonomous Vehicles Based on Salp Swarm Algorithm and Velocity Controller’, IEEE Access, vol. 8, pp. 166525–166540, 2020.
[14] J. and M. J. Morales, ‘Pure-Pursuit Reactive Path Tracking for Nonholonomic Mobile Robots with a 2D Laser Scanner’, EURASIP J Adv Signal Process, pp. 1–10, 2009.
[15] Z. and B. Y. and W. J. and W. X. Wang, ‘Vehicle path-tracking linear-time-varying model predictive control controller parameter selection considering central process unit computational load’, J Dyn Syst Meas Control, vol. 141, no. 5, 2019.
[16] Q. and T. Y. Yao, ‘A Model Predictive Controller with Longitudinal Speed Compensation for Autonomous Vehicle Path Tracking’, Applied sciences, vol. 9, no. 22, p. 4739, 2019.
[17] R. and S. S. and N. M. Marino, ‘Nested PID steering control for lane keeping in autonomous vehicles’, Control Eng Pract, vol. 19, no. 12, pp. 1459–1467, 2011.
[18] A. and M. M. and D. V. and P. E. N. Bemporad, ‘The explicit linear quadratic regulator for constrained systems’, Automatica, vol. 38, no. 1, pp. 3–20, 2002.
[19] G. V. and G. G. K. and N.-R. J. E. and K. C. R. and B. L. B. Raffo, ‘A Predictive Controller for Autonomous Vehicle Path Tracking’, IEEE transactions on intelligent transportation systems, vol. 10, no. 1, pp. 92–102, 2009.
[20] S. and Y. X. and L. P. and Z. M. and W. X. Wang, ‘Trajectory tracking control for mobile robots using reinforcement learning and PID’, Iranian Journal of Science and Technology, Transactions of Electrical Engineering, vol. 44, pp. 1059–1068, 2020.
[21] A.-T. and T. T. and E. L. and C. V. and P. R. and S. M. Nguyen, ‘Fuzzy control systems: Past, present and future’, IEEE Comput Intell Mag, vol. 14, no. 1, pp. 56–68, 2019.
[22] A. and W. Q. Alouache, ‘Genetic algorithms for trajectory tracking of mobile robot based on PID controller’, in IEEE 14th International Conference on Intelligent Computer Communication and Processing (ICCP), 2018, pp. 237–241.
[23] J. and Y. M. and X. Z. Xianhua, ‘Predictive fuzzy logic controller for trajectory tracking of a mobile robot’, IEEE Mid-Summer Wor shop on Soft Computing in Industrial Applications, 2005.
[24] T. V. and H. N.-T. and V. N.-C. and K. V. N. and H. S.-C. Nguyen, ‘Optimizing compliant gripper mechanism design by employing an effective bi-algorithm: Fuzzy logic and ANFIS’, Microsystem Technologies, vol. 27, no. 9, pp. 3389–3412, 2021.
[25] N.-T. and N. T. V. and T. N. T. and N. Q.-M. Huynh, ‘Optimizing magnification ratio for the flexible hinge displacement amplifier mechanism design’, in Proceedings of the 2nd Annual International Conference on Material, Machines and Methods for Sustainable Development, 2021, pp. 769–778.
[26] S. and L. L. and G. H.-Q. and C. Z.-G. and S. P. Cheng, ‘collision avoidance and lateral stability adaptive control system based on MPC of autonomous vehicles’, IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 6, pp. 2376–2385, 2019.
[27] C. and L. M. and P. F. Xu, ‘The system design and LQR control of a two-wheels self-balancing mobile robot’, International Conference on Electrical and Control Engineering, pp. 2786–2789, 2011.
[28] H. and Z. J. Xu, ‘Interval trajectory tracking for AGV based on MPC’, in Chinese Control Conference, 2019, pp. 2835–2839.
[29] J. and W. Y. and L. H. and D. H. Ni, ‘Path tracking motion control method of tracked robot based on improved LQR control’, in 41st Chinese Control Conference (CCC), 2022, pp. 2888–2893.
[30] W.-J. and H. T.-M. and W. T.-S. Wang, ‘The improved pure pursuit algorithm for autonomous driving advanced system’, in IEEE 10th international workshop on computational intelligence and applications (IWCIA), 2017, pp. 33–38.
[31] S. and Z. W. and M. L. and B. L. and J. C. and J. T. Qinpeng, ‘Path tracking control of wheeled mobile robot based on improved pure pursuit algorithm’, in Chinese Automation Congress (CAC), 2019, pp. 4239–4244.
[32] R. C. and others Coulter, ‘Implementation of the pure pursuit path tracking algorithm’, Carnegie Mellon University, The Robotics Institute, 1992.
| Style | # |
|---|---|
| MLA | Mohammed R. Hashim Al-Dahhan , Mahmood Abdulrazzaq Alsaadi , Ruqayah R. Al-Dahhan , Salah A. Aliesawi. "The Art of Navigation: Pure Pursuit Controller Strategies for Four-Wheeled Mobile Robots." Fusion: Practice and Applications, Vol. 15, No. 2, 2024 ,PP. 80-88 (Doi : https://doi.org/10.54216/FPA.150207) |
| APA | Mohammed R. Hashim Al-Dahhan , Mahmood Abdulrazzaq Alsaadi , Ruqayah R. Al-Dahhan , Salah A. Aliesawi. (2024). The Art of Navigation: Pure Pursuit Controller Strategies for Four-Wheeled Mobile Robots. Journal of Fusion: Practice and Applications, 15 ( 2 ), 80-88 (Doi : https://doi.org/10.54216/FPA.150207) |
| Chicago | Mohammed R. Hashim Al-Dahhan , Mahmood Abdulrazzaq Alsaadi , Ruqayah R. Al-Dahhan , Salah A. Aliesawi. "The Art of Navigation: Pure Pursuit Controller Strategies for Four-Wheeled Mobile Robots." Journal of Fusion: Practice and Applications, 15 no. 2 (2024): 80-88 (Doi : https://doi.org/10.54216/FPA.150207) |
| Harvard | Mohammed R. Hashim Al-Dahhan , Mahmood Abdulrazzaq Alsaadi , Ruqayah R. Al-Dahhan , Salah A. Aliesawi. (2024). The Art of Navigation: Pure Pursuit Controller Strategies for Four-Wheeled Mobile Robots. Journal of Fusion: Practice and Applications, 15 ( 2 ), 80-88 (Doi : https://doi.org/10.54216/FPA.150207) |
| Vancouver | Mohammed R. Hashim Al-Dahhan , Mahmood Abdulrazzaq Alsaadi , Ruqayah R. Al-Dahhan , Salah A. Aliesawi. The Art of Navigation: Pure Pursuit Controller Strategies for Four-Wheeled Mobile Robots. Journal of Fusion: Practice and Applications, (2024); 15 ( 2 ): 80-88 (Doi : https://doi.org/10.54216/FPA.150207) |
| IEEE | Mohammed R. Hashim Al-Dahhan, Mahmood Abdulrazzaq Alsaadi, Ruqayah R. Al-Dahhan, Salah A. Aliesawi, The Art of Navigation: Pure Pursuit Controller Strategies for Four-Wheeled Mobile Robots, Journal of Fusion: Practice and Applications, Vol. 15 , No. 2 , (2024) : 80-88 (Doi : https://doi.org/10.54216/FPA.150207) |