Lab Papers (GRASP)

Document Type

Conference Paper

Date of this Version

9-22-2008

Comments

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: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4651124&isnumber=4650570

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

Keywords

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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Date Posted: 01 October 2009