Sensor-level computer vision with pixel processor arrays for agile robots

计算机科学 智能摄像头 人工智能 机器人学 图像传感器 图像处理 利用 嵌入式系统 低延迟(资本市场) 计算机视觉 机器人 计算机硬件 实时计算 计算机网络 计算机安全 图像(数学)
作者
Piotr Dudek,Thomas Richardson,Laurie Bose,Stephen J. Carey,Jianing Chen,Colin Greatwood,Yanan Liu,Walterio Mayol‐Cuevas
出处
期刊:Science robotics [American Association for the Advancement of Science]
卷期号:7 (67) 被引量:33
标识
DOI:10.1126/scirobotics.abl7755
摘要

Vision processing for control of agile autonomous robots requires low-latency computation, within a limited power and space budget. This is challenging for conventional computing hardware. Parallel processor arrays (PPAs) are a new class of vision sensor devices that exploit advances in semiconductor technology, embedding a processor within each pixel of the image sensor array. Sensed pixel data are processed on the focal plane, and only a small amount of relevant information is transmitted out of the vision sensor. This tight integration of sensing, processing, and memory within a massively parallel computing architecture leads to an interesting trade-off between high performance, low latency, low power, low cost, and versatility in a machine vision system. Here, we review the history of image sensing and processing hardware from the perspective of in-pixel computing and outline the key features of a state-of-the-art smart camera system based on a PPA device, through the description of the SCAMP-5 system. We describe several robotic applications for agile ground and aerial vehicles, demonstrating PPA sensing functionalities including high-speed odometry, target tracking, obstacle detection, and avoidance. In the conclusions, we provide some insight and perspective on the future development of PPA devices, including their application and benefits within agile, robust, adaptable, and lightweight robotics.
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