Abstract
This paper describes the architecture and implementation of an autonomous passenger vehicle designed to navigate using locally perceived information in preference to potentially inaccurate or incomplete map data. The vehicle architecture was designed to handle the original DARPA Urban Challenge requirements of perceiving and navigating a road network with segments defined by sparse waypoints. The vehicle implementation includes many heterogeneous sensors with significant communications and computation bandwidth to capture and process high-resolution, high-rate sensor data. The output of the comprehensive environmental sensing subsystem is fed into a kino-dynamic motion planning algorithm to generate all vehicle motion. The requirements of driving in lanes, three-point turns, parking, and maneuvering through obstacle fields are all generated with a unified planner. A key aspect of the planner is its use of closed-loop simulation in a Rapidly-exploring Randomized Trees (RRT) algorithm, which can randomly explore the space while efficiently generating smooth trajectories in a dynamic and uncertain environment. The overall system was realized through the creation of a powerful new suite of software tools for message-passing, logging, and visualization. These innovations provide a strong platform for future research in autonomous driving in GPS-denied and highly dynamic environments with poor a priori information.
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
Preview
Unable to display preview. Download preview PDF.
References
Atreya, A.R., Cattle, B.C., Collins, B.M., Essenburg, B., Franken, G.H., Saxe, A.M., Schiffres, S.N., Kornhauser, A.L.: Prospect Eleven: Princeton university’s entry in the 2005 DARPA Grand Challenge. J. Robot. Syst. 23(9), 745–753 (2006)
Bertozzi, M., Broggi, A.: Gold: a parallel real-time stereo vision system for generic obstacle and lane detection. IEEE Transactions on Image Processing 7(1), 62–81 (1998)
Blom, H., Bar-Shalom, Y.: The interacting multiple model algorithm for systems with Markovian switching coefficients. IEEE Transactions on Automatic Control 33(8), 780–783 (1988)
Braid, D., Broggi, A., Schmiedel, G.: The TerraMax autonomous vehicle. J. Robot. Syst. 23(9), 693–708 (2006)
Chen, Q., Ozguner, U.: Intelligent off-road navigation algorithms and strategies of team desert buckeyes in the DARPA Grand Challenge 2005. J. Robot. Syst. 23(9), 729–743 (2006)
Cremean, L.B., Foote, T.B., Gillula, J.H., Hines, G.H., Kogan, D., Kriechbaum, K.L., Lamb, J.C., Leibs, J., Lindzey, L., Rasmussen, C.E., Stewart, A.D., Burdick, J.W., Murray, R.M.: Alice: An information-rich autonomous vehicle for high-speed desert navigation. J. Robot. Syst. 23(9), 777–810 (2006)
DARPA, Darpa urban challenge rules (2007), http://www.darpa.mil/GRANDCHALLENGE/rules.asp
Fischler, M.A., Bolles, R.C.: Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM 24(6), 381–395 (1981)
Frazzoli: Robust Hybrid Control for Autonomous Vehicle Motion Planning. PhD thesis, MIT (2001)
Grabowski, R., Weatherly, R., Bolling, R., Seidel, D., Shadid, M., Jones, A.: MITRE meteor: An off-road autonomous vehicle for DARPA’s grand challenge. J. Robot. Syst. 23(9), 811–835 (2006)
Hart, P.E., Nilsson, N.J., Raphael, B.: A formal basis for the heuristic determination of minimum cost paths. IEEE Trans. Syst. Sci. Cybern. 4(2), 100–107 (1968)
Hartley, R.I., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2001)
Iagnemma, K., Buehler, M.: Special issue on the DARPA Grand Challenge: Editorial. Journal of Field Robotics 23(9), 655–656 (2006)
Kelly, A., Stentz, A.: An approach to rough terrain autonomous mobility. In: International Conference on Mobile Planetary Robots (1997)
LaValle, S.M., Kuffner, J.J.: Randomized kinodynamic planning. International Journal of Robotics Research 20(5), 378–400 (2001)
Leedy, B.M., Putney, J.S., Bauman, C., Cacciola, S., Webster, J.M., Reinholtz, C.F.: Virginia Tech’s twin contenders: A comparative study of reactive and deliberative navigation. J. Robot. Syst. 23(9), 709–727 (2006)
Mason, R., Radford, J., Kumar, D., Walters, R., Fulkerson, B., Jones, E., Caldwell, D., Meltzer, J., Alon, Y., Shashua, A., Hattori, H., Takeda, N., Frazzoli, E., Soatto, S.: The Golem Group / UCLA autonomous ground vehicle in the DARPA Grand Challenge. Journal of Field Robotics 23(8), 527–553 (2006)
Mertz, C., Duggins, D., Gowdy, J., Kozar, J., MacLachlan, R., Steinfeld, A., Suppe, A., Thorpe, C., Wang, C.: Collision Warning and Sensor Data Processing in Urban Areas. In: Proc. 5th international conference on ITS telecommunications, pp. 73–78 (2005)
Newman, P.M.: MOOS - A Mission Oriented Operating Suite. Technical Report OE2003- 07, MIT Department of Ocean Engineering (2003)
Park, S., Deyst, J., How, J.P.: Performance and Lyapunov stability of a nonlinear path following guidance method. Journal of Guidance, Control, and Dynamics (6), 1718–1728 (2007)
Rivest, R.L., Leiserson, C.E.: Introduction to Algorithms. McGraw-Hill, Inc., New York (1990)
Schouwenaars, T., How, J., Feron, E.: Receding Horizon Path Planning with Implicit Safety Guarantees. In: Proceedings of the IEEE American Control Conference. IEEE, Los Alamitos (2004)
Stanford Racing Team: Stanford’s robotic vehicle Junior: Interim report (2007), http://www.darpa.mil/GRANDCHALLENGE/TechPapers/Stanford.pdf
Stein, G., Mano, O., Shashua, A.: A robust method for computing vehicle ego-motion. In: Proc. IEEE Intelligent Vehicles Symposium, pp. 362–368 (2000)
Stein, G., Mano, O., Shashua, A., Ltd, M., Jerusalem, I.: Vision-based ACC with a single camera: bounds on range and range rate accuracy. In: Proc. IEEE Intelligent Vehicles Symposium, pp. 120–125 (2003)
Tartan Racing, Tartan racing: A multi-modal approach to the DARPA urban challenge (2007), http://www.darpa.mil/GRANDCHALLENGE/TechPapers/TartanRacing.pdf
Thorpe, C., Carlson, J., Duggins, D., Gowdy, J., MacLachlan, R., Mertz, C., Suppe, A., Wang, B., Pittsburgh, P.: Safe Robot Driving in Cluttered Environments. In: Robotics Research: The Eleventh International Symposium (2005)
Thrun, S., Montemerlo, M., Dahlkamp, H., Stavens, D., Aron, A., Diebel, J., Fong, P., Gale, J., Halpenny, M., Hoffmann, G., Lau, K., Oakley, C., Palatucci, M., Pratt, V., Stang, P., Strohband, S., Dupont, C., Jendrossek, L.-E., Koelen, C., Markey, C., Rummel, C., van Niekerk, J., Jensen, E., Alessandrini, P., Bradski, G., Davies, B., Ettinger, S., Kaehler, A., Nefian, A., Mahoney, P.: Stanley: The robot that won the DARPA Grand Challenge. J. Robot. Syst. 23(9) (2006)
Trepagnier, P., Nagel, J., Kinney, P., Koutsourgeras, C., Dooner, M.: KAT-5: Robust systems for autonomous vehicle navigation in challenging and unknown terrain. Journal of Field Robotics: Special Issue on the DARPA Grand Challenge 23, 467–508 (2006)
Urmson, C., Anhalt, J., Bartz, D., Clark, M., Galatali, T., Gutierrez, A., Harbaugh, S., Johnston, J., Kato, H., Koon, P., Messner, W., Miller, N., Mosher, A., Peterson, K., Ragusa, C., Ray, D., Smith, B., Snider, J., Spiker, S., Struble, J., Ziglar, J., Whittaker, W.: A robust approach to high-speed navigation for unrehearsed desert terrain. Journal of Field Robotics: Special Issue on the DARPA Grand Challenge 23, 467–508 (2006)
USDOT Federal Highway Administration, Office of Information Management, Highway Statistics 2005. U.S. Government Printing Office, Washington, D. C (2005)
Wang, C.-C.: Simultaneous Localization, Mapping and Moving Object Tracking. PhD thesis, Robotics Institute, Carnegie Mellon University, Pittsburgh, PA (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Leonard, J. et al. (2009). A Perception-Driven Autonomous Urban Vehicle. In: Buehler, M., Iagnemma, K., Singh, S. (eds) The DARPA Urban Challenge. Springer Tracts in Advanced Robotics, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03991-1_5
Download citation
DOI: https://doi.org/10.1007/978-3-642-03991-1_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03990-4
Online ISBN: 978-3-642-03991-1
eBook Packages: EngineeringEngineering (R0)