Vanhoutte Erik, Mafrica Stefano, Ruffier Franck, Bootsma Reinoud J, Serres Julien
Aix-Marseille Université, CNRS, ISM UMR7287, 13288 Marseille Cedex 09, France.
Sensors (Basel). 2017 Mar 11;17(3):571. doi: 10.3390/s17030571.
For use in autonomous micro air vehicles, visual sensors must not only be small, lightweight and insensitive to light variations; on-board autopilots also require fast and accurate optical flow measurements over a wide range of speeds. Using an auto-adaptive bio-inspired Michaelis-Menten Auto-adaptive Pixel (M 2 APix) analog silicon retina, in this article, we present comparative tests of two optical flow calculation algorithms operating under lighting conditions from 6 × 10 - 7 to 1 . 6 × 10 - 2 W·cm - 2 (i.e., from 0.2 to 12,000 lux for human vision). Contrast "time of travel" between two adjacent light-sensitive pixels was determined by thresholding and by cross-correlating the two pixels' signals, with measurement frequency up to 5 kHz for the 10 local motion sensors of the M 2 APix sensor. While both algorithms adequately measured optical flow between 25 ∘ /s and 1000 ∘ /s, thresholding gave rise to a lower precision, especially due to a larger number of outliers at higher speeds. Compared to thresholding, cross-correlation also allowed for a higher rate of optical flow output (99 Hz and 1195 Hz, respectively) but required substantially more computational resources.
为了用于自主微型飞行器，视觉传感器不仅必须体积小、重量轻且对光照变化不敏感；机载自动驾驶仪还需要在很宽的速度范围内进行快速且精确的光流测量。在本文中，我们使用一种自适应的受生物启发的米氏自适应像素（M²APix）模拟硅视网膜，对两种在6×10⁻⁷至1.6×10⁻²W·cm⁻²的光照条件下（即对于人类视觉而言，从0.2勒克斯到12000勒克斯）运行的光流计算算法进行了对比测试。通过对两个相邻光敏像素之间的信号进行阈值处理和互相关来确定“传播时间”对比度，对于M²APix传感器的10个局部运动传感器，测量频率高达5千赫兹。虽然两种算法在25°/秒至1000°/秒之间都能充分测量光流，但阈值处理导致的精度较低，特别是在较高速度下存在大量异常值。与阈值处理相比，互相关还能实现更高的光流输出速率（分别为99赫兹和1195赫兹），但需要大量更多的计算资源。
