Little Ben: The Ben Franklin Racing Team's entry in the 2007 DARPA Urban Challenge

  • Authors:
  • Jonathan Bohren;Tully Foote;Jim Keller;Alex Kushleyev;Daniel Lee;Alex Stewart;Paul Vernaza;Jason Derenick;John Spletzer;Brian Satterfield

  • Affiliations:
  • University of Pennsylvania, Philadelphia, Pennsylvania 19104;University of Pennsylvania, Philadelphia, Pennsylvania 19104;University of Pennsylvania, Philadelphia, Pennsylvania 19104;University of Pennsylvania, Philadelphia, Pennsylvania 19104;University of Pennsylvania, Philadelphia, Pennsylvania 19104;University of Pennsylvania, Philadelphia, Pennsylvania 19104;University of Pennsylvania, Philadelphia, Pennsylvania 19104;Computer Science and Engineering, Lehigh University, Bethlehem, Pennsylvania 18015;Computer Science and Engineering, Lehigh University, Bethlehem, Pennsylvania 18015;Lockheed Martin Advanced Technology Laboratories, 3 Executive Campus, Suite 600, Cherry Hill, New Jersey 08002

  • Venue:
  • Journal of Field Robotics - Special Issue on the 2007 DARPA Urban Challenge, Part II
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

This paper describes "Little Ben," an autonomous ground vehicleconstructed by the Ben Franklin Racing Team for the 2007 DARPAUrban Challenge in under a year and for less than $250,000. Thesensing, planning, navigation, and actuation systems for Little Benwere carefully designed to meet the performance demands required ofan autonomous vehicle traveling in an uncertain urban environment.We incorporated an array of a global positioning system(GPS)-inertial navigation system, LIDARs, and stereo cameras toprovide timely information about the surrounding environment at theappropriate ranges. This sensor information was integrated into adynamic map that could robustly handle GPS dropouts and errors. Ourplanning algorithms consisted of a high-level mission planner thatused information from the provided route network definition andmission data files to select routes, whereas the lower levelplanner used the latest dynamic map information to optimize afeasible trajectory to the next waypoint. The vehicle was actuatedby a cost-based controller that efficiently handled steering,throttle, and braking maneuvers in both forward and reversedirections. Our software modules were integrated within ahierarchical architecture that allowed rapid development andtesting of the system performance. The resulting vehicle was one ofsix to successfully finish the Urban Challenge. © 2008 WileyPeriodicals, Inc.