The invention concerns a submarine exploration system (1) comprising: a master submarine drone (2) designed to move autonomously according to a predetermined flight plan (E) and comprising a communication module (C) for transmitting communication signals; a plurality of follower submarine drones (31, 32, 33, 34, 35, 36), each comprising at least one magnetic field detection system (D), each follower drone further comprising a communication module (C) for receiving communication signals from the master drone; the master drone being designed to transmit navigation instructions (I) to the follower drones and each follower drone being designed to move autonomously depending on the movement instruction such that its movement is slaved to the movement of the master drone.

A sonar system and method enable performing angled-looking sonar (ALS) by emitting sonar waves in a forward and downward direction from sonar transducers located at an underwater vessel. The sonar waves may be received by sonar transducers located al the underwater vessel. Additionally, a variable geometry sonar system and method enable performing side scan sonar (SSS) and ALS by moving al least one sonar transducer to perform both SSS and ALS. The variable geometry sonar system may be used with an underwater vessel to perform mine countermeasure (MCM) missions by using ALS for a homing phase on a target.

The invention relates to a method and system for path planning of a wave glider, comprising acquiring historical navigation data of the glider and an underwater vehicle via a shore-based monitoring center; fitting historical navigation data nonlinearly by a deep learning neural network to obtain a trained network; acquiring real-time navigation data of the glider at an off-line end, real-time navigation data and predetermined shipping track data of the vehicle; obtaining the set of off-line optimized path planning schemes of the glider by the above data and the trained network; and determining an optimal path planning scheme of the glider by the deep learning neural network according to real-time data and constraint data of the glider at the on-line end. The invention can reasonably plan the path of the glider and ensure continuous and reliable information interaction between the glider and the vehicle.

A geofenced autonomous aquatic drone for repelling sharks from a shoreline. The drone employs a buoyant housing resembling a portion of a predator such as an orca whale. A battery positioned within the drone is recharged through a floating inductive charging station. A transmitter unit coupled to at least one under water transducer introduces certain sounds, such as reproduction of orca whale or dolphin calling sounds. A propulsion system controlled a microprocessor receives location information via DGPS for providing a geofence around an area to be patrolled. The drone travels within the geofence area, monitored by the DGPS receiver, while said transducer produces certain sounds and or a solution of shark repellant is dispensed.

The present disclosure provides a small, inexpensive, long-lived underwater beacon locator. The beacon locator can illustratively include a housing, a communications link, a processor, a plurality of hydrophones and a motion generator.

An underwater vehicle for performing a variety of linear motions and turning motions with better stability and agility is disclosed. The underwater vehicle includes a main body, a front-drive mechanism, a rear-drive mechanism, and a steering assembly. The main body has a front end and a rear end, which defines a longitudinal axis extending from the front end to the rear end of the main body. The front-drive mechanism is connected to the main body to provide a forward propelling force in a direction parallel to the longitudinal axis. The steering assembly is fixed to the rear end and coupled to the rear-drive mechanism. The steering assembly is configured to rotate the rear-drive mechanism with respect to the longitudinal axis by a body angle for providing a lateral force on the main body.

An autonomous ship bottom inspection method by a ROV(s) based on a ship 3D model in STL format is provided. The ship 3D model is obtained and a surface thereof is spliced by triangular facets. Body 3D coordinate points of the ship 3D model are obtained and then expanded according to a safety distance of ROV and ship to obtain inspection track points of the ROV. The ship 3D model is divided into regions, and the inspection track points in each region are performed with interpolation and smoothing. Smoothed inspection track points of the regions are connected as per a result of the dividing to obtain a ship bottom inspection track, a real-time position of the ROV is obtained, a ship bottom inspection path is generated based on the ship bottom inspection track and the real-time position. The ROV is controlled to move as per the ship bottom inspection path.

A field configurable autonomous vehicle includes modular elements and attachable components. The vehicle can be assembled from these modular elements and components to meet desired mission and performance characteristics without the need to purchase specially designed vehicles for each mission. The vehicle can include a module for buoyancy control.

Multiple autonomous underwater vehicles (AUVs) are operated by a host platform by configuring the AUVs with intermediate nodes (such as unmanned surface vehicles (USVs)) so as to allow the host platform to manage multiple AUVs. The intermediate nodes act as a relay for communications between the host platform and the AUVs allowing the host platform to scale to higher numbers of vehicles thus simultaneously operating the entire fleet of AUVs. The AUVs may provide underwater mapping data. The host platform may be stationary. The host platform may communicate with the intermediate nodes by satellite.

An unmanned vehicle including a vehicle body, propulsion system, maneuvering system, vehicle control system, rack, sensor, and a power supply. The vehicle control may be used to control the unmanned vehicle in combination with the propulsion and the maneuvering system. The rack may include a retractable mount that may move between a down position and an up position. The sensor system may include a plurality of transient object detection sensors. The plurality of transient object detection sensors may include a sensor adapted to detect an item of interest and may provide an item of interest signal to the vehicle control system. The vehicle control system may identify an item of interest classification and may provide a classification signal. The classification signal may be determined by the item of interest classification and may be utilized to avoid detection of the unmanned vehicle by the item of interest.