Due to huge computational loads and the state of art of current hardware, nowadays how to implement real-time vision tasks on a signal chip is still a great interesting work. It is critical for eventually accomplishing biointelligence on robots, whatever humanoid robots, insect robots or even space robots. This paper presents a design of a so-called visual brain chip for robotic vision applications in order to explore biological visual information processing mechanisms. Biological vision systems explore their environments via allocating their visual resources to only the interesting parts of a scene. This is achieved by a selective visual attention mechanism that controls eye movements. Such mechanism is useful to reduce the complexity of calculation. The computational process was divided into three stages for achieving real-time visual computation. The whole system for the chip design used a PTZ TV camera, ASIC technology altogether with a LEON RISC processor and was verified on the FPGA development board. It is a good attempt for future robot vision system applications, especially for space robot, due to limited onboard computing resources, limited viewpoints and mobility.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    A Visual Brain Chip Based on Selective Attention for Robot Vision Application


    Contributors:
    Wang, Tao (author) / Zheng, Nanning (author) / Mei, Kuizhi (author)


    Publication date :

    2009-07-01


    Size :

    526059 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Visual robot navigation with omnidirectional vision

    Posada, Luis Felipe | TIBKAT | 2019


    Visual robot navigation with omnidirectional vision

    Posada, Luis Felipe | BASE | 2019

    Free access

    A visual attention model for robot object tracking

    Chu, J. K. / Li, R. H. / Li, Q. Y. et al. | British Library Online Contents | 2010


    Selective Attention for Identification Model: Simulating visual neglect

    Heinke, D. / Humphreys, G. W. | British Library Online Contents | 2005


    A computer vision model for visual-object-based attention and eye movements

    Sun, Y. / Fisher, R. / Wang, F. et al. | British Library Online Contents | 2008