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

Tao Wang, Nanning Zheng, K. Mei
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引用次数: 4

Abstract

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.
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基于选择性注意的视觉脑芯片在机器人视觉中的应用
由于庞大的计算量和当前硬件的技术水平,如何在信号芯片上实现实时视觉任务仍然是一个非常有趣的工作。这对于最终实现机器人的生物智能至关重要,无论是人形机器人、昆虫机器人还是太空机器人。为了探索生物视觉信息处理机制,本文设计了一种用于机器人视觉应用的视觉大脑芯片。生物视觉系统通过将视觉资源分配给场景中有趣的部分来探索环境。这是通过控制眼球运动的选择性视觉注意机制实现的。这种机制有助于降低计算的复杂性。为了实现实时可视化计算,将计算过程分为三个阶段。整个系统的芯片设计采用了PTZ电视摄像机、ASIC技术以及LEON RISC处理器,并在FPGA开发板上进行了验证。由于机载计算资源有限,视点和机动性有限,这是未来机器人视觉系统应用的一个很好的尝试,特别是空间机器人。
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