Research Laboratory - Robotics, Computer Vision and Geometric Computing

Humans, as well as many other living species, can easily operate within the physical environment that surrounds them: they acquire visual data, they process it into a model that represents the environment, and they use the model to manipulate and to navigate amid the objects present in the scene. In contrast, equipping a computer with similar capabilities is an extremely difficult task, pursued by many researchers for more than three decades. It encompasses the study of Computer Vision, Image Understanding and Object Recognition, and Automatic Task Planning in Robotics and Manufacturing.

It is the charter of the Robotics, Computer Vision and Geometric Computing Lab to study these topics and to develop methodologies and techniques that endow computers with the aforementioned capabilities. The lab, equipped with mobile robots and with state-of-the-art vision systems, conducts applied research, focusing on automatic motion planning in robotics, on object recognition, understanding and tracking in computer vision, and on the development of robust geometric software library (called CGAL) to support the implementation of the techniques developed in these studies.

The lab is supervised by: Prof. Lior Wolf, Prof. Dan Halperin, Prof. Micha Sharir and Prof. Hezy Yeshurun.