Path diversity is only part of the problem
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Artificial Life and Robotics
The University of Pennsylvania MAGIC 2010 multi-robot unmanned vehicle system
Journal of Field Robotics
Invariants for homology classes with application to optimal search and planning problem in robotics
Annals of Mathematics and Artificial Intelligence
| Hi-index | 0.00 |
We present the motion planning framework for an autonomous vehicle navigating through urban environments. Such environments present a number of motion planning challenges, including ultrareliability, high-speed operation, complex intervehicle 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 the first part of this article, we describe the underlying trajectory generator and the on-road planning component of this system. We then describe the unstructured planning component of this system used for navigating through parking lots and recovering from anomalous on-road scenarios. Throughout, we provide examples and results from “Boss” an autonomous sport utility vehicle that has driven itself over 3,000 km and competed in, and won, the DARPA Urban Challenge. © 2008 Wiley Periodicals, Inc.