The Golem Group / UCLA Autonomous Ground Vehicle in the DARPA Grand Challenge

This paper presents the Golem Group/UCLA entry to the 2005 DARPA Grand Challenge competition. We describe the main design principles behind the development of Golem 2, the race vehicle. The subsystems devoted to obstacle detection, avoidance, and state estimation are discussed in more detail. An overview of the vehicle performance in the field is provided, including successes together with an analysis of the reasons leading to failures.

[1]  R. E. Kalman,et al.  A New Approach to Linear Filtering and Prediction Problems , 2002 .

[2]  Laurent Moll,et al.  Real time correlation-based stereo: algorithm, implementations and applications , 1993 .

[3]  Amnon Shashua,et al.  Off-road Path Following using Region Classification and Geometric Projection Constraints , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[4]  Christopher Rasmussen,et al.  Combining laser range, color, and texture cues for autonomous road following , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[5]  Jonathan A. Bornstein Army ground robotics research program , 2002, SPIE Defense + Commercial Sensing.

[6]  Robert M. Rogers,et al.  Applied Mathematics in Integrated Navigation Systems , 2000 .

[7]  H. Hattori,et al.  Dense stereo matching in restricted disparity space , 2005, IEEE Proceedings. Intelligent Vehicles Symposium, 2005..

[8]  Emilio Frazzoli,et al.  Real-Time Motion Planning for Agile Autonomous Vehicles , 2000 .

[9]  Lydia E. Kavraki,et al.  Probabilistic roadmaps for path planning in high-dimensional configuration spaces , 1996, IEEE Trans. Robotics Autom..

[10]  Ernst D. Dickmanns,et al.  Dynamic Vision-Based Intelligence , 2004, AI Mag..

[11]  R. E. Kalman,et al.  New Results in Linear Filtering and Prediction Theory , 1961 .

[12]  Greg Welch,et al.  An Introduction to Kalman Filter , 1995, SIGGRAPH 2001.

[13]  Ernst D. Dickmanns,et al.  Vehicles Capable of Dynamic Vision , 1997, IJCAI.

[14]  K. Maeda,et al.  Visconti: multi-VLIW image recognition processor based on configurable processor [obstacle detection applications] , 2003, Proceedings of the IEEE 2003 Custom Integrated Circuits Conference, 2003..

[15]  Neill W Campbell,et al.  IEEE International Conference on Computer Vision and Pattern Recognition , 2008 .

[16]  Karl Murphy,et al.  Driving autonomously off-road up to 35 km/h , 2000, Proceedings of the IEEE Intelligent Vehicles Symposium 2000 (Cat. No.00TH8511).

[17]  Yoav Freund,et al.  Experiments with a New Boosting Algorithm , 1996, ICML.

[18]  S. LaValle Rapidly-exploring random trees : a new tool for path planning , 1998 .

[19]  Marilyn N. Abrams,et al.  An Intelligent World Model for Autonomous Off-Road Driving , 2001 .

[20]  Arthur Gelb,et al.  Applied Optimal Estimation , 1974 .