Real-Time Motion Planning With Applications to Autonomous Urban Driving
Name
Frazzoli-2009-Real-Time Motion Planning With Applications to Autonomous Urban Driving.pdf
Size
1.74 MB
Format
Adobe PDF
Checksum (MD5)
957e824ae1115c92e9e63f8198eb846f
Author(s)
Kuwata, Yoshiaki
Teo, Justin
Fiore, Gaston A.
Karaman, Sertac
Frazzoli, Emilio
How, Jonathan P.
Date Issued
August 2009
Journal
IEEE Transactions on Control Systems Technology
Publisher
Institute of Electrical and Electronics Engineers
Citation
Kuwata, Y. et al. “Real-Time Motion Planning With Applications to Autonomous Urban Driving.” IEEE Transactions on Control Systems Technology 17.5 (2009) : 1105-1118. © 2011 IEEE
Version
Final published version
Abstract
This paper describes a real-time motion planning algorithm, based on the rapidly-exploring random tree (RRT) approach, applicable to autonomous vehicles operating in an urban environment. Extensions to the standard RRT are predominantly motivated by: 1) the need to generate dynamically feasible plans in real-time; 2) safety requirements; 3) the constraints dictated by the uncertain operating (urban) environment. The primary novelty is in the use of closed-loop prediction in the framework of RRT. The proposed algorithm was at the core of the planning and control software for Team MIT's entry for the 2007 DARPA Urban Challenge, where the vehicle demonstrated the ability to complete a 60 mile simulated military supply mission, while safely interacting with other autonomous and human driven vehicles.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/tcst.2008.2012116
