A bioinspired vision chip architecture for collision detection in automotive applications

This paper describes the architecture and retino-topic unit of a bio-inspired vision chip intended for automotive applications. The chip contains an array of 100X150 sensors which are able to capture high dynamic range (HDR) images, with a programmable compressive characteristic. The chip also incorporates a mechanism for adaptation of the global exposition time to the average illumination conditions. Average values are evaluated over image areas which are programmable by the user. In addition to the HDR pixel, every retino-topic unit in the array incorporates digital memory for three 6-bit pixel values (18-bits), as required for the implementation of a bionspired computing model for collisions detection which has been developed in the framework of a multidisciplinary European research project. All processing steps are executed off-chip, though we are currently working in the design of tiny digital processors (one per column) which will allow for running the whole model on-chip in a future version of this prototype. The chip has been designed in a 0.35μm 2P-4M technology and maintains its correct operation in extreme temperature conditions (from -40°C to 110°C).

[1]  Y. Tsividis.  Operation and modeling of the MOS transistor , 1987 .

[2]  Reid R. Harrison,et al.  A Low-Power Analog VLSI Visual Collision Detector , 2003, NIPS.

[3]  G. Linan,et al.  A bioinspired collision detection algorithm for VLSI implementation , 2005, SPIE Microtechnologies.

[4]  F. Rind,et al.  Neural network based on the input organization of an identified neuron signaling impending collision. , 1996, Journal of neurophysiology.

[5]  Michel Declercq,et al.  Implementation of a neuron dedicated to Kohonen maps with learning capabilities , 1990, IEEE Proceedings of the Custom Integrated Circuits Conference.

[6]  B.J. Hosticka,et al.  A high dynamic range CMOS image sensor for automotive applications , 2000, Proceedings of the 25th European Solid-State Circuits Conference.

[7]  Orly Yadid-Pecht,et al.  Wide-dynamic-range sensors , 1999 .

[8]  L. McIlrath.  A low-power low-noise ultrawide-dynamic-range CMOS imager with pixel-parallel A/D conversion , 2001, IEEE J. Solid State Circuits.

[9]  Xinqiao Liu,et al.  A 10000 frames/s CMOS digital pixel sensor , 2001, IEEE J. Solid State Circuits.

[10]  Saibal Mukhopadhyay,et al.  Leakage current mechanisms and leakage reduction techniques in deep-submicrometer CMOS circuits , 2003, Proc. IEEE.

[11]  A. El Gamal,et al.  A 640/spl times/512 CMOS image sensor with ultra wide dynamic range floating-point pixel-level ADC , 1999, 1999 IEEE International Solid-State Circuits Conference. Digest of Technical Papers. ISSCC. First Edition (Cat. No.99CH36278).

[12]  P. Simmons,et al.  Seeing what is coming: building collision-sensitive neurones , 1999, Trends in Neurosciences.

[13]  Markus Böhm,et al.  100.000 pixel 120 dB imager in TFA-technology , 1999 .

[14]  M. Wagner,et al.  100000-pixel, 120-dB imager in TFA technology , 1999, IEEE Journal of Solid-State Circuits.

[15]  E. Vittoz,et al.  Analog Storage of Adjustable Synaptic Weights , 1991 .

[16]  S. Bermudez i Badia,et al.  A collision avoidance model based on the Lobula giant movement detector (LGMD) neuron of the locust , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

[17]  Behzad Razavi,et al.  Principles of data conversion system design / Behzad Razavi , 1995 .

[18]  Kaushik Roy,et al.  Leakage in nano-scale technologies: mechanisms, impact and design considerations , 2004, Proceedings. 41st Design Automation Conference, 2004..

[19]  Barry Fowler,et al.  A 640×512 CMOS Image Sensor with Ultra Wide Dynamic Range Floating-Point Pixel-Level ADC , 1999 .

[20]  Bedrich J. Hosticka,et al.  CMOS imaging for automotive applications , 2003 .

[21]  Randall L. Geiger,et al.  VLSI Design Techniques for Analog and Digital Circuits , 1989 .

[22]  Richard Stafford,et al.  A bio-inspired visual collision detection mechanism for cars: Optimisation of a model of a locust neuron to a novel environment , 2006, Neurocomputing.

[23]  Yannis Tsividis,et al.  Current copier cells , 1988 .