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Carnegie Mellon Robotics Institute

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Abstract

We present the motion planning framework for an autonomous vehicle navigating through urban environments. Such environments present a number of motion planning challenges, including ultra-reliability, high-speed operation, complex inter-vehicle interaction, parking in large unstructured lots, and constrained maneuvers. Our approach combines a model-predictive trajectory generation algorithm for computing dynamically-feasible actions with two higher-level planners for generating long range plans in both on-road and unstructured areas of the environment. In this Part II of a two-part paper, we describe the unstructured planning component of this system used for navigating through parking lots and recovering from anomalous on-road scenarios. We provide examples and results from "Boss", an autonomous SUV that has driven itself over 3000 kilometers and competed in, and won, the Urban Challenge.

Notes

Associated Center(s) / Consortia: National Robotics Engineering Center and Field Robotics Center

Associated Project(s): Urban Challenge and Tartan Racing

Number of pages: 7

Text Reference

David Ferguson, Thomas Howard, and Maxim Likhachev, "Motion Planning in Urban Environments: Part II," Proceedings of the IEEE/RSJ 2008 International Conference on Intelligent Robots and Systems, September, 2008.

BibTeX Reference

@inproceedings{Ferguson_2008_6166,
   author = "David Ferguson and Thomas Howard and Maxim Likhachev",
   title = "Motion Planning in Urban Environments: Part II",
   booktitle = "Proceedings of the IEEE/RSJ 2008 International Conference on Intelligent Robots and Systems",
   month = "September",
   year = "2008",
}

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