This paper presents a control and operation system for a remotely operated vehicle (ROV). The ROV used in the study was equipped with a manipulator and is being developed for underwater exploration and autonomous underwater working. Precision position and attitude control ability is essential for underwater operation using a manipulator. For propulsion, the ROV is equipped with eight thrusters, the number of those are more than six degrees-of-freedom. Four of them are in charge of surge, sway, and yaw motion, and the other four are responsible for heave, roll, and pitch motion. Therefore, it is more efficient to integrate the management of the thrusters rather than control them individually. In this paper, a thrust allocation method for thruster management is presented, and the design of a feedback controller using sensor data is described. The software for the ROV operation consists of a robot operating system that can efficiently process data between multiple hardware platforms. Through experimental analysis, the validity of the control system performance was verified.

This study focuses on autonomous exploration based on map expansion for an underwater robot equipped with acoustic sonars. Map expansion is applicable to large-area mapping, but it may affect localization accuracy. Thus, as the key contribution of this paper, we propose a method for underwater autonomous exploration wherein the robot determines the trade-off between map expansion ratio and position accuracy, selects which of the two has higher priority, and then moves to a mission step. An occupancy grid map is synthesized by utilizing the measurements of an acoustic range sonar that determines the probability of occupancy. This information is then used to determine a path to the frontier, which becomes the new search point. During area searching and map building, the robot revisits artificial landmarks to improve its position accuracy as based on imaging sonar-based recognition and EKF-SLAM if the position accuracy is above the predetermined threshold. Additionally, real-time experiments were conducted by using an underwater robot, yShark, to validate the proposed method, and the analysis of the results is discussed herein.