Sliding Mode Control for Trajectory Tracking on Non-Holonomic Autonomous Mobile Robot (AMR
##plugins.themes.academic_pro.article.sidebar##
Available on-line since
Oct 6, 2026
Download
Statistic
Read Counter : 0
Download : 0
Download : 0
##plugins.themes.academic_pro.article.main##
Abstract
Trajectory tracking of non-holonomic autonomous mobile robots (AMRs) becomes more demanding when a passive trailer is towed and wheel slip occurs. This study developed a two-surface sliding mode control (SMC) scheme that regulates the distance and heading errors of a pure-pursuit lookahead point and maps the desired accelerations to wheel torques through dynamic inversion, with boundary-layer saturation, heading-singularity safeguards, and jackknife protection. The controller was evaluated in ROS 2 Jazzy and Gazebo Harmonic and integrated with a breadth-first search (BFS) planner using mode-adaptive obstacle inflation. On an oval path with a rigid hitch, the tracking root-mean-square error (RMSE) was 0.042 m, whereas a replicated three-surface baseline diverged (RMSE 4.68 m) with 79.5% torque saturation; the proposed controller required approximately five times less control effort without saturation. A LuGre-based slip test showed that wheel-odometry feedback diverged substantially from ground truth, supporting map-based localization. Hardware validation remains necessary.
##plugins.themes.academic_pro.article.details##
License and Copyright
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright (c): Muhammad Daffa Karim, Wahyu Adhie Candra, Pipit Anggraeni, Noval Lilansa, Adhitya Sumardi Sunarya, Nur Jamiludin Ramadhan, Andri Wiyono (2026)
How to Cite
Karim, M., Candra, W., Anggraeni, P., Lilansa, N., Sunarya, A., Ramadhan, N., & Wiyono, A. (2026). Sliding Mode Control for Trajectory Tracking on Non-Holonomic Autonomous Mobile Robot (AMR. MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering, 8(2), 217 - 230. Retrieved from https://www.motivection.imeirs.org/index.php/motivection/article/view/599
References
[1] R. Bernardo, J. M. C. Sousa, and P. J. S. Gonçalves, “Survey on robotic systems for internal logistics,” J. Manuf. Syst., vol. 65, pp. 339–350, Oct. 2022, doi: 10.1016/j.jmsy.2022.09.014.
[2] M. B. Alatise and G. P. Hancke, “A review on challenges of autonomous mobile robot and sensor fusion methods,” IEEE Access, vol. 8, pp. 39830–39846, 2020, doi: 10.1109/ACCESS.2020.2975643.
[3] A. K. Grover and M. H. Ashraf, “Leveraging autonomous mobile robots for Industry 4.0 warehouses: A multiple case study analysis,” Int. J. Logist. Manag., vol. 35, no. 4, pp. 1168–1199, 2024, doi: 10.1108/IJLM-09-2022-0362.
[4] Risfendra, R. Nursalam, E. Purnama, and Defri, “Implementation of finite state automata for 6-axis robot in the screwing process,” MOTIVECTION: J. Mech. Electr. Ind. Eng., vol. 7, no. 2, pp. 189–200, 2025, doi: 10.46574/motivection.v7i2.445.
[5] A. Khanpoor, A. K. Khalaji, and S. A. A. Moosavian, “Modeling and control of an underactuated tractor–trailer wheeled mobile robot,” Robotica, vol. 35, no. 12, pp. 2297–2318, Dec. 2017, doi: 10.1017/S0263574716000886.
[6] D. Wang and C. B. Low, “Modeling and analysis of skidding and slipping in wheeled mobile robots: Control design perspective,” IEEE Trans. Robot., vol. 24, no. 3, pp. 676–687, Jun. 2008, doi: 10.1109/TRO.2008.921563.
[7] J. Wei and B. Zhu, “Model predictive control for trajectory-tracking and formation of wheeled mobile robots,” Neural Comput. Appl., vol. 34, no. 19, pp. 16351–16365, Oct. 2022, doi: 10.1007/s00521-022-07195-4.
[8] E. Kayacan, H. Ramon, and W. Saeys, “Robust trajectory tracking error model-based predictive control for unmanned ground vehicles,” IEEE/ASME Trans. Mechatronics, vol. 21, no. 2, pp. 806–814, Apr. 2016, doi: 10.1109/TMECH.2015.2492984.
[9] N.-B. Hoang and H.-J. Kang, “Neural network-based adaptive tracking control of mobile robots in the presence of wheel slip and external disturbance force,” Neurocomputing, vol. 188, pp. 12–22, May 2016, doi: 10.1016/j.neucom.2015.02.101.
[10] T. A. Mai, T. S. Dang, D. T. Duong, V. C. Le, and S. Banerjee, “A combined backstepping and adaptive fuzzy PID approach for trajectory tracking of autonomous mobile robots,” J. Braz. Soc. Mech. Sci. Eng., vol. 43, no. 3, Art. no. 156, Mar. 2021, doi: 10.1007/s40430-020-02767-8.
[11] P. Angraeni, M. N. Rizal, H. Khoirunnisa, and T. Kristian, “Experimental of quadcopter trajectory tracking control based ROS,” MOTIVECTION: J. Mech. Electr. Ind. Eng., vol. 5, no. 2, pp. 295–302, 2023, doi: 10.46574/motivection.v5i2.232.
[12] X. Gao, L. Yan, and C. Gerada, “Modeling and analysis in trajectory tracking control for wheeled mobile robots with wheel skidding and slipping: Disturbance rejection perspective,” Actuators, vol. 10, no. 9, Art. no. 222, Sep. 2021, doi: 10.3390/act10090222.
[13] K. Alipour, A. B. Robat, and B. Tarvirdizadeh, “Dynamics modeling and sliding mode control of tractor-trailer wheeled mobile robots subject to wheels slip,” Mech. Mach. Theory, vol. 138, pp. 16–37, Aug. 2019, doi: 10.1016/j.mechmachtheory.2019.03.038.
[14] M. Cui, H. Liu, W. Liu, and Y. Qin, “An adaptive unscented Kalman filter-based controller for simultaneous obstacle avoidance and tracking of wheeled mobile robots with unknown slipping parameters,” J. Intell. Robot. Syst., vol. 92, no. 3–4, pp. 489–504, Dec. 2018, doi: 10.1007/s10846-017-0761-9.
[15] V. Utkin, A. Poznyak, Y. Orlov, and A. Polyakov, “Conventional and high order sliding mode control,” J. Franklin Inst., vol. 357, no. 15, pp. 10244–10261, Oct. 2020, doi: 10.1016/j.jfranklin.2020.06.018.
[16] K. Liu, H. Gao, H. Ji, and Z. Hao, “Adaptive sliding mode based disturbance attenuation tracking control for wheeled mobile robots,” Int. J. Control Autom. Syst., vol. 18, no. 5, pp. 1288–1298, May 2020, doi: 10.1007/s12555-019-0262-7.
[17] B. Jiang, J. Li, and S. Yang, “An improved sliding mode approach for trajectory following control of nonholonomic mobile AGV,” Sci. Rep., vol. 12, no. 1, Art. no. 17763, Oct. 2022, doi: 10.1038/s41598-022-22697-w.
[18] E. A. Martínez, H. Ríos, and M. Mera, “Robust tracking control design for unicycle mobile robots with input saturation,” Control Eng. Pract., vol. 107, Art. no. 104676, Feb. 2021, doi: 10.1016/j.conengprac.2020.104676.
[19] H. Van Doan and N. T.-T. Vu, “Adaptive sliding mode control for uncertain wheel mobile robot,” Int. J. Electr. Comput. Eng., vol. 13, no. 4, pp. 3939–3947, Aug. 2023, doi: 10.11591/ijece.v13i4.pp3939-3947.
[20] K. J. Åström and C. Canudas-de-Wit, “Revisiting the LuGre friction model,” IEEE Control Syst. Mag., vol. 28, no. 6, pp. 101–114, Dec. 2008, doi: 10.1109/MCS.2008.929425.
[21] A. Mashayekhi, S. Behbahani, A. Nahvi, M. Keshmiri, and M. Shakeri, “Analytical describing function of LuGre friction model,” Int. J. Intell. Robot. Appl., vol. 6, no. 3, pp. 437–448, Sep. 2022, doi: 10.1007/s41315-021-00220-0.
[22] O. N. Şahin and M. İ. C. Dede, “Investigation of longitudinal friction characteristics of an omnidirectional wheel via LuGre model,” Robotica, vol. 39, no. 9, pp. 1654–1673, Sep. 2021, doi: 10.1017/S0263574720001423.
[23] X. Zhang, D. Qin, S. Wang, Y. Xie, H. Li, and S. Li, “Position/attitude cascade regulation of nonholonomic four-wheeled mobile robot via double-loop sliding-mode control mechanism,” Entropy, vol. 25, no. 1, Art. no. 27, 2023, doi: 10.3390/e25010027.
[24] B. K. Patle, G. Babu L, A. Pandey, D. R. K. Parhi, and A. Jagadeesh, “A review: On path planning strategies for navigation of mobile robot,” Def. Technol., vol. 15, no. 4, pp. 582–606, Aug. 2019, doi: 10.1016/j.dt.2019.04.011.
[2] M. B. Alatise and G. P. Hancke, “A review on challenges of autonomous mobile robot and sensor fusion methods,” IEEE Access, vol. 8, pp. 39830–39846, 2020, doi: 10.1109/ACCESS.2020.2975643.
[3] A. K. Grover and M. H. Ashraf, “Leveraging autonomous mobile robots for Industry 4.0 warehouses: A multiple case study analysis,” Int. J. Logist. Manag., vol. 35, no. 4, pp. 1168–1199, 2024, doi: 10.1108/IJLM-09-2022-0362.
[4] Risfendra, R. Nursalam, E. Purnama, and Defri, “Implementation of finite state automata for 6-axis robot in the screwing process,” MOTIVECTION: J. Mech. Electr. Ind. Eng., vol. 7, no. 2, pp. 189–200, 2025, doi: 10.46574/motivection.v7i2.445.
[5] A. Khanpoor, A. K. Khalaji, and S. A. A. Moosavian, “Modeling and control of an underactuated tractor–trailer wheeled mobile robot,” Robotica, vol. 35, no. 12, pp. 2297–2318, Dec. 2017, doi: 10.1017/S0263574716000886.
[6] D. Wang and C. B. Low, “Modeling and analysis of skidding and slipping in wheeled mobile robots: Control design perspective,” IEEE Trans. Robot., vol. 24, no. 3, pp. 676–687, Jun. 2008, doi: 10.1109/TRO.2008.921563.
[7] J. Wei and B. Zhu, “Model predictive control for trajectory-tracking and formation of wheeled mobile robots,” Neural Comput. Appl., vol. 34, no. 19, pp. 16351–16365, Oct. 2022, doi: 10.1007/s00521-022-07195-4.
[8] E. Kayacan, H. Ramon, and W. Saeys, “Robust trajectory tracking error model-based predictive control for unmanned ground vehicles,” IEEE/ASME Trans. Mechatronics, vol. 21, no. 2, pp. 806–814, Apr. 2016, doi: 10.1109/TMECH.2015.2492984.
[9] N.-B. Hoang and H.-J. Kang, “Neural network-based adaptive tracking control of mobile robots in the presence of wheel slip and external disturbance force,” Neurocomputing, vol. 188, pp. 12–22, May 2016, doi: 10.1016/j.neucom.2015.02.101.
[10] T. A. Mai, T. S. Dang, D. T. Duong, V. C. Le, and S. Banerjee, “A combined backstepping and adaptive fuzzy PID approach for trajectory tracking of autonomous mobile robots,” J. Braz. Soc. Mech. Sci. Eng., vol. 43, no. 3, Art. no. 156, Mar. 2021, doi: 10.1007/s40430-020-02767-8.
[11] P. Angraeni, M. N. Rizal, H. Khoirunnisa, and T. Kristian, “Experimental of quadcopter trajectory tracking control based ROS,” MOTIVECTION: J. Mech. Electr. Ind. Eng., vol. 5, no. 2, pp. 295–302, 2023, doi: 10.46574/motivection.v5i2.232.
[12] X. Gao, L. Yan, and C. Gerada, “Modeling and analysis in trajectory tracking control for wheeled mobile robots with wheel skidding and slipping: Disturbance rejection perspective,” Actuators, vol. 10, no. 9, Art. no. 222, Sep. 2021, doi: 10.3390/act10090222.
[13] K. Alipour, A. B. Robat, and B. Tarvirdizadeh, “Dynamics modeling and sliding mode control of tractor-trailer wheeled mobile robots subject to wheels slip,” Mech. Mach. Theory, vol. 138, pp. 16–37, Aug. 2019, doi: 10.1016/j.mechmachtheory.2019.03.038.
[14] M. Cui, H. Liu, W. Liu, and Y. Qin, “An adaptive unscented Kalman filter-based controller for simultaneous obstacle avoidance and tracking of wheeled mobile robots with unknown slipping parameters,” J. Intell. Robot. Syst., vol. 92, no. 3–4, pp. 489–504, Dec. 2018, doi: 10.1007/s10846-017-0761-9.
[15] V. Utkin, A. Poznyak, Y. Orlov, and A. Polyakov, “Conventional and high order sliding mode control,” J. Franklin Inst., vol. 357, no. 15, pp. 10244–10261, Oct. 2020, doi: 10.1016/j.jfranklin.2020.06.018.
[16] K. Liu, H. Gao, H. Ji, and Z. Hao, “Adaptive sliding mode based disturbance attenuation tracking control for wheeled mobile robots,” Int. J. Control Autom. Syst., vol. 18, no. 5, pp. 1288–1298, May 2020, doi: 10.1007/s12555-019-0262-7.
[17] B. Jiang, J. Li, and S. Yang, “An improved sliding mode approach for trajectory following control of nonholonomic mobile AGV,” Sci. Rep., vol. 12, no. 1, Art. no. 17763, Oct. 2022, doi: 10.1038/s41598-022-22697-w.
[18] E. A. Martínez, H. Ríos, and M. Mera, “Robust tracking control design for unicycle mobile robots with input saturation,” Control Eng. Pract., vol. 107, Art. no. 104676, Feb. 2021, doi: 10.1016/j.conengprac.2020.104676.
[19] H. Van Doan and N. T.-T. Vu, “Adaptive sliding mode control for uncertain wheel mobile robot,” Int. J. Electr. Comput. Eng., vol. 13, no. 4, pp. 3939–3947, Aug. 2023, doi: 10.11591/ijece.v13i4.pp3939-3947.
[20] K. J. Åström and C. Canudas-de-Wit, “Revisiting the LuGre friction model,” IEEE Control Syst. Mag., vol. 28, no. 6, pp. 101–114, Dec. 2008, doi: 10.1109/MCS.2008.929425.
[21] A. Mashayekhi, S. Behbahani, A. Nahvi, M. Keshmiri, and M. Shakeri, “Analytical describing function of LuGre friction model,” Int. J. Intell. Robot. Appl., vol. 6, no. 3, pp. 437–448, Sep. 2022, doi: 10.1007/s41315-021-00220-0.
[22] O. N. Şahin and M. İ. C. Dede, “Investigation of longitudinal friction characteristics of an omnidirectional wheel via LuGre model,” Robotica, vol. 39, no. 9, pp. 1654–1673, Sep. 2021, doi: 10.1017/S0263574720001423.
[23] X. Zhang, D. Qin, S. Wang, Y. Xie, H. Li, and S. Li, “Position/attitude cascade regulation of nonholonomic four-wheeled mobile robot via double-loop sliding-mode control mechanism,” Entropy, vol. 25, no. 1, Art. no. 27, 2023, doi: 10.3390/e25010027.
[24] B. K. Patle, G. Babu L, A. Pandey, D. R. K. Parhi, and A. Jagadeesh, “A review: On path planning strategies for navigation of mobile robot,” Def. Technol., vol. 15, no. 4, pp. 582–606, Aug. 2019, doi: 10.1016/j.dt.2019.04.011.