Underwater Acoustic Positioning Based on MEMS Microphone for a Lightweight Autonomous Underwater Vehicle "Kyubic"

Inniyaka, Irmiya R.; Solpico, Dominic B.; Hamada, Daiki; Sugino, Akihiro; Tanaka, Rikuto; Nishida, Yuya; Ishii, Kazuo

doi:10.5954/icarob.2022.os28-1

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For example, these include marine survey and mapping, pipeline recognition and tracking, and object detection and manipulation [1]. Our team has previously competed in the Okinawa Ocean Robotics Competition [2] and the Techno-Ocean Kobe Competition [3]. Therefore, we decided to compete in RoboSub2022 because it is an international robotics competition and the difficulty level of the image processing tasks is quite different from that of domestic competitions, making it an attractive opportunity to learn new skills.…”

Section: Introductionmentioning

confidence: 99%

Image-based navigation of Small-size Autonomous Underwater Vehicle "Kyubic" in International Underwater Robot Competition

Mizoguchi,

Hamada,

Fukuda

et al. 2023

Proceedings of International Conference on Artificial Life and Robotics

View full text Add to dashboard Cite

An International underwater robot competition, "RoboSub" is held in USA to demonstrate robot's autonomy by completing underwater tasks, with a new theme each year. Student project team, "Kyutech Underwater robotics" developed autonomous underwater vehicle (AUV) "KYUBIC" with built-in image processing module for the RoboSub. Sensors on the AUV are connected via ethernet and its automatic navigation program is built using ROS. The AUV moves through gate to the target objects based on self-localization using doppler velocity log and IMU. When approaching the object, the AUV aligns its direction to the object based on the red line detection by image processing as well as the type, position, and altitude of the target objects are detected by deep learning on the image processing module.

show abstract

Section: Introductionmentioning

confidence: 99%