Techniques are disclosed for communicating between a client device and an onboard data manager in a movable object environment. A data manager on a user device can identify an onboard data manager on a movable object. A feature list can be received from the onboard data manager, the feature list identifying at least one feature installed to the movable object. At least one input can be received by the user device, and a user device feature corresponding to the at least one input can be determined. It may be further determined that the user device feature is supported by the onboard data manager based on the feature list. In response to determining that the user device feature is supported, a first instruction corresponding to the at least one input can be sent to the movable object including the onboard data manager.

Example implementations may relate to self-deployment of operational infrastructure by an unmanned aerial vehicle (UAV). Specifically, a control system may determine operational location(s) from which a group of UAVs is to provide aerial transport services in a geographic area. For at least a first of the operational location(s), the system may cause a first UAV from the group to perform an infrastructure deployment task that includes (i) a flight from a source location to the first operational location and (ii) installation of operational infrastructure at the first operational location by the first UAV. In turn, this may enable the first UAV to operate from the first operational location, as the first UAV can charge a battery of the first UAV using the operational infrastructure installed at the first operational location and/or can carry out item transport task(s) at location(s) that are in the vicinity of the first operational location.

Provided is an air cleaner that can take a large amount of air in a large space into a dust collector with good efficiency while being lightweight and having easy maintenance. An air cleaner is provided with a drone and a dust collector. The drone has a main body unit and propellers attached to the tips of frames. The dust collector has electric discharge electrodes and a dust collection electrode. The electric discharge electrodes are connected to a booster unit within a central chamber. The booster unit is electrically connected to a control unit in the main body unit. Electric discharge is formed between the dust collection electrode and the electric discharge electrodes, and dust particles in the air are charged and collected by the dust collection electrode.

A method for image-guided agriculture includes capturing images based on one or more ground sampling distance values; processing the images to generate an orthophoto image of a target area; performing feature classification of the orthophoto image to identify corresponding crop information in regions of the target area; and assessing crop conditions in the regions based on one or more vegetation indices and the corresponding crop information in the regions.

Systems and methods are described herein for determining an optimized flight route for an aerial vehicle. In some examples, weather conditions for the aerial vehicle during a flight can be predicted based on weather data. At least two flight route segments based on the predicted weather data can be determined. The at least two flight route segments can include one of a solar flight route segment and a thermal flight route segment. A respective flight route segment of the at least two flight route segments can be discarded that can cause the aerial vehicle to violate a flight constraint. A replacement flight route segment for the respective discarded flight route segment can be determined. An optimized flight route for the aerial vehicle can be generated based on the replacement flight route segment and at least one remaining flight route segment of the at least two flight route segments.

An aerial vehicle includes a radio transceiver device configured for radio transmission in a set of radiation directions. The aerial vehicle includes a mechanical shield positioned to reduce power of the radio transmission in at least some of the radiation directions in the set of radiation directions. The aerial vehicle further includes a controller configured to control at least one of: movement of the aerial vehicle, movement of the mechanical shield, radio communication of the aerial vehicle via the radio transceiver device.

Embodiments described herein provide various examples of real-time visual object tracking. In another aspect, a process for performing a local re-identification of a target object which was earlier detected in a video but later lost when tracking the target object is disclosed. This process begins by receiving a current video frame of the video and a predicted location of the target object. The process then places a current search window in the current video frame centered on or in the vicinity of the predicted location of the target object. Next, the process extracts a feature map from an image patch within the current search window. The process further retrieves a set of stored feature maps computed at a set of previously-determined locations of the target object from a set of previously-processed video frames in the video. The process next computes a set of correlation maps between the feature map and each of the set of stored feature maps. The process then attempts to re-identify the target object locally in the current video frame based on the set of computed correlation maps.

An aircraft includes at least one sensor, an altitude actuator, a memory device, and an electronic controller. The at least one sensor is configured to detect altitude of the aircraft, current position of the aircraft and speed of the aircraft. The altitude actuator is configured to change the altitude of the aircraft. The memory device is configured to store predetermined terrain data of an area. The electronic controller is configured to estimate a future position of the aircraft based on a detected current position of the aircraft and a detected speed of the aircraft. The electronic controller is further configured to control the altitude actuator based on the future position, a detected altitude of the aircraft and the predetermined terrain data.

Systems, methods, and other embodiments described herein relate to a drone having selectively actuated arms. In one embodiment, a drone includes arms connected to a body. Individual ones of the arms have a first end and a second end with the first end forming a connection with the body. The drone further includes rotor units individually including a propeller attached to a motor and mounted to the second end of the individual ones of the arms. Additionally, actuator units are integrated with the arms. Individual ones of the actuator units include electromagnetic cells that when activated induce an electromagnetic motive force that flexes the arms.

An unmanned aerial vehicle may include: a sensor part configured to acquire inertia information or position information of the unmanned aerial vehicle; and a controller. The controller is configured to estimate the position of the unmanned aerial vehicle by applying the information acquired by the sensor part to an extended Kalman filter and control movement of the unmanned aerial vehicle, based on the estimated position of the unmanned aerial vehicle. The sensor part includes: an inertia sensor configured to acquire the inertia information of the unmanned aerial vehicle; a tag recognition sensor configured to recognize a tag attached to a rack and acquire absolute position information of the unmanned aerial vehicle; and an image sensor attached to the unmanned aerial vehicle so as to acquire an image of the movement environment of the unmanned aerial vehicle.