Navigation by Scenarios Using Topological Map
Momoko HARA, Hiroki SHIMADA, Ryuichi Ueda, Yasuo HAYASHIBARA · The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) · 2022
We propose a passage classification method using omnidirectional camera images and object detection by machine learning. In this method, image data of 360 degrees horizontally is firstly acquired using an omnidirectional camera. Next, objects such as passages and doors are detected from the acquired image data using the YOLO detector. Finally, it is determined which passage feature is classified according to the type and position of the detected object. We conducted an experiment to classify passage features from images in order to verify the effectiveness of the proposed method. In addition, the proposed method is applied and used for our scenario-based navigation method. We conduct navigation experiments and verify the effectiveness of the applied method.