Abstract—This paper presents the TerraMax vision systems used during the 2007 DARPA Urban Challenge. First, a descrip-tion of the different vision systems is provided, focusing on their hardware configuration, calibration method, and tasks. Then, each component is described in detail, focusing on the algorithms and sensor fusion opportunities: obstacle detection, road marking detection, and vehicle detection. The conclusions summarize the lesson learned from the developing of the passive sensing suite and its successful fielding in the Urban Challenge. Index Terms—Autonomous vehicles, data fusion, lane detection, obstacle detection, Urban Challenge, vision systems. I
This dissertation documents the perception algorithm in Cornell University's 2005 DARPA Grand Challe...
The development of autonomous vehicles for urban driving has seen rapid progress in the past 30 year...
Autonomous driving system can assist lo prevent the trafic accidents caused by the negligence of the...
This paper presents the TerraMax vision systems used during the 2007 DARPA Urban Challenge. First, a...
This paper presents the TerraMax autonomous vehicle, which competed in the DARPA Urban Challenge 200...
Operation in urban environments creates unique challenges for research\ud in autonomous ground vehic...
Team Oshkosh, comprised of Oshkosh Corporation, Teledyne Scientific and Imaging Company, VisLab of t...
Abstract—Autonomous driving in off-road environments requires an exceptionally capable sensor system...
The DARPA grand challenges were conducted between 2004 and 2007 and were initiated to foster researc...
Team Oshkosh, composed of Oshkosh Corporation, Teledyne Scientific and Imaging Company, VisLab of th...
The Urban Challenge represents a technological leap beyond the previous Grand Challenges. The challe...
International audienceSince two decades, research programs have studied the concept of ”intelligent ...
In questa tesi saranno presentati i sistemi di percezione frontale a 3 telecamere in posizione asimm...
Digital Object Identifier: 10.1098/rsta.2010.0110The development of autonomous vehicles for urban dr...
The recently growing interest the autonomous vehicle navigation has directed a lot of attention to t...
This dissertation documents the perception algorithm in Cornell University's 2005 DARPA Grand Challe...
The development of autonomous vehicles for urban driving has seen rapid progress in the past 30 year...
Autonomous driving system can assist lo prevent the trafic accidents caused by the negligence of the...
This paper presents the TerraMax vision systems used during the 2007 DARPA Urban Challenge. First, a...
This paper presents the TerraMax autonomous vehicle, which competed in the DARPA Urban Challenge 200...
Operation in urban environments creates unique challenges for research\ud in autonomous ground vehic...
Team Oshkosh, comprised of Oshkosh Corporation, Teledyne Scientific and Imaging Company, VisLab of t...
Abstract—Autonomous driving in off-road environments requires an exceptionally capable sensor system...
The DARPA grand challenges were conducted between 2004 and 2007 and were initiated to foster researc...
Team Oshkosh, composed of Oshkosh Corporation, Teledyne Scientific and Imaging Company, VisLab of th...
The Urban Challenge represents a technological leap beyond the previous Grand Challenges. The challe...
International audienceSince two decades, research programs have studied the concept of ”intelligent ...
In questa tesi saranno presentati i sistemi di percezione frontale a 3 telecamere in posizione asimm...
Digital Object Identifier: 10.1098/rsta.2010.0110The development of autonomous vehicles for urban dr...
The recently growing interest the autonomous vehicle navigation has directed a lot of attention to t...
This dissertation documents the perception algorithm in Cornell University's 2005 DARPA Grand Challe...
The development of autonomous vehicles for urban driving has seen rapid progress in the past 30 year...
Autonomous driving system can assist lo prevent the trafic accidents caused by the negligence of the...