Cooperative path-following control of a remotely operated underwater vehicle for human visual inspection task

In recent years, significant attention has been paid to remotely operated underwater vehicles (ROVs) in the performance of underwater tasks, such as the inspection and maintenance of the underwater infrastructure. The workload of ROV operators tends to be high, even for the skilled operators. Therefore, assistance methods for the operators are desired. This study focuses on a task in which a human operator controls an underwater robot to follow a certain path while visually inspecting objects in the vicinity of the path. In such a task, it is desirable to achieve the speed of trajectory control manually because the visual inspection is performed by a human operator. However, to allocate resources to visual inspection, it is desirable to minimize the workload on the path-following by assisting with the automatic control. Therefore, the objective of this study is to develop a cooperative path-following control method that achieves the above-mentioned task by expanding a robust path-following control law of non-holonomic wheeled vehicles. To simplify this problem, we considered a path-following and visual objects recognition task in a two-dimensional plane. We conducted an experiment with participants (n = 16) who completed the task using the proposed method and manual control. We compared results in terms of object recognition success rate, tracking error, completion time, attention distribution, and workload. The results showed that both the path-following errors and workload of the participants were significantly smaller with the proposed method than with manual control. In addition, subjective responses demonstrated that operator attention tended to be allocated to object recognition rather than robot operation tasks with the proposed method. These results demonstrate the effectiveness of the proposed cooperative path-following control method.