Mark Campbell

Publications (2)4.49 Total impact

• Source

  Available from: psu.edu

  Article: The MIT–Cornell collision and why it happened

  Luke Fletcher, Seth Teller, Edwin Olson, David Moore, Yoshiaki Kuwata, Jonathan How, John Leonard, Isaac Miller, Mark Campbell, Dan Huttenlocher, Aaron Nathan, Frank-Robert Kline
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  ABSTRACT: Midway through the 2007 DARPA Urban Challenge, MIT's robot “Talos” and Team Cornell's robot “Skynet” collided in a low-speed accident. This accident was one of the first collisions between full-sized autonomous road vehicles. Fortunately, both vehicles went on to finish the race and the collision was thoroughly documented in the vehicle logs. This collaborative study between MIT and Cornell traces the confluence of events that preceded the collision and examines its root causes. A summary of robot–robot interactions during the race is presented. The logs from both vehicles are used to show the gulf between robot and human-driver behavior at close vehicle proximities. Contributing factors are shown to be (1) difficulties in sensor data association leading to an inability to detect slow-moving vehicles and phantom obstacles, (2) failure to anticipate vehicle intent, and (3) an overemphasis on lane constraints versus vehicle proximity in motion planning. Finally, we discuss approaches that could address these issues in future systems, such as intervehicle communication, vehicle detection, and prioritized motion planning. © 2008 Wiley Periodicals, Inc.
  Journal of Field Robotics 09/2008; 25(10):775 - 807. · 2.24 Impact Factor
• Source

  Available from: usyd.edu.au

  Article: Team Cornell's Skynet: Robust perception and planning in an urban environment

  Isaac Miller, Mark Campbell, Dan Huttenlocher, Frank-Robert Kline, Aaron Nathan, Sergei Lupashin, Jason Catlin, Brian Schimpf, Pete Moran, Noah Zych, Ephrahim Garcia, Mike Kurdziel, Hikaru Fujishima
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  ABSTRACT: Team Cornell's Skynet is an autonomous Chevrolet Tahoe built to compete in the 2007 DARPA Urban Challenge. Skynet consists of many unique subsystems, including actuation and power distribution designed in-house, a tightly coupled attitude and position estimator, a novel obstacle detection and tracking system, a system for augmenting position estimates with vision-based detection algorithms, a path planner based on physical vehicle constraints and a nonlinear optimization routine, and a state-based reasoning agent for obeying traffic laws. This paper describes these subsystems in detail before discussing the system's overall performance in the National Qualifying Event and the Urban Challenge. Logged data recorded at the National Qualifying Event and the Urban Challenge are presented and used to analyze the system's performance. © 2008 Wiley Periodicals, Inc.
  Journal of Field Robotics 07/2008; 25(8):493 - 527. · 2.24 Impact Factor