A method for adaptive mission execution by an unmanned aerial vehicle includes receiving a set of pre-calculated mission parameters corresponding to an initial UAV mission; collecting UAV operation data during flight of the unmanned aerial vehicle; calculating a set of modified mission parameters from the set of pre-calculated mission parameters and the UAV operation data, the set of modified mission parameters corresponding to a modified UAV mission; and executing the modified UAV mission on the unmanned aerial vehicle.

An unmanned aerial vehicle is described and includes a computer carried by the unmanned aerial vehicle to control flight of the unmanned aerial vehicle and at least one sensor. The unmanned aerial vehicle is caused to fly to a specific location within a facility, where the unmanned aerial vehicle enters a hover mode, where the unmanned aerial vehicle remains in a substantially fixed location hovering over the specific location within the facility and sends raw or processing results of sensor data from the sensor to a remote server system.

A controller obtains a first horizontal distance and a first vertical distance which are respectively a component in a horizontal direction and a component in a vertical direction among distances from an unmanned aerial vehicle to a surface of a particular place where elevation gradually increases or decreases along the horizontal direction, decides, based on a ratio of the first horizontal distance to the first vertical distance, a movement amount by which the unmanned aerial vehicle is to be moved simultaneously in both the horizontal direction and the vertical direction, and moves the unmanned aerial vehicle based on the movement amount.

A 3D LIDAR obstacle avoidance system comprising a camera; a data processor; and a gimbaled laser ranging system. The gimbaled laser ranging system is bore sighted to the camera's optical axis and has its rotation axes centered on the camera focal plane (see the attached drawing). Two-dimensional information of the camera is converted to 3-dimensional information by selectively ranging scene objects of interest (i.e. moving targets). Selected object ranges are queried simply by commanding the gimbal to point to the angle in the scene represented by the object's location in the focal plane. By not sampling the entire scene, significant improvements in throughput and range are achieved. Sensor operation in inclement weather is possible by using an IR camera and a longer wavelength ranging-laser.

Systems and methods to detect objects and associated properties may be performed by an aerial vehicle having one or more propellers and one or more microphones. The aerial vehicle may emit propeller noise patterns via the propellers during operation, and the aerial vehicle may receive echoes of the propeller noise patterns via the microphones. Based on the emitted noise patterns and received echoes, the aerial vehicle may detect objects and associated properties within an environment of the aerial vehicle. In addition, the aerial vehicle may emit encoded propeller noise patterns via the propellers during operation to communicate with other aerial vehicles, and other aerial vehicles may receive the encoded propeller noise patterns via microphones. Using such encoded propeller noise patterns, a plurality of aerial vehicles may communicate and/or coordinate operations with each other.

The following relates generally to light detection and ranging (LIDAR). In some embodiments, an inventory list of personal belongings is generated based upon data received from a LIDAR camera. For instance, in some embodiments a system: receives LIDAR data generated from one or more LIDAR cameras; analyzes the LIDAR data to determine or identify one or more personal articles or insurable assets; and generates an electronic inventory list of personal belongings based upon the one or more personal articles or insurable assets determined or identified from the LIDAR data.

An apparatus for providing drone data provides a method of matching a user who needs drone data of a certain area with at least one provider capable of providing drone data of a part or the entirety of the certain area.

A management device allows: an information acquisition unit to acquire information that identifies an unmanned aerial vehicle that is an investigation target; a flight position determination unit to determine a flight position of the unmanned aerial vehicle that is the investigation target at a certain point in time; a search unit to search for one or more other unmanned aerial vehicles having a photographing function and positioned around the unmanned aerial vehicle that is the investigation target at the certain point in time; and an acquisition assist processing unit to assist acquisition of photographed data taken by the one or more other unmanned aerial vehicles that are searched for. Further, the management device may perform the above processing using communications through a blockchain network to cooperate with the blockchain network.

A method (110) for monitoring at least one aquaculture pond (112) is proposed. The method (110) comprises: a) monitoring at least one aerial parameter of use of the at least one aquaculture pond (112); b) determining a temporal development of the aerial parameter of use; and c) determining an intensity of use of the aquaculture pond (112) by using the temporal development of the aerial parameter of use.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for robot motion planning using unmanned aerial vehicles (UAVs). One of the methods includes determining that a current plan for performing a particular task with a robot requires modification; in response, generating one or more flight plans for an unmanned aerial vehicle (UAV) based on a robotic operating environment comprising the robot; obtaining, using the UAV in accordance with the one or more flight plans, a new measurement of the robotic operating environment comprising the robot; and generating, based at least on a difference between the new measurement of the robotic operating environment and a previous measurement of the robotic operating environment, a modified plan for performing the particular task with the robot.