Research and Implementation of Travel Aids for Blind and Visually Impaired People

Blind and visually impaired (BVI) people face multiple challenges in terms of perception, navigation and safety when traveling. Although there are infrastructures such as blind alleys and pavement markings in cities, the design and maintenance of these facilities are often inadequate to fully meet the needs of traveling. Traditional travel aids usually rely on crutches or simple acoustic feedback, with poor flexibility and interactivity, making it difficult to effectively cope with complex travel environments. Therefore, it is especially necessary to design a set of intelligent and real-time travel assistive devices. Based on this, this paper proposes a set of travel assistance devices based on deep learning. The hardware part of the device includes the main controller-NVIDIA Jetson Nano, the environment sensing unit-D435i depth camera and the feedback unit-SG90 servo. In the software part, in order to meet the limitation of the embedded device's arithmetic power, this paper designs a lightweight target detection and segmentation algorithm to realize obstacle detection and forward direction guidance, which mainly includes a multi-scale attention feature extraction backbone network, a dual-stream fusion module combined with the Mamba architecture, and detection and segmentation heads capable of adaptive context-awareness. The algorithm has high topicality and computational efficiency, which makes it possible to meet the needs of blind people traveling on low-power embedded devices. The overall workflow of the system is as follows: firstly, the binocular depth camera D435i captures real-time information about the surrounding environment; then, the processor recognizes and analyzes the acquired data and converts the obstacle distance and road direction offset signals into Arduino electrical signals, and finally, the servo provides the vibration feedback in order to guide and warn the blind. After the field test, the results show that the device can help the blind find and avoid obstacles in time, correct the traveling position deviation, and meet the real-time requirements of the blind traveling.