Obstacle Avoidance in Mobile Robots In RGB-D Images Using Deep Neural Network and Semantic Segmentation

Al-Adhamı A. A., Cansever G.

4th INTERNATIONAL CONGRESS ON HUMAN-COMPUTER INTERACTION, OPTIMIZATION AND ROBOTIC APPLICATIONS, Ankara, Turkey, 9 - 11 June 2022, pp.1-5

  • Publication Type: Conference Paper / Full Text
  • City: Ankara
  • Country: Turkey
  • Page Numbers: pp.1-5
  • Yıldız Technical University Affiliated: Yes

Abstract

Abstract— Robotics today is integrated into the modern environment in automated production systems where manipulative robots are used in commercial and industrial activities to maneuver or have a variety of products available. On the other hand, in the area of ​​mobile robots, they have another method of operation such as obstacle avoidance, line trackers and mobile explorers; These robots are required to have a greater demand due to their high complexity in their operating system since they are used in research methods. For this reason, we propose a vision system whose main purpose is to detect and avoid obstacle in know environments by deploying a feature extraction and classification algorithm DNN of obstacles in RGB-D images.

Keywords—CNN, SVM, DL, ML, Robotics, RGB-D