Motion Planning in Urban Environments: Part II

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Lab Papers (GRASP)
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mobile robots
path planning
position control
road vehicles
Urban Challenge
anomalous on-road scenarios
autonomous SUV
autonomous vehicle navigation
higher-level planners
model-predictive trajectory generation algorithm
motion planning
unstructured planning component
urban environments
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Ferguson, Dave
Howard, Thomas M

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 ldquoBossrdquo, an autonomous SUV that has driven itself over 3000 kilometers and competed in, and won, the Urban Challenge.

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Copyright 2008 IEEE. Reprinted from: Ferguson, D.; Howard, T.M.; Likhachev, M., "Motion planning in urban environments: Part II," Intelligent Robots and Systems, 2008. IROS 2008. IEEE/RSJ International Conference on , vol., no., pp.1070-1076, 22-26 Sept. 2008 URL: This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
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