SBIR Phase I: Energy-Efficient Perception for Autonomous Road Vehicles

Deepscale, Inc, San Jose CA

Investigators

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to allow consumers to buy vehicles enhanced by Advanced Driver Assistance Systems (ADAS) that are more robust and more accurate. Advanced Driver Assistance Systems in general, and fully autonomous vehicles in particular, promise a number of advantages, such as: (1) reducing the number of traffic fatalities in the US and abroad, (2) enabling humans to spend less time driving and more time on other activities, and (3) reducing fossil-fuel emissions. Practical implementations of Advanced Driver Assistance Systems require a few key elements: sensors, perception systems, motion planning systems, and control/actuation systems. Based on extensive discussions with key individuals at automakers and automotive suppliers, developing robust and accurate perception systems is the biggest obstacle toward developing mass-producible autonomous road vehicles. This Small Business Innovation Research (SBIR) Phase I project will create perception systems that utilize the rapidly evolving technologies of deep learning for computer vision. Specifically, the company will utilize deep learning to provide perceptual systems that are: 1) more robust in the presence of diverse and rapidly evolving sensor configurations; 2) more accurate due to the early fusion of sensor data; and 3) more accurate due to the application of state-of-the-art deep learning algorithms for computer vision. The company is already engaged in developing partnerships with automotive OEMs and semiconductor suppliers that will enable it to deliver proofs-of-concept of its unique approach.