A Multi-Modal, Silicon Retina Technique for Detecting the Presence of Reflective and Transparent Barriers

There is currently great interest in enhancing the ability of aerial robots to navigate indoors. Navigating a building under various lighting and environmental conditions would have application in disaster response, infrastructure inspections, as well as a wide variety of commercial applications. In order to achieve this goal, one common feature of indoor environments that must be addressed is the detection of transparent/reflective barriers. Transparent/reflective barriers as they pertain to structures generally take the form of a window, office divider, or storefront. Human tele-operators of aerial robots in environments such as malls, airports, office buildings, and museums that feature transparent barriers will need some means to enhance their situational awareness so they can recognize the presence of transparent/reflective barriers, distinguish between the two, and have some idea of the distance and pose relative to the transparent/reflective barrier. The ability to detect and localize transparent barriers will also be important for autonomous navigation. The focus of this work is to develop a multi-modal sensing solution that can successfully identify transparent/reflective barriers, distinguish between the two, and provide information on pose and distance to the barrier at time-scales exceeding human response in order to facilitate navigation of indoor spaces. The sensing solution relies on using an imager to measure the differences in the interactions of actively visible light illumination of transparent/reflective barriers. A silicon retina event-driven imager is used in this work to provide a path to obtaining information on transparent/reflective barriers at high speeds, while requiring very little communications bandwidth.