Laboratory for Intelligent & Safe Automobiles

Computer Vision and Robotics Research Laboratory

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The Laboratory for Intelligent and Safe Automobiles (LISA) is a multidisciplinary effort to explore innovative approaches to making future automobiles safer and "intelligent". Our research considers issues in sensing, analysis, modeling, and prediction of parameters associated with drivers, occupants, vehicle dynamics and vehicle surroundings as well as transportation infrastructures. This is accomplished by research in computer vision and intelligent systems with synergistic contributions from cognitive sciences, psychology and decision theory. The LISA team has a broad theoretical as well as experimental research agenda. Several unique and powerful test-beds, including vehicles, real-time machine vision systems, multimodal interfaces, and driving simulators, exist in our laboratory. Research is pursued with the close engagement of collaborators from industry and government agencies.

The Computer Vision & Robotics Research (CVRR) Laboratory at the University of California, San Diego offers a unique and stimulating environment to graduate students, faculty members, and visiting scholars/collaborators to pursue a wide spectrum of research studies in the Sensor-Based Intelligent Systems area. The major thrust of our research is on developing a clear understanding of the computational and engineering-related issues underlying the perception, planning, and control mechanisms for completely autonomous or semi-autonomous operation of integrated systems. The core group of researchers in the laboratory include graduate students, research faculty members, and adjunct faculty members. The academic program of the laboratory is primarily associated with the Electrical and Computer Engineering Department. Ties with Mechanical Engineering, Computer Science, Cognitive Science, Bioengineering, Structural Engineering, Scripps Institution of Oceanography, San Diego Supercomputing Center, and Salk Institute (Neuroscience) exist for interdisciplinary projects.

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