This paper presents the development and field testing of multiple autonomous surface vehicles (ASVs) for autonomous cooperative navigation tasks in marine environments. The developed ASVs were designed in a catamaran hull form, and various systems related to autonomous functionalities, including the electrical propulsion, wireless communication, and guidance, navigation, and control (GNC) systems, were integrated with the situational awareness sensor system. Because not all of the navigation and situational awareness sensor data can be shared owing to the large network load, the network communication and data protocol structure was designed to enhance the data management efficiency. Furthermore, for cooperative navigation between multiple ASVs, the network communication system was synchronously shared with motion information through a robot operating system (ROS) multi-master system. In particular, an autonomy framework with cooperative navigation and control was designed to enable autonomous cooperative maneuvering with multiple ASVs in a global navigation satellite system (GNSS)-denied environment. Furthermore, a cooperative navigation and control approach based on relative geometric information between vehicles was implemented in the framework, which incorporated the capabilities of following a predefined path and maintaining a specific formation based on the relative distance between ASVs. Moreover, to demonstrate the essential maneuvering and functional capabilities of the cooperative navigation and control approach of the developed ASVs, preliminary field tests were conducted in an inland water environment, and the test results are discussed in this paper.

Acoustic source localization is used in many underwater applications. Acquiring an accurate directional angle for an acoustic source is crucial for source localization. To achieve this purpose, this paper presents a method for directional angle estimation of underwater acoustic sources using a marine vehicle. It is assumed that the vehicle is equipped with two hydrophones and that the acoustic source transmits a specific signal repeatedly. The proposed method provides a probabilistic model for time delay estimation. The probability is recursively updated by prediction and update steps. The prediction step performs a probability transition using the angular displacement of the marine vehicle. The predicted probability is updated using a generalized cross correlation function with a verification process using entropy measurement. The proposed method can provide a reliable and accurate estimation of the directional angles of underwater acoustic sources. Experimental results demonstrate good performance of the proposed probabilistic directional angle estimation method in both an inland water environment and a harbor environment.

This paper proposes a probability-based framework for recognizing underwater landmarks using sonar images. Current recognition methods use a single image, which does not provide reliable results because of weaknesses of the sonar image such as unstable acoustic source, many speckle noises, low resolution images, single channel image, and so on. However, using consecutive sonar images, if the status—i.e., the existence and identity (or name)—of an object is continuously evaluated by a stochastic method, the result of the recognition method is available for calculating the uncertainty, and it is more suitable for various applications. Our proposed framework consists of three steps: (1) candidate selection, (2) continuity evaluation, and (3) Bayesian feature estimation. Two probability methods—particle filtering and Bayesian feature estimation—are used to repeatedly estimate the continuity and feature of objects in consecutive images. Thus, the status of the object is repeatedly predicted and updated by a stochastic method. Furthermore, we develop an artificial landmark to increase detectability by an imaging sonar, which we apply to the characteristics of acoustic waves, such as instability and reflection depending on the roughness of the reflector surface. The proposed method is verified by conducting basin experiments, and the results are presented.