マルチビームイメージングソーナーを用いたAUV による遊泳生物の探知追跡手法

―浅海域におけるウミガメ追跡実験―

抄録

Toward long-term and non-invasive observation of nektons by an AUV without attaching any tag to them, the authors propose an autonomous detection and tracking method with a multi-beam imaging sonar. Sea turtles are set as the initial target. The method utilizes convolutional neural network (CNN) for detecting a sea turtle in sonar imagery. Surge and yaw movements of the AUV are controlled to maintain the relative distance and direction to the detected target. The proposed method was implemented in the AUV HATTORI. The AUV succeeded in tracking a sea turtle in natural condition for 270 seconds in shallow sea.