On-board real-time optic-flow for miniature event-based vision sensors

This paper presents a novel, drastically simplified method to compute optic flow on a miniaturized embedded vision system, suitable on-board of miniaturized indoor flying robots. Estimating optic flow is a common technique for robotic motion stabilization in systems without ground contact, such as unmanned aerial vehicles (UAVs). Because of high computing power requirements to process video camera data, most optic flow algorithms are implemented off-board on PCs or on dedicated hardware, connected through tethered or wireless links. Here, in contrast, we present a miniaturized stand-alone embedded system that utilizes a novel neuro-biologically inspired event-based vision sensor (DVS) to extract optic flow on-board in real-time with minimal computing requirements. The DVS provides asynchronous events that resemble temporal contrast changes at individual pixel level, instead of full image frames at regular time intervals. Such a representation provides high temporal resolution while simultaneously reducing the amount of data to be processed. We present a simple algorithm to extract optic flow information from such event-based vision data, which is sufficiently efficient in terms of data storage and processing power to be executed on an embedded 32bit ARM7 microcontroller in real-time. The developed stand-alone system is small, lightweight and energy efficient, and is ready to serve as sensor for ego motion estimates based on optic flow in autonomous UAVs.