Our motivation is a variety of applications in need of visual intelligence. We will refer to visual intelligence as the ability to make quantitative and qualitative decisions based on only the intensity information provided by a single or set of visual images. We limit our discussion to visual intensity images because we are concerned with emulating the biological system at least in a general manner. Further, the decisions may be formulated from off-line training and knowledge gathering processes. A growing number of problems in many different disciplines are calling for machines and computers to extend to the next level of intelligence.
Many manufacturing processes call for visual inspection of work done by machines.
In fact, there are many machine vision applications in manufacturing that rely on visual inspections by computers to perform a task. There are growing number of tasks in medical, military, space exploration, and environmental fields that are in need of machines that have the ability to autonomously navigate unknown environments with little or no help from human operators. Most researchers agree that the best models are based on human models and the use of vision to navigate unknown environments. Our research is centered on designing an agile, inexpensive vehicle that primarily uses vision to navigate and recognize objects. The machine will integrate classical and experimental algorithms together to perform tasks arranged in a knowledge database.