Abstract
In this chapter, a rather straightforward procedure is presented to obtain navigation algorithms for a broad class of vehicle models, based on an adapted version of the passivity-based nonlinear MPC examined in [1]. The proposed PB/MPC approach for navigation planning can be seen as a generalization of the well-known DWA developed in [2–4]. Similar to the navigation based on the MPC/CLF [5], the PB/MPC optimization setup guarantees the task completion, which means the vehicle is being able to reach the goal position. However, whereas in the MPC/CLF navigation framework a control action that decreases the Lyapunov function has to be found in advance, which is rather difficult if not impossible for complex vehicle models, the PB/MPC navigation framework gives directly the control action as a consequence of the passivity-based control. Therefore, the PB/MPC can be easily adapted to a variety of vehicle and terrain models providing a straightforward procedure for the navigation of wide range of vehicles.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
T. Raff, C. Ebenbauer, F. Allgoewer, Nonlinear Model Predictive Control: Passivity-based Approach (Springer, Berlin, 2007)
R. Simmons, The curvature-velocity method for local obstacle avoidance, in Proceedings of the IEEE International Conference on Robotics and Automation, 1996, pp. 3375–3382
D. Fox, W. Burgard, S. Thrun, The dynamic window approach to collision avoidance. IEEE Robot. Autom. Mag. 4, 23–33 (1997)
O. Brock, O. Khatib, High-speed navigation using the global dynamic window approach, in Proceedings of the IEEE International Conference on Robotics and Automation, vol. 1. 1999, pp. 341–346
P. Oegren, N.E. Leonard, A convergent dynamic window approach to obstacle avoidance. IEEE Trans. Robot. 21(2), 188–195 (2005)
A. Tahirovic, G. Magnani, P. Rocco, Mobile robot navigation using passivity-based MPC, in Proceedings of the IEEE/ASME International Conference on Advanced Intelligent, Mechatronics, July 2010, pp. 248–488
A. Tahirovic, G. Magnani, General framework for mobile robot navigation using passivity-based MPC. IEEE Trans. Autom. Control 56(1), (2011)
A. Tahirovic, G. Magnani, Passivity-based model predictive control for mobile robot navigation planning in rough terrains, in Proceedings of the 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, Oct 2010
J. Latombe, Robot Motion Planning (Kluwer, Boston, 1991)
J. Barraquand, B. Langlois, J. Latombe, Numerical potential field techniques for robot path planning. IEEE Trans. Syst. Man Cybern. 22(2), 224–241 (1992)
E. Rimon, D.E. Koditschek, Exact robot navigation using artificial potential fields. IEEE Trans. Robot. Autom. 8, 501–518 (Oct. 1992)
O. Khatib, Real-time obstacle avoidance for manipulators and mobile robots. Int. J. Robot. Res. 5(1), 90–98 (1986)
T.M. Howard, A. Kelly, Optimal rough terrain trajectory generation for wheeled mobile robots. Int. J. Robot. Res. 26(2), 141–166 (2007)
K. Iagnemma, S. Shimoda, Z. Shiller, Near-optimal navigation of high speed mobile robots, in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 2. 2008, pp. 22—26
Z. Shiller, Y.-R. Gwo, Dynamic motion planning of autonomous vehicles. IEEE Trans. Robot. Autom. 7(2), 241–249 (1991)
Z. Shiller, Obstacle traversal for space exploration, in Proceedings of the IEEE International Conference on Robotics and Automation, 2000
S. Singh, R. Simmons, T. Smith, A. Stentz, V. Verma, A. Yahja, K. Schwehr, Recent progress in local and global traversability for planetary rovers, in Proceedings of the IEEE International Conference on Robotics and Automation, 2000
H. Seraji, Fuzzy traversability index: a new concept for terrain-based navigation. J. Robot. Syst. 17(2), 75–91 (2000)
A. Howard, H. Seraji, Vision-based terrain characterization and traversability assessment. J. Robot. Syst. 18(10), 577–587 (2001)
K. Iagnemma, S. Dubowsky, Mobile Robots in Rough Terrain: Estimation, Motion Planning and Control with Application to Planetary Rovers (Springer, Berlin, 2004)
A. Tahirovic, G. Magnani, A roughness-based RRT for mobile robot navigation planning, in Proceedings of the 18th IFAC World Congress, 2011, pp. 5944–5949
A. Tahirovic, G. Magnani, Y. Kuwata, An approximate of the cost-to-go map on rough terrains, in Proceedings of the IEEE International Conference on Mechatronics, 2013
A. Stentz, The focussed D* algorithm for real-time replanning, in Proceedings of the International Joint Conference on Artificial Intelligence, pp. 1652–1659, 1995
S. Koenig, M. Likhachev, Fast replanning for navigation in unknown terrain. IEEE Trans. Robot. 21(3), 354–363 (2005)
A. Lacaze, Y. Moscovitz, N. Declaris, K. Murphy, Path planning for autonomous vehicle driving over rough terrain, in Proceedings of the IEEE International Symposium on Intelligent Control (Gaithersburg, MD, 1998), pp. 50–55
M. Pivtoraiko, R.A. Knepper, A. Kelly, Differentially constrained mobile robot motion planning in state lattices. J. Field Robot. 26(3), 308–333 (2009)
T.M. Howard, C.J. Green, A. Kelly, D. Ferguson, State space sampling of feasible motions for high-performance mobile robot navigation in complex environments. J. Field Robot. 25(10), 325–345 (2008)
Y. Yoon, J. Shin, H.J. Kim, Y. Park, S. Sastry, Model-predictive active steering and obstacle avoidance for autonomous ground vehicles. Control Eng. Pract. 17(7), 741–750 (2009)
H.K. Khalil, Nonlinear Systems, 3rd edn. (Prentice Hall, Upper Saddle River, 2002)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2013 The Author(s)
About this chapter
Cite this chapter
Tahirovic, A., Magnani, G. (2013). PB/MPC Navigation Planner. In: Passivity-Based Model Predictive Control for Mobile Vehicle Motion Planning. SpringerBriefs in Electrical and Computer Engineering(). Springer, London. https://doi.org/10.1007/978-1-4471-5049-7_2
Download citation
DOI: https://doi.org/10.1007/978-1-4471-5049-7_2
Published:
Publisher Name: Springer, London
Print ISBN: 978-1-4471-5048-0
Online ISBN: 978-1-4471-5049-7
eBook Packages: EngineeringEngineering (R0)