An method for ice fishing using a submersible vehicle assembly and underwater powered observation system using a camera and source of light of a green laser to be directed to the underside of ice so as to locate the vehicle assembly and allow the user to cut a hole in the ice at or near fish. In this manner the vehicle assembly may be utilized for the underwater tasks of locating fish and/or observing fish under the ice. Additional features include identifying water temperature and depth information that may be displayed on the control unit, a hydrophobic coating preventing ice buildup, and a stand adaptable for resting on the bottom during use.

A vehicular collision avoidance system includes a first image processor that processes image data captured by a forward-viewing camera to detect vehicles and determine vehicles present in the occupied lane and adjacent lane, and a second image processor that processes image data captured by a rearward-viewing camera to detect the presence of vehicles and determine vehicles present in the occupied lane and adjacent lane. Information relating to the vehicles is wirelessly transmitted between the vehicles. Responsive at least in part to at least one of (i) image processing of image data captured by the forward-viewing camera and/or rearward-viewing camera, (ii) sensor data sensed by at least one other sensor, and (iii) information transmitted to or from the equipped vehicle via the car2car (v2v) communication system, the collision avoidance system is operable to determine imminence of collision with the equipped vehicle by another vehicle present exterior the equipped vehicle.

A driver warning system automatically detects the existence of in-the-road, passable obstructions and provides timely notification to a driver in proximity of such an in-the-road, passable obstruction prior to it being encountered with sufficient warning time for the driver to avoid the in-the-road, passable obstruction. To detect in-the-road, passable obstructions, the warning unit of a driver whose vehicle hits an in-the-road, passable obstruction will automatically generate a signal that is indicative of the existence of the in-the-road, passable obstruction and its location. This signal may be transmitted to a server, which contains a database of located obstructions. The collected information about the detected in-the-road, passable obstructions are provided to various warning units, so that they, knowing the driver location, e.g., based on global positioning system (GPS), can provide the driver with a warning of any upcoming in-the-road, passable obstructions with sufficient lead time for the driver to avoid hitting the obstruction.

A system for actively damping a power steering system includes a damping activation module that generates a damping activation signal based on a motor velocity signal, a t-bar torque signal, and a final motor command; a command calculation module that generates a calculated command based on the motor velocity signal and a vehicle speed signal; and a damping calculation module that generates a damping command based on the damping activation signal and the calculated command, the damping command reduces a motor velocity of a motor of the power steering system to mitigate a rack disturbance.

Proposed is a control method of an underwater robot equipped with a multi-degree-of-freedom robot arm according to an exemplary embodiment, including: a) step 1-1th of obtaining a propulsive force prediction value by predicting a propulsive force of the underwater robot based on an artificial neural network and configuring a sensorless propulsion controller equipped with a propulsion system to control a speed of the underwater robot; and b) step 1-2th of configuring a underwater robot manipulator (URM) controller that obtains a torque prediction value by predicting an output torque of an actuator constituting the multi-degree-of-freedom robot arm provided in the underwater robot based on the artificial neural network.

Proposed is a control method of an underwater robot equipped with a multi-degree-of-freedom robot arm according to an exemplary embodiment, including: a) step 1-1th of obtaining a propulsive force prediction value by predicting a propulsive force of the underwater robot based on an artificial neural network and configuring a sensorless propulsion controller equipped with a propulsion system to control a speed of the underwater robot; and b) step 1-2th of configuring a underwater robot manipulator (URM) controller that obtains a torque prediction value by predicting an output torque of an actuator constituting the multi-degree-of-freedom robot arm provided in the underwater robot based on the artificial neural network.

A vehicle drive-control device which executes trajectory control in which steered wheels are controlled so as to make the vehicle travel along a target trajectory. When the possibility exists that the travel direction of the vehicle may be changed by the trajectory control, at least one of an operation position of a steering input unit operated by a driver; a yaw angle of the vehicle; and a lateral position of the vehicle with respect to a lane is changed before a change in the travel direction is made, thereby giving occupants in the vehicle advance notice of the possibility of a change in vehicle travel direction caused by the trajectory control.

Information display is performed, in which recognizability of information regarding a driving support control is relatively good even in a situation where a driving load is relatively large, the information display not annoying a driver. A display controller displays a support state displaying image, which is an image having a configuration in which a vehicle image is superimposed on a mesh image as a mesh-like planar image, on a liquid crystal display device provided in a meter panel of a meter device. In addition, upon having determined that a driving support control implemented by a driving support device is operating, the display controller performs a display control to change a display mode of a mesh image portion of the support state displaying image, which is to be displayed on the liquid crystal display device, to a preset display mode.

An unmanned water vessel can include a body defining an internal volume and having a shape adapted to travel through water, with a front and a back; at least one directional device that is exposed to the flow of water past the vehicle when the vehicle travels in a forward direction, the directional device having a first position that provides an angle of attack through the water flow and a second position that provides a second angle of attack through the water flow; and a control system that provides commands to the at least one directional device in view of a starting point, an end point, and at least information about water flow expected to be encountered by the water vessel during travel.

An unmanned water vessel can include a body defining an internal volume and having a shape adapted to travel through water, with a front and a back; at least one directional device that is exposed to the flow of water past the vehicle when the vehicle travels in a forward direction, the directional device having a first position that provides an angle of attack through the water flow and a second position that provides a second angle of attack through the water flow; and a control system that provides commands to the at least one directional device in view of a starting point, an end point, and at least information about water flow expected to be encountered by the water vessel during travel.