As artificial intelligence continues to drive the development of autonomous vehicles, the use of practical, real-time deep learning algorithms has also been on the rise. CAVS is leading the way in developing deep learning technology, with teams of faculty, research engineers and students using neural networks to identify objects from camera images. While working with industry leaders like NVIDIA, CAVS is specifically exploring deep learning for use in rural environments.
Training neural networks requires extensive data sets and human interaction to manually classify objects. By using simulation, this cycle time can be reduced. This is a critical feature for off-road applications, since there is more variety in natural obstacles, like trees, than in man-made objects.