Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-26T07:01:05.558Z Has data issue: false hasContentIssue false
  • English
  • Français

Trajectory estimation of a skid-steering mobile robot propelled by independently driven wheels

Published online by Cambridge University Press:  06 May 2011

Tokuji Okada ,
Abeer Mahmoud ,
Wagner Tanaka Botelho  and
Toshimi Shimizu
Tokuji Okada*
Affiliation:
Information Science and Engineering, Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan
Abeer Mahmoud
Affiliation:
Information Science and Engineering, Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan
Wagner Tanaka Botelho
Affiliation:
Information Science and Engineering, Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan
Toshimi Shimizu
Affiliation:
Information Science and Engineering, Graduate School of Science and Technology, Niigata University, Niigata 950-2181, Japan
*
*Corresponding author. E-mail: okada@eng.niigata-u.ac.jp
Get access Rights & Permissions [Opens in a new window]

Summary

This paper analyses a mobile robot with independently rotating wheels travelling on uneven but smooth ground, including ascending or descending surfaces. We formulate a mathematical expression for the energy cost of the robot's movement. For our analysis, we utilise the principle of virtual work and assume that the robot moves with a fixed arrangement of wheel axes and without using a steering handle. The mathematical model reveals that the coefficient of friction and the payload distribution dominate the wheel behaviour, including slipping and skidding. We minimise the virtual work expression to determine the robot's motion complying with driven wheels. The model also enables us to estimate trajectories for different ground conditions. A hybrid robot, PEOPLER-II, is used to demonstrate the predicted motions, including turns and spins, by following angular velocity control rules. Experimental data verifies that the proposed formulation and minimisation of virtual work are valid techniques for predicting a robot's trajectory. The method described is widely applicable to wheeled robots having independently driven wheels.

Keywords

Wheeled robotTrajectory estimationVirtual workCoefficient of frictionPayload distribution
Type
Articles
Information
Robotica , Volume 30 , Issue 1 , January 2012 , pp. 123 - 132
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Asano, F. and Luo, Z.-W., “Asymptotically stable biped gait generation based on stability principle of rimless wheel,” Robotica 27, 949–958 (2009).CrossRefGoogle Scholar
2.Han, S., Choi, B. and Lee, J., “A precise curved motion planning for a differential driving mobile robot,” Mechatronics 18, 486–494 (2008).Google Scholar
3.Shiller, Z. and Gwo, Y.-R., “Dynamic motion planning of autonomous vehicles,” IEEE Trans. Robot. Autom. 7 (2), 241–249 (1991).CrossRefGoogle Scholar
4.Nitulescu, M., “Theoretical Aspects in Wheeled Mobile Robot Control,” Proceedings of the IEEE International Conference on Automation, Quality and Testing, Robotics, Cluj-Napoca (May 2008) vol. 2, pp. 331–336.Google Scholar
5.Low, C. B. and Wang, D., “Integrated Estimation for Wheel Mobile Robot Posture, Velocities, and Wheel Skidding and Slipping Perturbations,” Proceedings of the IEEE/RSJ Internatinal Conference on Intelligent Robots and Systems (IROS), Nice, France (Sep. 2008) pp. 20–30.Google Scholar
6.Caracciolo, L., Luca, A. D. and Iannitti, S., “Trajectory Tracking Control of a Four-Wheel Differentially Driven Mobile Robot,” Proceedings of the IEEE International Conference on Robotics and Automation, Detroit, Michigan (May 1999) pp. 2632–2638.Google Scholar
7.Wang, D. and Low, C. B., “Modeling and analysis of skidding and slipping in wheeled mobile robots: Control design perspective,” IEEE Trans. Robot. 24 (3), 676–687 (2008).Google Scholar
8.Balakrishna, R. and Ghosal, A., “Modeling of slip for wheeled mobile robots,” IEEE Trans. Robot. Autom. 11 (1), 126–132 (1995).Google Scholar
9.Chitsaz, H., Lavalle, S. M., Balkcom, D. J. and Mason, M. T., “Minimum wheel-rotation paths for differential-drive mobile robots,” Int. J. Rob. Res. 28 (1), 66–80 (2009).Google Scholar
10.Reister, D. B. and Pin, F. G., “Time-optimal trajectories for mobile robots with two independently driven wheels,” Int. J. Rob. Res. 13 (1), 38–54 (1994).Google Scholar
11.Minor, M. A., Albiston, B. W. and Schwensen, C. L., “Simplified motion control of a two-axle compliant framed wheeled mobile robot,” Int. Trans. Robot. 22 (3), 491–506 (2006).Google Scholar
12.Okada, T., Mahmoud, A. and Botelho, W., “Trajectory Analysis of an Independently Driven Wheeled Robot and It's Experimental Verification,” Proceedings of the 12th International Conference on Climbing and Walking Robots (CLAWAR), Istanbul, Turkey (Sep. 2009) pp. 781–790.Google Scholar
13.Okada, T., Botelho, W. T. and Shimizu, T., “Compatible Use of a Legged Robot as a Wheeled Robot and Its Demonstrative Simulation,” Proceedings of the 9th International Conference on Climbing and Walking Robots (CLAWAR), Brussels, Belgium (Sep. 2006) pp. 34–44.Google Scholar
14.Okada, T., Botelho, W. T. and Shimizu, T., “Motion analysis with experimental verification of the hybrid robot, PEOPLER-II, for reversible switch between walk and roll on demand,” Int. J. Rob. Res. 29 (9), 1199–1221 (Aug. 2010).Google Scholar
15.Sakai, H., “Friction and wear of tire tread rubber,” J. Tire Science and Technology, 24 (3), 252–275 (Jul. 1996).CrossRefGoogle Scholar
16.Hotta, H., “On a friction coefficient of sliding on the ground,” Monthly Report of CERI, 481, 65–68 (1993) (in Japanese).Google Scholar
17.Mahmoud, A., Okada, T. and Shimizu, T., “A simulation for estimating a circular trajectory of a rotating four-legged mobile robot on regular terrain,” J. Cybern. Syst. 2 (1), 9–16 (Jun. 2009).Google Scholar