用边缘设备加速物体检测，显著降低推理耗时与功耗。
Fast Object Detection with a Machine Learning Edge Device
- 选用Edge TPU芯片，实现比GPU快25%、比CPU快87.5%的推理速度。
- 在单目与双目视觉对比中，验证了双目对机器人场景理解的有效性。
- 为自主人形机器人实时视觉导航提供轻量高效计算方案。
本研究探讨了一种低成本边缘设备与嵌入式系统结合的计算机视觉方案，在物体检测与分类任务中实现了推理时间与精度的提升。研究目标是降低推理延迟与功耗，支持竞争级自主人形机器人的实时需求，涵盖物体识别、场景理解、视觉导航、运动规划与自主导航。对比了中央处理器（CPU）、图形处理器（GPU）和张量处理器（TPU）在推理性能上的差异。结果显示，采用TPU的推理时间较GPU减少25%，较CPU减少87.5%。研究还评估了单目与双目视觉在机器人应用中的表现差异，最终确定谷歌Coral Edge TPU为最优选。Arduino Nano 33 BLE Sense Tiny ML Kit因初期兼容性问题被暂搁，未来将另行实验验证。
原文摘要 · Abstract (English)
This machine learning study investigates a lowcost edge device integrated with an embedded system having computer vision and resulting in an improved performance in inferencing time and precision of object detection and classification. A primary aim of this study focused on reducing inferencing time and low-power consumption and to enable an embedded device of a competition-ready autonomous humanoid robot and to support real-time object recognition, scene understanding, visual navigation, motion planning, and autonomous navigation of the robot. This study compares processors for inferencing time performance between a central processing unit (CPU), a graphical processing unit (GPU), and a tensor processing unit (TPU). CPUs, GPUs, and TPUs are all processors that can be used for machine learning tasks. Related to the aim of supporting an autonomous humanoid robot, there was an additional effort to observe whether or not there was a significant difference in using a camera having monocular vision versus stereo vision capability. TPU inference time results for this study reflect a 25% reduction in time over the GPU, and a whopping 87.5% reduction in inference time compared to the CPU. Much information in this paper is contributed to the final selection of Google's Coral brand, Edge TPU device. The Arduino Nano 33 BLE Sense Tiny ML Kit was also considered for comparison but due to initial incompatibilities and in the interest of time to complete this study, a decision was made to review the kit in a future experiment.
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