I will present robotics application of insect-inspired autoadaptive sensors (Time-of-travel local motion sensor, CurvACE, M2APix) where motion detection is at a premium, such as collision-free navigation of aerial robots (Octave, Lora, Beerotor robots) and odometry of terrestrial robots (BioCarBot robot).
In most animal species, vision is mediated by compound eyes, which offer lower resolution than vertebrate single-lens eyes, but significantly larger fields of view with negligible distortion and spherical aberration, as well as high temporal resolution in a tiny package.
Compound eyes are ideally suited for fast panoramic motion perception. Engineering a miniature artificial compound eye is challenging because it requires accurate alignment of photoreceptive and optical components on a curved surface.
In this talk, I will detail:
(i) a unique design method for biomimetic compound eyes called CurvACE (1) featuring a panoramic, undistorted field of view in a very thin package. The design consists of three planar layers of separately produced arrays, namely, a microlens array, a neuromorphic photodetector array, and a flexible printed circuit board that are stacked, cut, and curved to produce a mechanically flexible imager. Following this method, we have prototyped and characterized an artificial compound eye bearing a hemispherical field of view with embedded and programmable low-power signal processing, high temporal resolution, and local adaptation to illumination. The prototyped artificial compound eye possesses several characteristics similar to the eye of the fruit fly Drosophila and other arthropod species.
(ii) a novel analog silicon retina featuring auto-adaptive pixels that obey the Michaelis-Menten law The novel pixel, called M2APix (2), which stands for Michaelis-Menten Auto-Adaptive Pixel, can auto-adapt in a 7-decade range and responds appropriately to step changes up to +/-3 decades in size without causing any saturation of the Very Large Scale Integration (VLSI) transistors. Thanks to the intrinsic properties of the Michaelis-Menten equation, the pixel output always remains within a constant limited voltage range. The results presented here show that the M2APix produced a quasi-linear contrast response once it had adapted to the average luminosity.
(iii) application of these bio-inspired sensors where motion detection is at a premium, such as collision-free navigation of aerial robots (3) (i.e. Beerotor) and odometry of terrestrial robots (4) (i.e. BioCarBot).
(1) D. Floreano, R. Pericet-Camara, S. Viollet, F. Ruffier, A. Brückner, R. Leitel, W. Buss, M. Menouni, F. Expert, R. Juston, M. K. Dobrzynski, G. L’Eplattenier, F. Recktenwald, H. A. Mallot, N. Franceschini (2013)
« Miniature curved artificial compound eyes »
Proceedings of National Academy of Sciences of USA, PNAS, 2013 Jun 4, 110(23):9267-72
(2) S. Mafrica, S. Godiot, M. Menouni, M. Boyron, F. Expert, R. Juston, N. Marchand, F. Ruffier, S. Viollet (2015)
« A bio-inspired analog silicon retina with Michaelis-Menten auto-adaptive pixels sensitive to small and large changes in light »
Optics Express (OSA), Vol. 23, Issue 5, pp. 5614-5635
(3) F. Expert and F. Ruffier (2015)
« Flying over uneven moving terrain based on optic-flow cues without any need for reference frames or accelerometers »
Bioinspiration & Biomimetics, 10, 026003 (IOP)
(4) S. Mafrica, A. Servel, F. Ruffier (2016)
« Optic-Flow Based Car-Like Robot Operating in a 5-Decade Light Level Range »
2016 IEEE Int. Conf. Robot. Autom. (ICRA 2016), Stockholm, Sweden, May 16-21, 2016
Franck Ruffier received an engineering degree in 2000 and a Ph.D. degree from INP-Grenoble in 2004, as well as a habilitation to supervise research (HDR in French) from Aix-Marseille University in 2013. He was visiting scientist invited by Prof. Michael Dickinson, Univ. of Washington, Seattle, USA during 2 months in 2012 as well as in 2008 by Dr. T. Mukai at RIKEN, Nagoya, Japan. Franck Ruffier published more than 80 articles in international Journals, referred Proceedings and 12 book chapters as well as he filed 9 patents. His present position is CNRS research scientist at the Institute of Movement Science (ISM). His main areas of interest are bio-inspired vision and robotic.