Proper setting of feedback control according to the ship. The ship control device includes processing circuitry configured to set the ship characteristic parameters of the combined system of first order lag and dead time, which integrates the behavior of the rudder and the behavior of the ship. Using the ship characteristic parameters, the processing circuitry is further configured to calculate the control parameters of feedback control with respect to the rudder angle of the rudder. Using the control parameters, the processing circuitry is further configured to perform feedback control.

A marine vessel maneuvering system that is able to avoid a collision with an object includes a controller configured or programmed to function as a judging unit to judge whether or not there is a collision possibility of a collision between an object and a marine vessel, wherein the controller is configured or programmed to execute a deceleration control in response to the judging unit judging that there is the collision possibility.

The navigation support device includes processing circuitry. The processing circuitry generates a set of candidate values for a plurality of parameters associated with an automatic berthing control of a ship, performs simulations of a berthing behavior of the ship based on each set of candidate values for the plurality of parameters, performs evaluations of the berthing behavior for each set of candidate values for the plurality of parameters based on results of the simulations, and determines a control parameter associated with the automatic berthing control from the set of candidate values for the plurality of parameters, based on the results of the evaluation of the berthing behavior.

The present disclosure discloses a method for target assignment and route planning for multi-agent unmanned surface vehicles (USVs). Task information is transmitted to a task allocator, which identifies unassigned targets and available USVs. Based on a comprehensive cost function considering navigation distance and turning penalties between targets and USVs, a target is assigned to each USV A path planner then generates a smooth waypoint sequence for each assigned USV and target pair, serving as the navigation path. During navigation, a navigation controller constructs a velocity optimization model according to cooperative collision avoidance and maritime boundary constraints, and controls the USVs in real-time to navigate along the waypoint sequences. The present disclosure achieves efficient matching of multiple targets and multi-agent USVs, generates smooth navigation paths satisfying constraints, and enables intelligent navigation control while meeting cooperative collision avoidance requirements and maritime boundary constraints.

An adaptive fuzzy integral differential line-of-sight (AFIDLOS) method for path tracking of a laser bathymetry unmanned surface vehicle is provided. The AFIDLOS method includes determining an AFIDLOS manner, establishing an unmanned surface vehicle control model, determining an LQR heading controller, and determining a path tracking manner by combining the AFIDLOS manner and the LQR controller to realize a path tracking control of an unmanned surface vehicle in a microcontroller. The method for path tracking is verified in experiments. Experimental results show that, compared with a traditional LOS guidance rate, 79.85% reduction in overshoot, and 55.32% shorter adjustment time are achieved by the AFIDLOS manner in simulation experiments, while 9.5% of an average lateral error is reduced in the Beihai Beach experiment, and an overlap rate between strips reaches 30% in the Pinqing Lake experiment, which meets the accuracy requirements of bathymetric mapping.

A system for automatically identifying available docking positions using a vision system of a marine vessel is provided, the system comprising: an imaging device, wherein the imaging device is configured to be mounted to the marine vessel with an associated field of view of an environment of the marine vessel; and one or more hardware processors configured to: identify, based on image data captured using the imaging device, a dock instance; determine, based on the image data, whether the dock instance is available for docking; indicate that the dock instance is an available docking position; and cause the marine vessel to maneuver to the available docking position.

An optimized coverage-path planning method for a single unmanned surface mapping vessel (USMV) is implemented with a system including a computer processor executing a computer program loaded in a storage device and implanting the method. The method includes rasterizing and initializing an environmental map, and an unmanned vessel outputting position data and obstacle data according to the environmental map so that path planning is started to provide a target point to the unmanned vessel. In case of tripping in a local optimum at a current-level map for the target point, the map level is updated in an ascending order until the highest level, in order to identify a map level in which the target point is found.

A system for a boat includes a first guideway installed under a main deck of the boat, a first battery pack coupled to the first guideway under the main deck, and a first actuator configured to move the first battery pack along the first guideway. A controller is electrically and/or signally coupled with the first actuator. A user input device is electrically and/or signally coupled with the controller. The controller is configured to control the first actuator to move the first battery pack along the first guideway in response to an input to the user input device so as to relocate the weight of the first battery pack under the main deck.

This application provides a swimming pool robot, including a robot body, a filter, a control unit, and a moving mechanism. Operating environments of the swimming pool robot at least include a first operating environment and a second operating environment. The moving mechanism at least includes a first moving mechanism configured to drive the swimming pool robot to move in the first operating environment and a second moving mechanism configured to drive the swimming pool robot to move in the second operating environment. The first operating environment is an underwater environment. The second operating environment is a non-underwater environment. The control unit is capable of controlling, based on a current operating environment of the swimming pool robot, a moving mechanism corresponding to the current operating environment of the swimming pool robot to drive the swimming pool robot to move. According to this application, operating efficiency of the robot can be improved.

A controller 100 that calculates an operation quantity of an actuator 12 to move a mover 1 includes: a setter 22 that sets an instruction value to move the mover 1 to a target position; a restrictor 25 that sets a constraint condition of an instruction value for avoidance of an obstacle; a corrector 26 that corrects the instruction value to fall within a restricted range defined by the constraint condition if the instruction value is out of the restricted range; and an operation quantity calculator 28 that calculates the operation quantity based on the instruction value.