Insert title here Insert title here Insert title here

Operation of Mobile Robot in Snowy Environment [ June 2021 ~ Present ]

Research Background
Semantic Segmentation by Using GAN in Snow-covered Road
In order to reduce the burden on the elderly in heavy snowfall areas, it is important to support snow removal work with robots. In this research, we propose a motion control method to follow snow-covered road for autonomous mobile robot equipped with an RGB camera. To this end, we improve the road detection accuracy of semantic segmentation by using generative adversarial network (GAN) in snowy environment. In addition, the central point of the detected road area was extracted as sub-goal for the motion control of the mobile robot; thus, the mobile robot is able to follow snow-covered road stably.


Mov. 1 Semantic segmentation-based road detecion using fake image translated by GAN.


Mov. 2 Autonomous navigation of mobile robot in snowy environment.


Related Paper
•三浦 玲和, 池 勇勳, "Structure from motionによる3次元モデルを利⽤した全⽅位カメラ画像の走行可能領域検出," ビジョン技術の実利用ワークショップ2024講演論文集 (ViEW2024), 横浜, December 2024.
• Fangzheng Li and Yonghoon Ji, "Dual-Type Discriminator Adversarial Reservoir Computing for Robust Autonomous Navigation in a Snowy Environment," Proceedings of the 2024 21th International Conference on Ubiquitous Robots (UR2024), New York, USA, June 2024.
• Jiaheng Lu and Yonghoon Ji, "Autonomous Navigation with Route Opening Capability Based on Deep Reinforcement Learning by Material Recognition," Proceedings of the 2024 21th International Conference on Ubiquitous Robots (UR2024), New York, USA, June 2024.
• Yugo Takagi and Yonghoon Ji, "Motion Control of Mobile Robot Based on Semantic Segmentation of GAN-generated Fake Image for Snow-covered Environment," Proceedings of the 19th International Conference on Ubiquitous Robots (UR2022), Jeju , Korea, July 2022.