A Travel Aid for Visually Impaired: R-Cane

An Electronic Travel Aid (ETA) has become a necessity for visually impaired to provide them proper guidance and assistance in their daily routine. As the number of blind persons are gradually increasing, there is a dire need of an effective and low-cost solution for assisting them in their daily tasks. This paper presents a cane called R-Cane which is an ETA for the visually impaired and is capable of detecting obstacles in front direction using sonar sensor and alerts the user by informing whether the obstacle is within the range of one meter. In R-Cane, tensorflow object-detection API has been used for object recognition. It makes the user aware about the nature of objects by providing them voice-based output through bluetooth earphones. Raspberry Pi has been used for processing and Pi camera has been used to capture frames for object recognition. Further, we have implemented four models based on Single Shot Multibox Detector (SSD) for object detection. The experimental analysis shows that out of the four models, the average F1 score for all the classes is highest for SSD_Mobilenet_v1 _Ppn_Coco model.