Abstract
As mobile robots venture into more difficult environments, more complex state-space paths are required to move safely and efficiently. The difference between mission success and failure can be determined by a mobile robots capacity to effectively navigate such paths in the presence of disturbances. This paper describes a technique for mobile robot model predictive control that utilizes the structure of a regionalmotion plan to effectively search the local continuum for an improved solution. The contribution, a receding horizon model-predictive control (RHMPC) technique, specifically addresses the problem of path following and obstacle avoidance through geometric singularities and discontinuities such as cusps, turn-in-place, and multi-point turn maneuvers in environments where terrain shape and vehicle mobility effects are non-negligible. The technique is formulated as an optimal controller that utilizes a model-predictive trajectory generator to relax parameterized control inputs initialized from a regional motion planner to navigate safely through the environment. Experimental results are presented for a six-wheeled skid-steered field robot in natural terrain.
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References
Amidi, O.: Integrated mobile robot control. Technical Report CMU-RI-TR-90-17, Carnegie Mellon, Pittsburgh (1990)
Besiadecki, J.J., Leger, P.C., Maimone, M.W.: Tradeoffs between directed and autonomous driving on the Mars Exploration Rovers. International Journal of Robotics Research 26(91), 91–104 (2007)
Bonnafous, D., Lacroix, S., Siméon, T.: Motion generation for a rover on rough terrains. In: Proceedings of the 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems, October 2001, vol. 2, pp. 784–789 (2001)
Coulter, R.C.: Implementation of the pure pursuit path tracking algorithm. Technical Report CMU-RI-TR-92-01, Carnegie Mellon, Pittsburgh (1992)
Howard, T.M., Kelly, A.: Optimal rough terrain trajectory generation for wheeled mobile robots. International Journal of Robotics Research 26(2), 141–166 (2007)
Kelly, A., Stentz, T.: Rough terrain autonomous mobility - Part 2: An active vision and predictive control approach
Kuwata, Y., Fiore, A., Teo, J., Frazzoli, E., How, J.P.: Motion planning for urban driving using RRT. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, September 2008, pp. 1681–1686 (2008)
Lacze, A., Moscovitz, Y., DeClaris, N., Murphy, K.: Path planning for autonomous vehicles driving over rough terrain. In: Proceedings of the 1998 IEEE ISIC/CIRA/ISAS Joint Conference, pp. 50–55 (September 1998)
Lapierre, L., Zapata, R., Lepinay, P.: Combined path-following and obstacle avoidance control of a wheeled robot. International Journal of Robotics Research 26(4), 361–375 (2007)
Pivtoraiko, M., Knepper, R., Kelly, A.: Optimal, smooth, nonholonomic mobile robot motion planning in state lattices. Technical Report CMU-RI-TR-07-15, Carnegie Mellon, Pittsburgh (2007)
Simmons, R., Krotkov, E., Chrisman, L., Cozman, F., Goodwin, R., Hebert, M., Katragadda, L., Koenig, S., Krishnaswamy, G., Shinoda, Y., Whittaker, W.L., Klarer, P.: Experience with rover navigation for lunar-like terrains. In: Proceedings of the 1995 IEEE Conference on Intelligent Robots and Systems, August 1995, vol. 1, pp. 441–446 (1995)
Thrun, S., Montemerlo, M., Dahlkamp, H., Stavens, D., Aron, A., Diebel, J., Fong, P., Gale, J., Halpenny, M., Goffmann, G., Lau, K., Oakley, C., Palatucci, M., Pratt, V., Stang, P.: Stanley: The robot that won the DARPA Grand Challenge. Journal of Field Robotics 23(9), 661–692 (2006)
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Howard, T.M., Green, C.J., Kelly, A. (2010). Receding Horizon Model-Predictive Control for Mobile Robot Navigation of Intricate Paths. In: Howard, A., Iagnemma, K., Kelly, A. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 62. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13408-1_7
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DOI: https://doi.org/10.1007/978-3-642-13408-1_7
Publisher Name: Springer, Berlin, Heidelberg
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