Deep Learning-based Target Following and Obstacle Avoidance Methods in Mobile Robots
- Authors
- Lee, M.C.; Lee, M.
- Issue Date
- Oct-2022
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- companion robot; mobile robot; object avoidance; object detection and classification; object tracking
- Citation
- 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022
- Journal Title
- 2022 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2022
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/69898
- DOI
- 10.1109/ICCE-Asia57006.2022.9954653
- ISSN
- 0000-0000
- Abstract
- In this study, we develop a companion robot function that can recognize people and obstacles, and track the human target while avoiding the obstacles. In implementing the JetBot tracking function, a deep learning-based object detection model is modified and utilized. A transfer learning algorithm with a pretrained mobile model is introduced for a feasible operation in the proposed framework with mobile robots.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - College of ICT Engineering > School of Electrical and Electronics Engineering > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/69898)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.