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Waypoints guidance of differential-drive mobile robots with kinematic and precision constraints

Published online by Cambridge University Press:  22 July 2014

Patrice Boucher
Patrice Boucher*
Affiliation:
Perception and Robotics Laboratory, Faculty of Electrical Engineering, Polytechnique Montreal, 2500, Chemin de Polytechnique, Canada
*
*Corresponding author. E-mail: [email protected]
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Summary

This paper proposes a new kinematic controller for the waypoints guidance of robotic mobile platforms. A notable feature of the controller is its ability to process the raw sequence of waypoints to produce smooth reference velocities from control laws that are derived by taking into account a driving profile including the velocity limits, the acceleration limits, the motion modes through each waypoint (forward or backward) and the precision constraints that are required to ensure accurate waypoints traversal. A mathematical analysis demonstrates the convergence of the movements through the waypoints sequence. In addition, we present a simple way to adapt the driving profile in order that the platform reaches the last waypoint at a prescribed time. A feed-forward unit is finally described, that compensates for delays and first-order poles in the velocity response of the platform. Various simulations and experiments on real robotic platforms demonstrate the behavior and the effectiveness of the solution.

Keywords

Waypoints guidancepath-followingkinematic constraintssmooth navigationtemporal planningmobile robots
Type
Articles
Information
Robotica , Volume 34 , Issue 4 , April 2016 , pp. 876 - 899
Copyright
Copyright © Cambridge University Press 2014 

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References

1.Boucher, P., Atrash, A., Kelouwani, S., Honoré, W., Nguyen, H., Villemure, J., Routhier, F., Cohen, P., Demers, L. and Forget, R.et al., “Design and validation of an intelligent wheelchair towards a clinically-functional outcome,” J. Neuroeng. Rehabil. 10 (1), 58 (2013).Google Scholar
2.Gulati, S. and Kuipers, B., “High Performance Control for Graceful Motion of an Intelligent Wheelchair,” Proceedings of the IEEE International Conference on Robotics and Automation, 2008. ICRA 2008, IEEE (2008) pp. 3932–3938.Google Scholar
3.Park, J. J. and Kuipers, B., “A Smooth Control Law for Graceful Motion of Differential Wheeled Mobile Robots in 2d Environment,” Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2011 (May 2011) pp. 4896–4902.Google Scholar
4.Dubins, L., “On curves of minimal length with a constraint on average curvature, and with prescribed initial and terminal positions and tangents,” Am. J. Math. 79 (3), 497–516 (1957).Google Scholar
5.Munoz, V., Ollero, A., Prado, M. and Simon, A., “Mobile Robot Trajectory Planning with Dynamic and Kinematic Constraints,” Proceedings of the International Conference on Robotics and Automation 1994 IEEE (1994) pp. 2802–2807.Google Scholar
6.Kanayama, Y. and Hartman, B., “Smooth local-path planning for autonomous vehicles,” Int. J. Robot. Res. 16 (3), 263 (1997).Google Scholar
7.On, S. and Yazici, A., “A Comparative Study of Smooth Path Planning for a Mobile Robot Considering Kinematic Constraints,” Proceedings of the 2011 International Symposium on Innovations in Intelligent Systems and Applications (INISTA) (Jun. 2011) 565–569.Google Scholar
8.Connors, J. and Elkaim, G., “Analysis of a spline based, obstacle avoiding path planning algorithm,” Piscataway, NJ 08855-1331, United States (2007) pp. 2565–2569.Google Scholar
9.Lapierre, L., Soetanto, D., and Pascoal, A., “Nonsingular path following control of a unicycle in the presence of parametric modelling uncertainties,” Int. J. Robust Nonlinear Control 16 (10), 485–503 (2006). [Online]. Available: http://dx.doi.org/10.1002/rnc.1075Google Scholar
10.Kim, Y. and Minor, M., “Path manifold-based kinematic control of wheeled mobile robots considering physical constraints,” Int. J. Robot. Res. 26 (9), 955 (2007).Google Scholar
11.Arakawa, A., Hiyama, M., Emura, T. and Kagami, Y., “Trajectory Generation for Wheeled Mobile Robot Based on Landmarks,” Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, Vol. 2 (1995).Google Scholar
12.Boucher, P. and Cohen, P., “A Smoothness-Preserving Waypoints follower for Mobile Platforms,” Proceedings of the 2010 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (2010).Google Scholar
13.Aguiar, A. and Pascoal, A., “Dynamic positioning and way-point tracking of underactuated auvs in the presence of ocean currents,” Int. J. Control 80 (7), 109261108 (2007).Google Scholar
14.Antonelli, G., Chiaverini, S. and Fusco, G., “A fuzzy-logic-based approach for mobile robot path tracking,” IEEE Trans. Fuzzy Syst. 15 (2), 211–221 (2007).Google Scholar
15.Gulati, S., Jhurani, C., Kuipers, B. and Longoria, R., “A Framework for Planning Comfortable and Customizable Motion of an Assistive Mobile Robot,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009. IROS 2009, IEEE (2009) pp. 4253–4260.Google Scholar
16.Conn, A. R., Gould, N. I. and Toint, P. L., Trust Region Methods, vol. 1 (Siam, 2000).Google Scholar
17.Bourmistrova, A., Simic, M., Hoseinnezhad, R. and Jazar, R. N., “Autodriver algorithm,” J. Systemics, Cybern. Inform. 9 (1) (2011).Google Scholar
18.Koh, K. C. and Cho, H. S., “A smooth path tracking algorithm for wheeled mobile robots with dynamic constraints,” J. Intell. Robot. Syst. 24 (4), 367–385 (1999).CrossRefGoogle Scholar
19.Macek, K., Petrovic, I. and Siegwart, R., “A Control Method for Stable and Smooth Path following of Mobile Robots,” Proceedings of the European Conference on Mobile Robots (2005).Google Scholar
20.Katić, D., Ćosić, A., Šušić, M.; and Graovac, S., “An Integrated Approach for Intelligent Path Planning and Control of Mobile Robot in Structured Environment,” In: New Trends in Medical and Service Robots (Springer, 2014) pp. 161–176.CrossRefGoogle Scholar
21.Guarino, C.Bianco, Lo, “Minimum-jerk velocity planning for mobile robot applications,” (2013).Google Scholar
22.Belkhouche, F. and Bendjilali, B., “Reactive path planning for 3-d autonomous vehicles,” IEEE Trans. Control Syst. Technol. 20 (1), 249–256 (2012).Google Scholar
23.Morin, P. and Samson, C., “Motion Control of Wheeled Mobile Robots,” In: Springer Handbook of Robotics (2008) pp. 799–826.Google Scholar
24.Zalzal, V., Gava, R., Kelouwani, S. and Cohen, P., “Acropolis: A fast protoyping robotic application,” Int. J. Adv. Robot. Syst. 6 (1) (2009).Google Scholar
25.Boucher, P., Kelouwani, S. and Cohen, P., “Mobile Platform Self-Localization in Partially Unknown Dynamic Environments,” Proceedings of the ICINCO 2009-6th International Conference on Informatics in Control, Automation and Robotics (2009).Google Scholar