Individuals who are differently-able in vision cannot proceed with their day-to-day activities as smoothly as other people do. Especially independent walking is a hard target to achieve with their visual impairment. Assistive electronic travel aids equipped with different types of sensors are designed for visually impaired persons to assist their safe navigation. The amount of research on combining multiple sensors in assistive navigation aids for visually impaired navigation is limited. Most work is targeted at sensor integration but not at sensor fusion. This paper aims to address how sensor fusion and integration will be used to improve the sub-processes of visually impaired navigation and the way to evaluate the sensor fusion-based approach for visually impaired navigation which consists of several contributions to field sensor fusion in visually impaired navigation such as a novel homogeneous sensor fusion algorithm based on extended Kalman filter, a novel heterogeneous sensor integration approach, and a complementary sensor fusion algorithm based on error state extended Kaman filter. Overall this research presents a novel navigational framework to integrate obstacle detection, obstacle recognition, localization, motion planning, and current context awareness with sensor fusion.

翻译：视觉功能受限的个体无法像其他人那样顺畅地进行日常活动。特别是在视觉障碍的情况下，独立行走是一个难以实现的目标。为辅助视障人士安全出行，配备了多种传感器的辅助电子出行设备应运而生。目前，关于在视障导航辅助设备中融合多种传感器的研究仍较为有限。大多数工作侧重于传感器集成而非传感器融合。本文旨在探讨如何利用传感器融合与集成技术改进视障导航的各个子过程，并提出基于传感器融合的视障导航方法评估体系。本研究为视障导航领域的传感器融合技术作出了多项贡献，包括：一种基于扩展卡尔曼滤波的新型同构传感器融合算法、一种新型异构传感器集成方法，以及一种基于误差状态扩展卡尔曼滤波的互补传感器融合算法。总体而言，本研究提出了一种创新的导航框架，通过传感器融合技术将障碍物检测、障碍物识别、定位、运动规划和当前环境感知等功能进行集成。