SBIR Phase I: GHz Time-of-Flight Depth Sensing for Robotic Bin Picking

这个项目更广泛的影响/商业影响将是创建一个深度视觉系统，加速向智能自动化的过渡。智能自动化运动是由提高人类生产力的机会驱动的，它可以在各个领域看到：从西门子？it’亚马逊的自组织制造工厂？美国提议用无人机送货。该项目旨在提高机器人的视觉，这是目前限制更大的自主性。该研究利用半导体物理学的创新来创造飞行时间深度相机，达到新的空间分辨率和保真度水平。这些摄像头与快速发展的软件（利用深度数据来模拟物理世界）相结合，赋予机器人系统在动态环境中执行更复杂任务所需的类人能力。机器人将在导航、物料搬运和物体操纵任务方面变得越来越有效，这些任务是许多制造和物流过程的基础。该项目的成果将推进最先进的深度视觉技术，并提供一个原型相机，可用于测试各种具有挑战性的目标识别任务。这个小企业创新研究（SBIR）第一阶段项目解决了使用相位延迟飞行时间（TOF）方法的深度相机的一个重要限制。现有的TOF相机使用像素级解调。：特别设计的光电探测器阵列，其中每个像素都进行光探测和解调。这种设计限制了调制频率，从而限制了深度精度，因为高频信号会产生过多的噪声和寄生电容。作者提出了另一种选择？光解调?光通过一个快速光学快门解调，然后由一个单独的传统图像传感器采集的设计。通过将光调制与光检测分离，消除了寄生电容，并且可以在可接受的功耗和噪声下达到高频率。该研究项目将开发新的光学快门，以展示这些特性，并将快门集成到一个功能原型深度相机中。成功将表明，attof相机可以生产出具有更高空间分辨率和设计灵活性的相机。

The broader impact/commercial impact of this project will be to create a depth vision system that acceleratesthe transition to intelligent automation. The intelligent automation movement is driven by the opportunityto increase human productivity, and it can be seen in all domains: from Siemen?s self-organizingmanufacturing plants to Amazon?s proposed delivery drones. This project aims to improve robotic vision,which is currently a limitation to greater autonomy. The research uses innovations in semiconductorphysics to create time-of-flight depth cameras that reach new levels of spatial resolution and fidelity. Thesecameras, in conjunction with rapidly evolving software that uses depth data to model the physical world,give robotic systems the human-like abilities they need to perform more complicated tasks in dynamicenvironments. Robotics will become increasingly effective at the navigation, material handling, and objectmanipulation tasks that are the basis of so many manufacturing and logistics processes. The projectoutcomes will advance the state-of-the-art in depth vision technology, and provide a prototype camera thatcan be used to test a variety of challenging object recognition tasks.This Small Business Innovation Research (SBIR) Phase I project addresses an important limitation in depthcameras that use the phase delay time-of-flight (TOF) method. Existing TOF cameras use ?pixel-leveldemodulation?: specially designed photodetector arrays where each pixel performs both light detection anddemodulation. This design limits the modulation frequency, and thus depth accuracy, because the highfrequency signals create excessive noise and parasitic capacitances. The authors propose an alternative?optical demodulation? design wherein light is demodulated by a single fast optical shutter, and thencollected by a separate conventional image sensor. By separating light modulation from light detection,parasitic capacitances are eliminated and it is possible to reach high frequencies with acceptable powerconsumption and noise. The research program will develop new optical shutters that demonstrate thesecharacteristics, and integrate the shutters into a functioning prototype depth camera. Success will show thatTOF cameras can be produced with substantially higher spatial resolution and design flexibility.