An efficient neuromorphic analog network for motion estimation

Abstract

Optical flow estimation is a critical mechanism for autonomous mobile robots as it provides a range of useful information. As real-time processing is mandatory in this case, an efficient solution is the use of specific very large scale integration (VLSI) analog circuits. This paper presents a simple and regular architecture based on analog circuits, which implements the entire processing line from photoreceptor to accurate and reliable optical flow estimation. The algorithm we propose, is an energybased method using a novel wideband velocity-tuned filter which proves to be an efficient alternative to the well-known Gabor filters. Our approach shows that a high level of accuracy can be obtained from a small number of loosely tuned filters. It exhibits similar or improved performance to that of other existing algorithms, but with a much lower complexity. © 1999 IEEE.