为了辅助视障人士出行，设计了一个基于AI机器视觉的盲道信息采集系统，实现对盲道信息的智能化采集。系统基于图像边缘检测以及形态学约束识别正常盲道，实现轮式机器人沿盲道的自动行驶，使用YOLOv8目标检测模型搭配华为昇腾AI处理器识别盲道异常情况，并将检测结果通过Wi-Fi上传至上位机。测试时铺设30cm×30cm模拟盲道砖块，并在不同位置放置破损盲道、缺失盲道、可移动与不可移动障碍物进行多次检测。经测试，该系统能在设定场景下完成盲道信息采集，确定异常情况类型与发生位置，盲道异常情况检测平均准确率达95%，异常情况定位信息与实际位置的平均绝对误差小于9.12cm，可应用于市政了解盲道环境信息，辅助视障人士安全出行。

To assist visually impaired individuals in navigation, an AI-based machine vision system for collecting tactile paving information has been designed to enable intelligent data acquisition. The system identifies standard tactile paving through image edge detection and morphological constraints, enabling wheeled robots to autonomously traverse tactile paths. It employs the YOLOv8 object detection model paired with Huawei Ascend AI processors to detect anomalies in tactile paving, transmitting detection results to a host computer via Wi-Fi. During testing, simulated tactile paving tiles measuring 30cm × 30cm were laid out. Multiple detection runs were conducted with damaged tactile paving, missing sections, and both movable and immovable obstacles placed at various positions. Testing confirmed the system's capability to collect tactile paving data within defined scenarios, identify anomaly types and locations, with an average detection accuracy of 95%. The average absolute error in anomaly location pinpointing was less than 9.12 cm relative to actual positions. This system can assist municipal authorities in understanding tactile paving conditions and support safe travel for visually impaired individuals.