Implementation of Behavior-Based Navigation Algorithm on Four-Wheel Steering Mobile Robot

Document Type : Research Paper


1 Mechatronics Laboratory, Department of Mechanical Engineering, Tarbiat Modares University, Tehran, Iran

2 Assistant Professor, Department of Mechanical Engineering, Tarbiat Modares University, Tehran, Iran.


In recent years, wheeled autonomous mobile robots have become widely used in a number of industrial applications. Therefore, accurate and efficient controllers are required in order to assure safe and accurate navigation of these vehicles. In this study, an effective behavior-based navigation algorithm (BBNA) is applied to control the trajectory of the four-wheel steering (FWS) mobile robot. The BBNA combines the ‘Goal-to-Goal’ and ‘Obstacle Avoidance’ behaviors into one comprehensive navigation strategy. With this algorithm, many switching between modes occurs over a short amount of time, which increases the risk of creating the chattering phenomenon. Due to overcoming this phenomenon, an additional mode is considered between the ‘Go-to-Goal’ and ‘Obstacle Avoidance’ modes that is called ‘Follow-Wall’ behavior. At first, the BBNA was designed to control the navigation of a point mass robot. One of the significant characteristics of BBNA is that its control commands can be used to calculate the linear and angular velocity of a unicycle mobile robot. Thus, the BBNA can navigate the unicycle mobile robot successfully to the goal position. In order to apply the BBNA to an FWS mobile robot, its dynamic equations must be converted to those of a unicycle mobile robot. The present study determines the dynamic equations of the FWS mobile robot by using the Ackermann- Jeantnat model of steering. Since these equations are the same as those for the unicycle mobile robot, the FWS mobile robot can be controlled by the BBNA. Finally, the implementation of the BBNA for the FWS mobile robot is simulated using MATLAB software. Simulated results indicate that BBNA generates an optimal path by perfectly switching between ‘Go to Goal’, ‘Obstacle Avoidance’, and ‘Follow Wall’ modes, which keeps the FWS mobile robot arriving at the goal position.


  1. Fuke, Y., Krotkov, E.: Dead reckoning for a lunar rover on uneven terrain. Proc. - IEEE Int. Conf. Robot. Autom. 1, 411–416 (1996).
  2. Caracciolo, L., De Luca, A., Iannitti, S.: Trajectory tracking control of a four-wheel differentially driven mobile robot. Proc. - IEEE Int. Conf. Robot. Autom. 4, 2632–2638 (1999).
  3. Roland Siegwart, Illah Nourbakhsh, D.S.: Introduction to Autonomous Mobile Robots - Roland Siegwart, Illah Reza Nourbakhsh, Davide Scaramuzza - Google Boeken. (2004)
  4. Khadiv, M., Moosavian, S.A.A., Yousefi-Koma, A., Sadedel, M., Ehsani-Seresht, A., Mansouri, S.: Rigid vs compliant contact: an experimental study on biped walking. Multibody Syst. Dyn. 45, 379–401 (2019).
  5. Sadedel, M., Yousefi-Koma, A., Khadiv, M., Mahdavian, M.: Adding low-cost passive toe joints to the feet structure of SURENA III humanoid robot. Robotica. 35, 2099–2121 (2017).
  6. Sadedel, M., Yousefikoma, A., Iranmanesh, F.: Analytical Dynamic Modelling of Heel-off and Toe-off Motions for a 2D Humanoid Robot. J. Comput. Appl. Mech. 46, 243–256 (2015).
  7. Saenz, A., Santibañez, V., Bugarin, E., Dzul, A., Ríos, H., Villalobos-Chin, J.: Velocity Control of an Omnidirectional Wheeled Mobile Robot Using Computed Voltage Control with Visual Feedback: Experimental Results. Int. J. Control. Autom. Syst. 19, 1089–1102 (2021).
  8. Nagatani, K., Noyori, T., Yoshida, K.: Development of multi-D.O.F. tracked vehicle to traverse weak slope and climb up rough slope. In: IEEE International Conference on Intelligent Robots and Systems. pp. 2849–2854 (2013)
  9. Li, H., Zhao, Y., Lin, F., Zhu, M.: Nonlinear dynamics modeling and rollover control of an off-road vehicle with mechanical elastic wheel. J. Brazilian Soc. Mech. Sci. Eng. 40, 1–17 (2018).
  10. Xu, X., Waters, T., Pickem, D., Glotfelter, P., Egerstedt, M., Tabuada, P., Grizzle, J.W., Ames, A.D.: Realizing simultaneous lane keeping and adaptive speed regulation on accessible mobile robot testbeds. 1st Annu. IEEE Conf. Control Technol. Appl. CCTA 2017. 2017-Janua, 1769–1775 (2017).
  11. Ajeil, F.H., Ibraheem, I.K., Azar, A.T., Humaidi, A.J.: Autonomous navigation and obstacle avoidance of an omnidirectional mobile robot using swarm optimization and sensors deployment. Int. J. Adv. Robot. Syst. 17, 172988142092949 (2020).
  12. Oftadeh, R., Aref, M.M., Ghabcheloo, R., Mattila, J.: Bounded-velocity motion control of four wheel steered mobile robots. 2013 IEEE/ASME Int. Conf. Adv. Intell. Mechatronics Mechatronics Hum. Wellbeing, AIM 2013. 255–260 (2013).
  13. Oftadeh, R., Aref, M.M., Ghabcheloo, R., Mattila, J.: Mechatronic design of a four wheel steering mobile robot with fault-tolerant odometry feedback. IFAC (2013)
  14. Sorour, M., Cherubini, A., Khelloufi, A., Passama, R., Fraisse, P.: Complementary-route based ICR control for steerable wheeled mobile robots. Rob. Auton. Syst. 118, 131–143 (2019).
  15. VertiGo wheeled robot isn’t stopped by walls,
  16. Do, K.D.: Global inverse optimal exponential path-tracking control of mobile robots driven by Lévy processes. Robotica. 1–27 (2021).
  17. Valero, F., Rubio, F., Llopis-Albert, C.: Assessment of the Effect of Energy Consumption on Trajectory Improvement for a Car-like Robot. Robotica. 37, 1998–2009 (2019).
  18. Prasad, A., Sharma, B., Vanualailai, J.: A new stabilizing solution for motion planning and control of multiple robots. Robotica. 34, 1071–1089 (2016).
  19. Valera, Á., Valero, F., Vallés, M., Besa, A., Mata, V., Llopis-Albert, C.: Navigation of autonomous light vehicles using an optimal trajectory planning algorithm. Sustain. 13, 1–23 (2021).
  20. Lee, J.K., Choi, Y.H., Park, J.B.: Sliding mode tracking control of mobile robots with approach angle in cartesian coordinates. Int. J. Control. Autom. Syst. 13, 718–724 (2015).
  21. Fnadi, M., Menkouz, B., Plumet, F., Ben Amar, F.: Path Tracking Control for a Double Steering Off-Road Mobile Robot. In: CISM International Centre for Mechanical Sciences, Courses and Lectures. pp. 441–449 (2019)
  22. Carlucho, I., De Paula, M., Acosta, G.G.: Double Q-PID algorithm for mobile robot control. Expert Syst. Appl. 137, 292–307 (2019).
  23. Wang, D., Wei, W., Yeboah, Y., Li, Y., Gao, Y.: A Robust Model Predictive Control Strategy for Trajectory Tracking of Omni-directional Mobile Robots. J. Intell. Robot. Syst. Theory Appl. 98, 439–453 (2020).
  24. Allagui, N.Y., Abid, D.B., Derbel, N.: Autonomous navigation of mobile robot with combined fractional order PI and fuzzy logic controllers. 16th Int. Multi-Conference Syst. Signals Devices, SSD 2019. 78–83 (2019).
  25. Maalouf, E., Saad, M., Saliah, H.: A higher level path tracking controller for a four-wheel differentially steered mobile robot. Rob. Auton. Syst. 54, 23–33 (2006).
  26. Hu, C., Wang, R., Yan, F., Chen, N.: Output constraint control on path following of four-wheel independently actuated autonomous ground vehicles. IEEE Trans. Veh. Technol. 65, 4033–4043 (2016).
  27. Wang, D., Qi, F.: Trajectory planning for a four-wheel-steering vehicle. In: Proceedings - IEEE International Conference on Robotics and Automation. pp. 3320–3325 (2001)
  28. Caracciolo, L., De Luca, A., Iannitti, S.: Trajectory tracking control of a four-wheel differentially driven mobile robot. Proc. - IEEE Int. Conf. Robot. Autom. 4, 2632–2638 (1999).
  29. Filipescu, A., Minzu, V., Filipescu, A., Minca, E.: Discrete-time sliding-mode control of a mobile platform with four driving/steering wheels. In: Lecture Notes in Electrical Engineering. pp. 401–409. Springer, Berlin, Heidelberg (2011)
  30. Arkin, R., Arkin, R.: Behavior-based robotics. (1998)
  31. Kortenkamp, D.Y., Bonasso, R.P., Murphy, R.: Artificial Intelligence and Mobile Robots. (1998)
  32. Mahadevuni, A., Li, P.: Navigating mobile robots to target in near shortest time using reinforcement learning with spiking neural networks. Proc. Int. Jt. Conf. Neural Networks. 2017-May, 2243–2250 (2017).
  33. M.Egerestedt: Control of Mobile Robots.
  34. M. Egerstedt: Controls for the Masses. EEE Control Syst. Mag-azine. 33, 40–44 (2013)
  35. Egerstedt, M.: Behavior based robotics using hybrid automata. Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics). 1790, 103–116 (2000).
  36. Khazaee, M., Sadedel, M., Davarpanah, A.: Behavior-Based Navigation of an Autonomous Hexapod Robot Using a Hybrid Automaton. J. Intell. Robot. Syst. Theory Appl. 102, (2021).
  37. Armah: Implementation of Autonomous Navigation Algorithms on Two-Wheeled Ground Mobile Robot. Am. J. Eng. Appl. Sci. 7, 149–164 (2014).
  38. Gautam, P., Sahai, S., Kelkar, S.S., Agrawal, P.S., D, M.R.: Designing Variable Ackerman Steering Geometry for Formula Student Race Car. Int. J. Anal. Exp. Finite Elem. Anal. 8, 1–11 (2021).
  39. Khan, A., Patel, M., Bhosale, O., Pawar, S., Patil, A.: A Review on Design and Assembly of Go- Kart Steering System. 193–197 (2021)
  40. Hartani, K., Miloud, Y., Miloudi, A.: Electric Vehicle stability with rear Electronic differential Traction. Int. Symp. Enviroment Friendly Energies Electrcal Appllcations. 1–5 (2010)
  41. Gillespie, T.D.: Fundamentals of Vehicle Dynamics. Fundam. Veh. Dyn. (1992).
  42. Hao, Y., Wang, J., Chepinskiy, S.A., Krasnov, A.J., Liu, S.: Backstepping based trajectory tracking control for a four-wheel mobile robot with differential-drive steering. Chinese Control Conf. CCC. 4918–4923 (2017).
  43. Wu, X., Xu, M., Wang, L.: Differential Speed Steering Control for Four-Wheel Independent Driving Electric Vehicle. Int. J. Mater. Mech. Manuf. 355–359 (2013).
Volume 52, Issue 4
December 2021
Pages 619-641
  • Receive Date: 04 September 2021
  • Revise Date: 20 December 2021
  • Accept Date: 26 December 2021