An automatic parking lot management system includes an infrastructure sensor for detecting a preset range in a parking lot. A mobile body including a peripheral detection sensor is used, and the mobile body is able to be moved to a detectable position at which the peripheral detection sensor of the mobile body is able to detect a detection range of the infrastructure sensor. When determination is made that there is an abnormality in the infrastructure sensor, the mobile body is moved to the detectable position to cause the peripheral detection sensor to detect the detection range of the infrastructure sensor.

An unmanned aerial vehicle (UAV) uses a first baseband processor to establish a first communication link with a ground station of a wireless network and a second baseband processor that establishes a second communication link with a user device. The second baseband processor for processing a radio transmission from a user equipment. The second baseband processor is communicatively coupled to the first baseband processor such that the radio transmission is communicated to the ground station via the first communication link. Flight-control hardware steers the UAV along a flight trajectory that is determined by a ground-based UAV controller based at least on the radio transmission, such that the UAV or the ground station can locate or track the user equipment.

A control system acquires predicted tsunami information, and generates a flight plan for unmanned aerial vehicles. The flight plan includes flight paths along safety boundaries between an expected damage area and a safe area. The expected damage is an area expected to be damaged by the tsunami indicated by the predicted tsunami information. The safe area is an area to be safe from damage caused by the tsunami. The control system transmits the flight plan to the unmanned aerial vehicles.

An unmanned aerial vehicle includes one or more magnetometers, configured to detect a magnetic field and to output magnetometer data corresponding to a magnitude of the detected magnetic field; a position sensor, configured to detect a position of the unmanned aerial vehicle relative to one or more reference points, and to output position sensor data representing the detected position; one or more processors, configured to control the unmanned aerial vehicle to rotate about its z-axis; receive magnetometer data comprising a plurality of z-axis directional measurements taken during the rotation about the z-axis; receive position sensor data and determine from at least the position sensor data a magnetic field inclination of the detected position; and determine a z-axis magnetometer correction value as a difference between the received magnetometer data for the z-axis and the determined magnetic field inclination.

The autonomous driving device including a communication circuit configured to communicate with an unmanned aerial vehicle, a plurality of sensors disposed in the autonomous vehicle to monitor all directions of the autonomous vehicle, and a processor, wherein the processor is configured to: control the unmanned aerial vehicle to hover at each of a plurality of waypoints of a designated flight path by controlling a relative position of the unmanned aerial vehicle through the communication circuit, change a posture angle of the unmanned aerial vehicle to a plurality of posture angles corresponding to the waypoints of the flight path, generate a plurality of images including the checkerboard and corresponding to the plurality of waypoints and the plurality of posture angles through the plurality of sensors, and calibrate the plurality of sensors on the basis of a relationship between matching points of the plurality of images.

A computer-implemented method for effective agriculture and environment monitoring. The method may comprise measuring a desired variable over an area of interest using a remote inspection platform according to an inspection plan, predicting an occlusion of the remote inspection platform, and in response to the predicted occlusion, determining whether to invoke a local inspection platform to complete the inspection plan. The occlusion in some embodiments interrupts the inspection plan for the remote inspection platform.

In some examples, an unmanned aerial vehicle (UAV) may receive location information via the global navigation satellite system (GNSS) receiver and may receive acceleration information via an onboard accelerometer. The UAV may determine a first measurement of acceleration of the UAV in a navigation frame of reference based on information from the accelerometer prior to or during takeoff. In addition, the UAV may determine a second measurement of acceleration of the UAV in a world frame of reference based on the location information received via the GNSS receiver prior to or during takeoff. The UAV may determine a relative heading of the UAV based on the first and second acceleration measurements. The determined relative heading may be used for navigation of the UAV at least one of during or after takeoff of the UAV.

A base unit (1), e.g. a luminaire, comprises fixation means (3, 5, 15) configured to fixate a module (11), e.g. a light module, in the base unit. The fixation means, e.g. comprising one or more protrusions (15), one or more recesses (3) and one or more magnetic field generators (5), is configured to release the module from the base unit upon detecting an unmanned aircraft (31) being docked with the base unit or the module.

An unmanned aerial vehicle (UAV) includes a sprayer configured to generate a pressurized fluid flow and a nozzle configured to receive the pressurized fluid from the sprayer and to generate a spray fan to apply the fluid to a surface. The UAV includes sensors and a control unit to control both flight of the UAV and spraying by the sprayer. The fluid can be stored onboard the UAV in a reservoir or can be remotely stored and pumped to the UAV. The UAV control unit can be preloaded with a spray plan and a flight plan, or the UAV can be controlled by a user.

The present invention is directed to methods and systems for determining a location of a vehicle within a geofence. The location of the vehicle is determined by a fencing agent on a vehicle. The geofence is defined by a plurality of geographic designators, with the plurality of geographic designators each being associated with an Internet Protocol (IP) address, preferably an IPv6 address.