This paper presents a new holistic vision-based mobile assistive navigation system to help blind and visually impaired people with indoor independent travel. The system detects dynamic obstacles and adjusts path planning in real-time to improve navigation safety. First, we develop an indoor map editor to parse geometric information from architectural models and generate a semantic map consisting of a global 2D traversable grid map layer and context-aware layers. By leveraging the visual positioning service (VPS) within the Google Tango device, we design a map alignment algorithm to bridge the visual area description file (ADF) and semantic map to achieve semantic localization. Using the on-board RGB-D camera, we develop an efficient obstacle detection and avoidance approach based on a time-stamped map Kalman filter (TSM-KF) algorithm. A multi-modal human-machine interface (HMI) is designed with speech-audio interaction and robust haptic interaction through an electronic SmartCane. Finally, field experiments by blindfolded and blind subjects demonstrate that the proposed system provides an effective tool to help blind individuals with indoor navigation and wayfinding.

中文翻译：

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基于视觉的盲人移动室内辅助导航设备


本文提出了一种新型的基于整体视觉的移动辅助导航系统，以帮助盲人和视障人士进行室内独立出行。系统检测动态障碍物并实时调整路径规划，提高导航安全性。首先，我们开发一个室内地图编辑器来解析建筑模型中的几何信息，并生成由全局 2D 可遍历网格地图层和上下文感知层组成的语义地图。通过利用Google Tango设备内的视觉定位服务（VPS），我们设计了一种地图对齐算法来桥接视觉区域描述文件（ADF）和语义地图，以实现语义定位。使用机载 RGB-D 相机，我们开发了一种基于时间戳地图卡尔曼滤波器 (TSM-KF) 算法的高效障碍物检测和规避方法。多模式人机界面 (HMI) 设计为通过电子 SmartCane 实现语音交互和强大的触觉交互。最后，蒙眼和盲人受试者的现场实验表明，所提出的系统提供了一种有效的工具来帮助盲人进行室内导航和寻路。