Smart Robotic Wheelchair for Bus Boarding Using CNN Combined with Hough Transforms

Abstract

In recent times, several smart robotic wheelchair research studies have been conducted for the sake of providing a safe and comfortable ride for the user with real-time autonomous operations like object recognition. Further reliability support is essential for such wheelchairs to perform in real-time, common actions like boarding buses or trains. In this paper, we propose a smart wheelchair that can detect buses and precisely recognize bus doors and whether they are opened or closed for automated boarding. We use a modified simple CNN algorithm (i.e. modified Tiny-YOLO) as a base network on the CPU for fast detection of buses and bus doors. After that, we feed the detected information of our Hough line transform based method for accurate localization information of open bus doors. This information is indispensable for our bus-boarding robotic wheelchair to board buses. To evaluate the performance of our proposed method, we also compare the accuracy of our modified Tiny-YOLO and our proposed combined detection method with the original ground truth.