A Stereovision Method for Obstacle Detection and Tracking in Non-Flat Urban Environments

Obstacle detection is an essential capability for the safe guidance of autonomous vehicles, especially in urban environments. This paper presents an efficient method to integrate spatial and temporal constraints for detecting and tracking obstacles in urban environments. In order to enhance the reliability of the obstacle detection task, we do not consider the urban roads as rigid planes, but as quasi-planes, whose normal vectors have orientation constraints. Under this flexible road model, we propose a fast, robust stereovision based obstacle detection method. A watershed transformation is employed for obstacle segmentation in dense traffic conditions, even with partial occlusions, in urban environments. Finally a UKF (Unscented Kalman filter) is applied to estimate the obstacles parameters under a nonlinear observation model. To avoid the difficulty of the computation in metric space, the whole detection process is performed in the disparity image. Various experimental results are presented, showing the advantages of this method.Qian Yu received the B.E. degree in Computer Science from Tsinghua University, Beijing, China, in 2001, and the Master degree in Computer Science also from Tsinghua University in 2004, working at the Artificial Intelligence Laboratory. From October 2002 to April 2003, he was a visiting student at the Institute of System and Robotics (ISR), University of Coimbra, Portugal. His current research interests are in computer vision and robotics.Helder Araujo is currently Associate Professor in the Department of Electrical and Computer Engineering, University of Coimbra, Portugal. He is co-founder of the Portuguese Institute for Systems and Robotics (ISR), where he is now a Researcher and Vice-Director of the Coimbra pole. His primary research interests are in computer vision and mobile robotics.Hong Wang received his Ph.D. degree from the Department of Computer Science and Technology, Tsinghua University in 1993. He is currently an associate professor at Department of Computer Science and Technology, Tsinghua University. He worked as a visiting researcher at the Department of Intelligent Assistant Driving, Daimler-Benz Research, Stuttgart, Germany, from August 1996 to August 1997. His main research interests include Artificial Intelligence, Mobile Robotics, Vision Navigation, Multi-sensor Data Fusion. He has published over 40 papers in international conference and journals. He is a member of Special Committee of Machine Perception and Virtual Reality of the Chinese Association of Artificial Intelligence and a member of Scientific Committee of the Olympiad in Informatics of the Chinese Computer Association. He has served as an Associated Director of the Central Laboratory of the State Key Laboratory of Intelligent Technology and Systems, Tsinghua University.