Motion planning in urban environments: Part I

— 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 I of a two-part paper, we describe the underlying trajectory generator and the onroad planning component of this system. 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.

• Type: Conference
• Year: 2008
• Where: IROS
• Authors: Dave Ferguson, Thomas M. Howard, Maxim Likhachev
• Keywords: IROS 2008, Model-predictive Trajectory Generation, Motion Planning, Motion Planning Framework, Robotics