LiDAR-Based Obstacle Detection and Distance Estimation in Navigation Assistance for Visually Impaired
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People with visual impairments can face challenges with independent navigation and therefore may use traditional aids such as guide dogs, white canes, or a travel companion for navigation assistance. In recent years, researchers have been working on AI-based navigation assistance systems. Obstacle detection and distance estimation are two of the key challenges in such systems. In this paper, we describe a LiDAR-based obstacle detection and distance estimation technique. A lightweight deep learning-based model called EfficientDet-LiteV4 is used for obstacle detection, and a depth map from the LiDAR is used to estimate the distance to the obstacles. We have implemented and tested the approach with the LiDAR integrated into a Raspberry Pi4 board. The results show good accuracy in detecting the obstacles and in estimating distance.