Motion planning in urban environments: Part II

— 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.

• Type: Conference
• Year: 2008
• Where: IROS
• Authors: Dave Ferguson, Thomas M. Howard, Maxim Likhachev
• Keywords: IROS 2008, Large Unstructured Lots, Motion Planning, Motion Planning Framework, Robotics