Disclosed is a dynamic collision avoidance method for an unmanned surface vessel based on route replanning. The method comprises the following steps: acquiring navigation information and pose information of a neighboring ship of an unmanned vessel itself via a vessel-borne sensor; constructing a collision cone between the unmanned vessel and the neighboring ship; introducing a degree of uncertainty with respect to observing movement information of the neighboring ship and applying a layer of soft constraint to the collision cone; applying a speed and a heading limit range of the unmanned vessel; acquiring an ultimate candidate speed set; introducing a cost function to select an optimum collision avoidance speed; and performing an internal recycle of navigation simulation with the optimum collision avoidance speed to obtain a route replanning point for dynamic collision avoidance of the unmanned vessel. According to the present invention, a dynamic collision avoidance strategy of the unmanned surface vessel is output in form of route replanning to meet constraints of international regulations for preventing collisions at sea, and it is well adapted to manipulate and control the unmanned vessel itself, so that a dynamic collision avoidance requirement of the unmanned vessel is met.

Apparatuses, methods, and computer-readable medium for navigation safety and collision prevention are described herein. The apparatus may cause the collection of marine electronic data from marine data sources. Marine data sources may include a radar system, a sonar system, a position system, a tracking system, and/or a chart system. The apparatus may further determine, based upon the marine electronic data, the presence of a hazard in the projected path of the watercraft. The apparatus may determine if the hazard is within a threshold distance and, in response, may cause the watercraft to stop before reaching the hazard. In some instances, the apparatus may transmit a warning alert to the watercraft operator, and after a predetermined period of time without response by the operator, the apparatus may cause the watercraft to stop to prevent collision with the hazard.

A marine autopilot system configured to control a marine vessel through a marine environment is disclosed herein. The marine autopilot system may obtain data of the marine environment from charts and community shared data and generate a path from a first location to a destination location in the marine environment. The marine autopilot system may control the marine vessel along the path based on the marine vessel dynamics and weather and water current conditions. Sensors may detect hazards on and in the water and object detections systems may classify the hazards. The marine autopilot system may control the marine vessel to avoid the hazards based on the location and classification of the hazards. Furthermore, sensors may be utilized to generate detailed 3D maps that change with time to dock the marine vessel at known and unknown locations.

The present invention discloses a vessel collision avoiding system and method based on Artificial Potential Field algorithm, the method comprises the following steps: (S1) obtaining a vessel information, at least one obstacle information and a target information; (S2) establishing an Artificial Potential Field (APF) by the vessel information, the at least one obstacle information and the target information, wherein the Artificial Potential Field comprises an attractive field of the target and a repulsive field of the obstacle; (S3) combining the attractive field and the repulsive field to obtain a first resultant force; (S4) Adding an external force to the Artificial Potential Field based on the vessel information or the obstacle information; (S5) combining the first resultant force and the external force to obtain a second resultant force; and (S6) the vessel sails in the direction of the second resultant force to avoid the obstacle.

The present invention discloses a vessel collision avoiding system and method based on Artificial Potential Field algorithm, the method comprises the following steps: (S1) obtaining a vessel information, at least one obstacle information and a target information; (S2) establishing an Artificial Potential Field (APF) by the vessel information, the at least one obstacle information and the target information, wherein the Artificial Potential Field comprises an attractive field of the target and a repulsive field of the obstacle; (S3) combining the attractive field and the repulsive field to obtain a first resultant force; (S4) Adding an external force to the Artificial Potential Field based on the vessel information or the obstacle information; (S5) combining the first resultant force and the external force to obtain a second resultant force; and (S6) the vessel sails in the direction of the second resultant force to avoid the obstacle.

The present invention relates to a method for acquiring an object information, the method comprising: obtaining an input image acquired by capturing a sea; obtaining a noise level of the input image; when the noise level indicates a noise lower than a predetermined level, acquiring an object information related to an obstacle included in the input image from the input image by using a first artificial neural network, and when the noise level indicates a noise higher than the predetermined level, obtaining a noise-reduced image of which the environmental noise is reduced from the input image by using a second artificial neural network, and acquiring an object information related to an obstacle included in the sea from the noise-reduced image by using the first artificial neural network.

A system and method for multi-image-based vessel proximity situation recognition support is proposed. The system may include an unmanned surface vehicle (USV) configured to detect and track surrounding objects by monitoring surroundings using surrounding images and navigation sensors. The system may also include a remote navigation controller configured to support proximity situation recognition of the unmanned surface vehicle according to detection of the surrounding objects, wherein the unmanned surface vehicle may include an image acquisition processor, a navigation sensor, and a detector.

A stern drive is for propelling a marine vessel in water. The stern drive has an upper drive unit with a lower mounting surface; a lower gearcase coupled to the lower mounting surface and a trailing end surface that is angled relative to the lower mounting surface; and a propeller shaft extending forwardly from the lower gearcase and being configured to rotate a propeller for pulling the marine vessel in the water. The upper drive unit and the lower gearcase are configured such that when a forward side of the lower gearcase impacts an underwater obstruction, the lower gearcase is caused to pivot relative to the upper drive unit until the trailing end surface impacts the lower mounting surface, which thereby causes the lower gearcase to completely uncouple from the upper drive unit.

A stern drive is for propelling a marine vessel in water. The stern drive has an upper drive unit with a lower mounting surface; a lower gearcase coupled to the lower mounting surface and a trailing end surface that is angled relative to the lower mounting surface; and a propeller shaft extending forwardly from the lower gearcase and being configured to rotate a propeller for pulling the marine vessel in the water. The upper drive unit and the lower gearcase are configured such that when a forward side of the lower gearcase impacts an underwater obstruction, the lower gearcase is caused to pivot relative to the upper drive unit until the trailing end surface impacts the lower mounting surface, which thereby causes the lower gearcase to completely uncouple from the upper drive unit.

A method of controlling a propulsion system on a marine vessel includes receiving proximity measurements describing locations of one or more objects with respect to the marine vessel, receiving a command vector instructing magnitude and direction for propulsion of the marine vessel with respect to a point of navigation for the marine vessel, and then determining a funnel boundary based on the command vector. An object is identified based on the proximity measurements and determined to be within the funnel boundary, and then a propulsion adjustment command is calculated based on the command vector and an angle of the object with respect to the point of navigation. At least one propulsion device is then controlled based on the propulsion adjustment command in order to avoid the object.