The present invention relates to methods, computer program products and computing devices for calibrating a Digital Twin for an autonomous vehicle using machine learning and to the use of the calibrated Digital Twin to both tune at least one controller, navigation algorithms and/or guidance algorithms for an autonomous vehicle using machine learning and to optimising a vehicle shape of an autonomous vehicle using machine learning.

The moving body of the present invention is a moving body that has a weight of 300 kg or less and is activated by a user to move, the moving body comprising: a movement mechanism for moving; a communication unit for performing communication; a control unit that controls the moving mechanism so that the moving body moves when communication between the communication unit and an external communication device is not possible; and an attachment for fixing, wherein the control unit controls the moving mechanism so that the moving body moves when fixation by the attachment is released, and wherein the communication unit transmits user-related information, which is information related to the user, to the external communication device when the communication between the communication unit and the external communication device is possible.

The moving body of the present invention is a moving body that has a weight of 300 kg or less and is activated by a user to move, the moving body comprising: a movement mechanism for moving; a communication unit for performing communication; a control unit that controls the moving mechanism so that the moving body moves when communication between the communication unit and an external communication device is not possible; and an attachment for fixing, wherein the control unit controls the moving mechanism so that the moving body moves when fixation by the attachment is released, and wherein the communication unit transmits user-related information, which is information related to the user, to the external communication device when the communication between the communication unit and the external communication device is possible.

The present invention relates to an unmanned aerial vehicle (UAV) for agricultural weed management. The UAV comprises a control and processing unit (20), and a camera (30). The control and processing unit is configured to control the UAV to fly to a location inside the canopy of a crop and below the vertical height of the crop and/or between a row of a plurality of crops and below the vertical height of the plurality of crops. The control and processing unit is configured to control the camera to acquire at least one image relating to the ground at the location inside the canopy of a crop and below the vertical height of the crop and/or between a row of a plurality of crops and below the vertical height of the plurality of crops. The control and processing unit is configured to analyse the at least one image to determine the presence of at least one weed and its location on the ground.

The present invention relates to an unmanned aerial vehicle (UAV) for agricultural weed management. The UAV comprises a control and processing unit (20), and a camera (30). The control and processing unit is configured to control the UAV to fly to a location inside the canopy of a crop and below the vertical height of the crop and/or between a row of a plurality of crops and below the vertical height of the plurality of crops. The control and processing unit is configured to control the camera to acquire at least one image relating to the ground at the location inside the canopy of a crop and below the vertical height of the crop and/or between a row of a plurality of crops and below the vertical height of the plurality of crops. The control and processing unit is configured to analyse the at least one image to determine the presence of at least one weed and its location on the ground.

A vehicle, such as a micro-aerial vehicle or underwater vehicle, includes at least one lift structure, such as a low-aspect-ratio wing or a fin, respectively. The at least one lift structure comprises one or more alulas. A leading surface of each alula is (a) flush with a leading surface of the lift structure or (b) offset from the leading edge of the lift surface by up to approximately 10% of the chord length of the lift structure. The length of each alula is no more than approximately 20% of a lift structure length corresponding to the lift structure. In various embodiments, the alula is deflected or canted with respect to a plane defined by the lift structure. In an example embodiment, the alulas may be slid or translated along at least a portion of the span of the lift structure.

A spectroscopy system including a base station having a reflecting telescope and a laser light source coupled to the telescope, the laser providing an outgoing light signal; at least one Unmanned Aerial Vehicle containing a mobile retroreflector configured to receive the light signal from the laser and return a light signal back to the telescope; a detector to record the intensity of the returning light signal; and optical components for spectroscopic measurements, the optical components utilizing the intensity of the returning light signal, revealing the presence of a chosen narrow band for the purpose of detecting a target.

A spectroscopy system including a base station having a reflecting telescope and a laser light source coupled to the telescope, the laser providing an outgoing light signal; at least one Unmanned Aerial Vehicle containing a mobile retroreflector configured to receive the light signal from the laser and return a light signal back to the telescope; a detector to record the intensity of the returning light signal; and optical components for spectroscopic measurements, the optical components utilizing the intensity of the returning light signal, revealing the presence of a chosen narrow band for the purpose of detecting a target.

Systems and methods for deconflicting small Unmanned Aircraft Systems (sUAS) within a domain. One example system includes a plurality of UAM/AAM vehicles; and a processor configured to: receive environmental data for a domain, the environmental data determined based on operational weather prediction models or weather observations; process the environmental data through an atmospheric model of the domain to determine mesoscale and microscale weather forecast data for the domain and a positional uncertainty of the sUAS vehicles within the domain; generate a Weighted Graph that describes and spans a plurality of possible sUAS vehicle routes over the domain; determine a route and a corresponding flight schedule for at least one of sUAS vehicles within the domain based on the Weighted Graph; and provide the route and the corresponding flight schedule to the at least one of the sUAS vehicles.

A projectile-launched aircraft system includes a projectile launcher including a triggering mechanism, a rotary-wing, hover-capable aircraft including a rotor assembly that includes at least one rotor blade, wherein the rotor blade includes a stowed configuration and a deployed configuration that is circumferentially spaced from the stowed configuration about a pivot axis, wherein, upon actuation of the triggering mechanism, the projectile launcher is configured to launch the aircraft along a flightpath.