Skip to main content
Log in

Adaptive Fuzzy Velocity Field Control for Navigation of Nonholonomic Mobile Robots

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

This paper presents a novel contour tracking scheme based on a well-posed kinematic representation of differential-driven nonholonomic mobile robots. Firstly, a fuzzy aggregation of spatial sets in cluttered environments allows designing a velocity field to encode the desired velocity vector pointing to the target (the contour). Thus, the resultant smooth trajectory avoids obstacles by combining spatially distributed velocity fields that enable the robot navigation. Finally, the universal approximation property of fuzzy systems facilitates the design of an adaptive PI-like controller, whose closed-loop stability leads to the precise tracking of the velocity field. The results of the performed numerical simulations illustrate the reliability of the proposed scheme.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Data Availability

Data will be available by request after the publication of this paper.

Code Availability

Code will be available by request.

References

  1. Jhang, J.-Y., Lin, C.-J., Lin, C.-T., Young, K.-Y.: Navigation control of mobile robots using an interval type-2 fuzzy controller based on dynamic-group particle swarm optimization. Int. J. Control Autom. Syst. 16(5), 2446–2457 (2018)

    Article  Google Scholar 

  2. Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. In: Autonomous Robot Vehicles, pp. 396–404. Springer (1986)

  3. Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. In: Proceedings. 1985 IEEE International Conference on Robotics and Automation, vol. 2, pp. 500–505. IEEE (1985)

  4. Oriolo, G., Luca, A.D., Vendittelli, M.: Wmr control via dynamic feedback linearization: design, implementation, and experimental validation. IEEE Trans. Control Syst. Technol. 10(6), 835–852 (2002)

    Article  Google Scholar 

  5. Defoort, M., Palos, J., Kokosy, A., Floquet, T., Perruquetti, W., Boulinguez, D.: Experimental motion planning and control for an autonomous nonholonomic mobile robot. In: Proceedings 2007 IEEE International Conference on Robotics and Automation, pp. 2221–2226. IEEE, p 2007 (2007)

  6. Desai, J.P., Ostrowski, J.P., Kumar, V.: Modeling and control of formations of nonholonomic mobile robots. IEEE Trans. Robot. Autom. 17(6), 905–908 (2001)

    Article  Google Scholar 

  7. Fierro, R., Lewis, F.L.: Control of a nonholonomic mobile robot using neural networks. IEEE Trans. Neural Netw. 9(4), 589–600 (1998)

    Article  Google Scholar 

  8. Wang, X., Yang, S.X.: A neuro-fuzzy approach to obstacle avoidance of a nonholonomic mobile robot. In: Proceedings IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM 2003), vol. 1, pages 29–34. IEEE, p 2003 (2003)

  9. Yang, H., Fan, X., Shi, P., Hua, C.: Nonlinear control for tracking and obstacle avoidance of a wheeled mobile robot with nonholonomic constraint. IEEE Trans. Control Syst. Technol. 24(2), 741–746 (2015)

    Google Scholar 

  10. Kapitanyuk, Y.A., Proskurnikov, A.V., Cao, M.: A guiding vector-field algorithm for path-following control of nonholonomic mobile robots. IEEE Trans. Control Syst. Technol. 26(4), 1372–1385 (2017)

    Article  Google Scholar 

  11. Defoort, M., Floquetc, A.K.T., Perruquettic, W.: Decentralized motion planning for cooperative nonholonomic mobile robots. Robot. Auton. Syst. 57(11), 1094–1106 (2009)

    Article  Google Scholar 

  12. Ye, J.: Adaptive control of nonlinear pid-based analog neural networks for a nonholonomic mobile robot. Neurocomputing 71(7-9), 1561–1565 (2008)

    Article  Google Scholar 

  13. Hou, Z.-G., Zou, A.-M., Cheng, L., Tan, M.: Adaptive control of an electrically driven nonholonomic mobile robot via backstepping and fuzzy approach. IEEE Trans. Control Syst. Technol. 17(4), 803–815 (2009)

    Article  Google Scholar 

  14. Fukao, T., Nakagawa, H., Adachi, N.: Adaptive tracking control of a nonholonomic mobile robot. IEEE Trans. Robot. Autom. 16(5), 609–615 (2000)

    Article  Google Scholar 

  15. Dong, W., Kuhnert, K.-D.: Robust adaptive control of nonholonomic mobile robot with parameter and nonparameter uncertainties. IEEE Trans. Robot. 21(2), 261–266 (2005)

    Article  Google Scholar 

  16. Park, B.S., Yoo, S.J., Park, J.B., Choi, Y.H.: A simple adaptive control approach for trajectory tracking of electrically driven nonholonomic mobile robots. IEEE Trans. Control Syst. Technol. 18(5), 1199–1206 (2009)

    Article  Google Scholar 

  17. Yousuf, B.M., Ghauri, M., Noor, A., Ali, A., Khan, A.S., Fatima, R.: Trajectory tracking for nonholonomic mobile robot (nmr) via non-singular terminal sliding mode control. In: 2019 12th Asian Control Conference (ASCC), pp. 533–537. IEEE (2019)

  18. Koubaa, Y., Boukattaya, M., Damak, T.: Adaptive sliding mode control for trajectory tracking of nonholonomic mobile robot with uncertain kinematics and dynamics. Appl. Artif. Intell. 32(9-10), 924–938 (2018)

    Article  Google Scholar 

  19. Mu, J., Yan, X.-G., Spurgeon, S.K., Mao, Z.: Nonlinear sliding mode control of a two-wheeled mobile robot system. Int. J. Model. Identif. Control 27(2), 75–83 (2017)

    Article  Google Scholar 

  20. Wu, X., Jin, P., Zou, T., Qi, Z., Xiao, H., Lou, P.: Backstepping trajectory tracking based on fuzzy sliding mode control for differential mobile robots. J. Intell. Robot. Syst. 96(1), 109–121 (2019)

    Article  Google Scholar 

  21. Safwan, M., Asif, M., et al.: Nonholonomic mobile robot trajectory tracking using hybrid controller. Mehran Univ. Res. J. Eng. Technol. 35(2), 161–170 (2016)

    Google Scholar 

  22. Rubio, Y., Picos, K., Orozco-Rosas, U., Sepúlveda, C., Ballinas, E., Montiel, O., Castillo, O., Sepúlveda, R.: Path following fuzzy system for a nonholonomic mobile robot based on frontal camera information. In: Fuzzy Logic Augmentation of Neural and Optimization Algorithms: Theoretical Aspects and Real Applications, pp. 223–240. Springer (2018)

  23. Tang, L., Landers, R.G.: Multiaxis contour control—the state of the art. IEEE Trans. Control Syst. Technol. 21(6), 1997–2010 (2013)

    Article  Google Scholar 

  24. Li, P.Y., Horowitz, R.: Passive velocity field control (pvfc). part i. geometry and robustness. IEEE Trans. Autom. Control 46(9), 1346–1359 (2001)

    Article  Google Scholar 

  25. Li, P.Y., Horowitz, R.: Passive velocity field control (pvfc). part ii. application to contour following. IEEE Trans. Autom. Control 46(9), 1360–1371 (2001)

    Article  Google Scholar 

  26. Gonċalves, V.M., Pimenta, L.C.A., Maia, C.A, Dutra, Bruno CO, Pereira, Guilherme AS: Vector fields for robot navigation along time-varying curves in n-dimensions. IEEE Trans. Robot. 26(4), 647–659 (2010)

    Article  Google Scholar 

  27. Muñoz-Vázquez, A.J., Sánchez-Torres, J.D., Gutiérrez-Alcalá, S., Jiménez-Rodríguez, E., Loukianov, A.G: Predefined-time robust contour tracking of robotic manipulators. J. Franklin Inst. 356(5), 2709–2722 (2019)

    Article  MathSciNet  Google Scholar 

  28. Ge, S.S., Cui, Y.J.: New potential functions for mobile robot path planning. IEEE Trans. Robot. Autom. 16(5), 615–620 (2000)

    Article  Google Scholar 

  29. Guldner, J., Utkin, V.I: Sliding mode control for gradient tracking and robot navigation using artificial potential fields. IEEE Trans. Robot. Autom. 11(2), 247–254 (1995)

    Article  Google Scholar 

  30. Ge, S.S., Cui, Y.J: Dynamic motion planning for mobile robots using potential field method. Auton. Robot. 13(3), 207–222 (2002)

    Article  Google Scholar 

  31. Rasekhipour, Y., Khajepour, A., Chen, S.-K., Litkouhi, B.: A potential field-based model predictive path-planning controller for autonomous road vehicles. IEEE Trans. Intell. Transp. Syst. 18(5), 1255–1267 (2016)

    Article  Google Scholar 

  32. Li, P.Y, Horowitz, R.: Passive velocity field control of mechanical manipulators. IEEE Trans. Robot. Autom. 15(4), 751–763 (1999)

    Article  Google Scholar 

  33. Yamakita, M., Yazawa, T., Zheng, X.-Z., Ito, K.: An application of passive velocity field control to cooperative multiple 3-wheeled mobile robots. In: Proceedings IEEE/RSJ International Conference on Intelligent Robots and Systems. Innovations in Theory, Practice and Applications (Cat. No. 98CH36190), vol. 1, pp. 368–373. IEEE, p 1998 (1998)

  34. Dixon, W.E, Galluzo, W.E., Hu, G., Crane, C.: Adaptive velocity field control of a wheeled mobile robot. In: Proceedings of the Fifth International Workshop on Robot Motion and Control, pp. 145–150. IEEE (2005)

  35. Erdogan, A., Satici, A.C., Patoglu, V.: Passive velocity field control of a forearm-wrist rehabilitation robot. In: IEEE International Conference on Rehabilitation Robotics, pp. 1–8. IEEE, p 2011 (2011)

  36. Moreno-Valenzuela, J.: A new velocity field controller for robot arms. In: IEEE International Conference on Robotics and Automation, pp. 13–18. IEEE (2006)

  37. Moreno-Valenzuela, J.: Velocity field control of robot manipulators by using only position measurements. J. Franklin Inst. 344(8), 1021–1038 (2007)

    Article  MathSciNet  Google Scholar 

  38. Asl, H.J., Narikiyo, T., Kawanishi, M.: Neural network velocity field control of robotic exoskeletons with bounded input. In: IEEE International Conference on Advanced Intelligent Mechatronics, pp. 1363–1368. IEEE (2017)

  39. Perez-D’Arpino, C., Medina-Melendez, W., Guzman, J., Fermin, L., Fernandez-Lopez, G.: Fuzzy logic based speed planning for autonomous navigation under velocity field control. In: IEEE International Conference on Mechatronics, pp. 1–6. IEEE (2009)

  40. Kelly, R., Bugarín, E., Campa, R.: Application of velocity field control to visual navigation of mobile robots. IFAC Proc Vol 37(8), 537–542 (2004)

    Article  Google Scholar 

  41. Ouyang, P.R, Pano, V., Dam, T.: Pid position domain control for contour tracking. Int. J. Syst. Sci. 46(1), 111–124 (2015)

    Article  Google Scholar 

  42. Ouyang, P.R., Pano, V., Tang, J., Yue, W.H.: Position domain nonlinear pd control for contour tracking of robotic manipulator. Robot. Comput. Integr. Manuf. 51, 14–24 (2018)

    Article  Google Scholar 

  43. Ouyang, P.R., Dam, T., Huang, J., Zhang, W.J.: Contour tracking control in position domain. Mechatronics 22(7), 934–944 (2012)

    Article  Google Scholar 

  44. Ling, J., Feng, Z., Yao, D., Xiao, X.: Non-linear contour tracking using feedback pid and feedforward position domain cross-coupled iterative learning control. Trans. Inst. Meas. Control. 40(6), 1970–1982 (2018)

    Article  Google Scholar 

  45. Meng, D., Li, A., Chen, F., Zhang, K.: Coordinated motion control of a pneumatic-cylinder-driven biaxial gantry for contour tracking tasks. Trans. Inst. Meas. Control. 40(7), 2249–2258 (2018)

    Article  Google Scholar 

  46. Munoz-Vazquez, A.J., Parra-Vega, V., Sanchez, A., Garcia, O., Ruiz-Sanchez, F, Rosales, S.: Passive velocity field control for contour tracking of robots with model-free controller. In: IEEE International Conference of Robotics and Automation, pp. 1934–1940. IEEE, p 2013 (2013)

  47. Munoz-Vazquez, A.J., Parra-Vega, V., Sanchez, A., Rosales, S., Garcia, O., Ruiz-Sanchez, F.: Passive force/velocity field control for contour tracking of constrained robots. In: American Control Conference, pp. 5728–5734. IEEE, p 2013 (2013)

  48. Muñoz-Vázquez, A.J., Parra-Vega, V., Sánchez-Orta, A., Ruiz-Sánchez, F.: A novel force-velocity field for object manipulation with a model-free cooperative controller. Trans. Inst. Meas. Control. 41 (2), 573–581 (2019)

    Article  Google Scholar 

  49. Munoz-Vazquez, A.J., Parra-Vega, V., Sanchez, A.: A passive velocity field control for navigation of quadrotors with model-free integral sliding modes. J. Intell. Robot. Syst. 73(1-4), 373–385 (2014)

    Article  Google Scholar 

  50. Muñoz-Vázquez, A.J., Sánchez-Torres, J. D., Parra-Vega, V., Sánchez-Orta, A., Martínez-Reyes, F.: Robust contour tracking of nonholonomic mobile robots via adaptive velocity field motion planning scheme. Int. J. Adapt. Control Signal Process. 33(6), 890–899 (2019)

    Article  MathSciNet  Google Scholar 

  51. Becerra, H.M., Colunga, J.A., Romero, J.G.: Simultaneous convergence of position and orientation of wheeled mobile robots using trajectory planning and robust controllers, vol. 15, p 1729881418754574 (2018)

  52. Spong, M.W., Hutchinson, S., Vidyasagar, M.: Robot Modeling And Control. Wiley, New York (2020)

    Google Scholar 

Download references

Funding

The present research received no specific grant from any funding agency.

Author information

Authors and Affiliations

Authors

Contributions

A.J. Munõz-Vázquez: Writing the original draft, editing and reviewing, investigation, simulation programming, formal analysis, methodology, conceptualization, and supervision. V. Parra-Vega: Writing the original draft, editing and reviewing, investigation, formal analysis, methodology, conceptualization, and supervision. A. Sánchez-Orta: Writing the original draft, editing and reviewing, investigation, formal analysis, methodology, and conceptualization. J.D. Sánchez-Torres: Editing and reviewing, investigation, formal analysis, and conceptualization.

Corresponding author

Correspondence to Aldo Jonathan Muñoz-Vázquez.

Ethics declarations

Conflict of Interests

The authors declare no conflict of interest.

Consent for Publication

The authors declare no interest conflict regarding the publication of this paper.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Muñoz-Vázquez, A.J., Parra-Vega, V., Sánchez-Orta, A. et al. Adaptive Fuzzy Velocity Field Control for Navigation of Nonholonomic Mobile Robots. J Intell Robot Syst 101, 38 (2021). https://doi.org/10.1007/s10846-020-01306-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10846-020-01306-w

Keywords

Navigation