Skip to main content
Log in

Visual Contact Angle Estimation and Traction Control for Mobile Robot in Rough-Terrain

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

Abstract

For a wheeled mobile robot traversing a rough terrain, knowledge of terrain variables is very important for developing effective traction control algorithms. A key variable of the most prevalent information that should be taken into account is the contact angle between the robot wheels and the ground. This paper presents an algorithm for visual estimation of wheel-ground contact angle on uneven terrain. We call it the Visual Contact Angle Estimation (VCAE) method. Given a white LED light source, a monocular camera is required to be mounted on the front wheel and the rear wheel respectively, with a field of view containing the wheel-ground contact interface and its location relative to the wheel is known and fixed during robot travel. This arrangement is used to measure the contact angle with an edge detection strategy. Then a traction control methodology based on multi-objective optimization is presented. This exploits the wheel-ground contact angle obtained in the VCAE system to improve ground traction and reduce power consumption. Simulation and experiment results for a wheeled robot traversing a symmetrical uneven testbed demonstrate the effectiveness of the VCAE method and traction control algorithms.

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.

Similar content being viewed by others

References

  1. Iagnemma, K., Dubowsky, S.: Vehicle wheel-ground contact angle estimation: with application to mobile robot traction control. In: Proceedings of the 7th International Symposium on Advances in Robot Kinematics, pp. 137–146 (2000)

  2. Sreenivasan, S.V., Wilcox, B.H.: Stability and traction control of an actively actuated micro-rover. J. Robot. Syst. 11, 487–502 (1994)

    Article  Google Scholar 

  3. Lauria, M., Piguet, Y., Octopus, R.S.: An autonomous wheeled climbing robot. In: The Fifth International Conference on Climbing and Walking Robots, London, UK, pp. 315 (1994)

  4. Gustafsson, F.: Slip-based tire-road friction es timation. Automatica 33, 1087–1099 (1997)

    Article  MathSciNet  Google Scholar 

  5. Hyeongcheol, L., Masayoshi, T.: Adaptive vehicle traction force control for intelligent vehicle highway systems (IVHS). ASME, DSCD 58, 17–24 (1996)

    Google Scholar 

  6. Eddine, A.D., Tayeb, B.: A comparison of a classical PID and sliding mode: traction control for fast wheeled mobile robot. Int. J. Autom. Control. 4(1), 65–83 (2009)

    Google Scholar 

  7. Iagnemma, K., Dubowsky, S.: Traction control of wheeled robotic vehicles in rough terrain with application to rovers. Int. J. Robot. Res. 23(10), 1029–1040 (2004)

    Article  Google Scholar 

  8. Iagnemma, K., Shibly, H., Rzepniewski, A., Dubowsky, S.: Planning and control algorithms for enhanced rough-terrain rover mobility. In: Proceedings of the Sixth International Symposium on Artificial Intelligence, Robotics and Automation in Space, I-SAIRAS (2001)

  9. Amar, F.B., Jarrault P., Bidaud, P., Grand, C.: Analysis and optimization of obstacle clearance of articulated rovers. In: 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS, pp. 4128–4133 (2009)

  10. Lamon, P., Krebs, A., Lauria, M., Siegwart, R., Shooter, S.: Wheel torque control for a rough terrain rover. In: Proceedings of IEEE International Conference on Robotics and Automation, 2004(5), pp. 4682–4687 (2004)

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to He Xu or Xing Liu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Xu, H., Liu, X., Fu, H. et al. Visual Contact Angle Estimation and Traction Control for Mobile Robot in Rough-Terrain. J Intell Robot Syst 74, 985–997 (2014). https://doi.org/10.1007/s10846-013-9859-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-013-9859-x

Keywords

Navigation