A method according to certain embodiments generally involves operating a system including an unmanned aerial vehicle (UAV) and a base station. The base station includes a nest including an upper opening having an upper opening diameter and a lower opening having a lower opening diameter less than the upper opening diameter. The lower opening is accessible from within the base station. The method generally includes landing the UAV within the nest such that a portion of the UAV is accessible via the lower opening, releasably attaching a load to the UAV, and operating the UAV to deliver the load to a destination.

A method according to certain embodiments generally involves operating a system including an unmanned aerial vehicle (UAV) and a base station. The base station includes a nest including an upper opening having an upper opening diameter and a lower opening having a lower opening diameter less than the upper opening diameter. The lower opening is accessible from within the base station. The method generally includes landing the UAV within the nest such that a portion of the UAV is accessible via the lower opening, releasably attaching a load to the UAV, and operating the UAV to deliver the load to a destination.

Systems and methods for automatically identifying and ascertaining an estimated amount of damage at a location by utilizing one or more autonomous vehicles, e.g., drone devices, to autonomously capture data of the location and utilizing Artificial Intelligence (AI) logic modules to analyze the captured data and construct a 3-D model of the location.

Systems and method for providing navigational control of a watercraft are provided herein. The system comprises a display, processor and memory. The memory including computer program code is configured to cause presentation of a chart on the display including at least a portion of the body of water. The system further receives user input indicating initiation of a drift protocol, including indication of a boundary area for which the watercraft will drift through, and causes presentation of the boundary area on the chart. The system determines an instance when the watercraft drifts outside of the boundary area and provides an alert when the watercraft exits or nears the boundary area. The system determines a starting position corresponding to the boundary area and engages an autopilot to cause the watercraft to navigate to the starting position or provides instructions to enable the user to navigate the watercraft to the starting position.

To reduce environmental influence in flight (including taking-off and landing) of a flying object, main drone current position information acquisition unit acquires a current position of a main drone from a main drone control terminal, and provides the current position to the movement instruction unit. The sub-drone current position information acquisition unit acquires a current position from the sub-drone, and provides it to the movement instruction unit. The movement instruction unit determines a movement position of the sub-drone on the basis of the current position of the main drone. In addition, the movement instruction unit generates a movement instruction for the sub-drone based on a difference between the current position and the movement position of the sub-drone, and transmits the movement instruction to the sub-drone. The drive control unit acquires the movement instruction transmitted from the sub-drone control terminal.

An apparatus for artificial intelligence (AI) bathymetry is disclosed. The apparatus includes a sonic unit attached to a boat, the sonic unit configured to generate a plurality of metric data as a function of a plurality of ultrasonic pulses and a plurality of return pulses. An image processing module is configured to generate a bathymetric image as a function of the plurality of metric data, identify, as a function of the bathymetric image, an underwater landmark, and register the bathymetric image to a map location as a function of the underwater landmark. A communication module is configured to transmit the registered bathymetric image to at least a computing device. An autonomous navigation module is configured to determine a heading for the boat as a function of a path datum and command boat control to navigate the boat as a function of the heading.

A specific object is quickly detected to improve safety of flight. A control unit of an unmanned aerial vehicle control system obtains an image in which surroundings of an unmanned aerial vehicle are captured, the unmanned aerial vehicle being movable in any direction. A control unit for obtaining movement direction information about a movement direction of the unmanned aerial vehicle. A control unit for specifying a part to be processed in the image based on the movement direction information. A control unit for performing detection processing on the part to be processed to detect a specific object. A flight control unit for controlling flight of the unmanned aerial vehicle based on a result of the detection processing.

Methods, systems and apparatus, including computer programs encoded on computer storage media for unmanned aerial vehicle beyond visual line of sight (BVLOS) flight operations. In an embodiment, a flight planning system of an unmanned aerial vehicle (UAV) can identify handoff zones along a UAV flight corridor for transferring control of the UAV between ground control stations. The start of the handoff zones can be determined prior to a flight or while the UAV is in flight. For handoff zones determined prior to flight, the flight planning system can identify suitable locations to place a ground control station (GCS). The handoff zone can be based on a threshold visual line of sight range between a controlling GCS and the UAV. For determining handoff zones while in flight, the UAV can monitor RF signals from each GCS participating in the handoff to determine the start of a handoff period.

Methods, systems and apparatus, including computer programs encoded on computer storage media for unmanned aerial vehicle beyond visual line of sight (BVLOS) flight operations. In an embodiment, a flight planning system of an unmanned aerial vehicle (UAV) can identify handoff zones along a UAV flight corridor for transferring control of the UAV between ground control stations. The start of the handoff zones can be determined prior to a flight or while the UAV is in flight. For handoff zones determined prior to flight, the flight planning system can identify suitable locations to place a ground control station (GCS). The handoff zone can be based on a threshold visual line of sight range between a controlling GCS and the UAV. For determining handoff zones while in flight, the UAV can monitor RF signals from each GCS participating in the handoff to determine the start of a handoff period.

Various embodiments of a vision-guided unmanned aerial vehicle (UAV) system to identify and collect foreign objects from the surface of a body of water are disclosed herein. A vision system and methodology has been developed to reduce reflections and glare from a water surface to better identify an object for removal. A linearized polarization filter and a specularity-removal algorithm is used to eliminate excessive reflection and glare. A contour-based detection algorithm is implemented for detecting the targeted objects on water surface. Further, the system includes a boundary layer sliding mode control (BLSMC) methodology to reduce and minimize position and velocity errors between the UAV and object in the presence of modeling and parameter uncertainties due to variation in a moving water surface.