A system for testing a plurality of electrical circuits includes a first remote cooperative testing device including a testing component and a first transceiver and a second remote cooperative testing device including a conductive component and a second transceiver. In response to receiving instructions from a remote computing device, the first remote cooperative testing device locates a first electrical circuit and a second electrical circuit and selectively positions the testing component to electrically couple a first portion of the first electrical circuit to a first portion of the second electrical circuit at a first node, and the second remote cooperative testing device selectively positions the conductive component to electrically couple a second portion of the first electrical circuit to a second portion of the second electrical circuit at a second node, thereby forming a testing circuit between the first node and the second node.

The present disclosure provides a system and device for drones with ducted rotors. In some aspects, drones may comprise one or more systems of ducted rotors. In some embodiments, ducted rotors may increase the durability of the drone, limiting exposure of the rotors to external conditions and objects. In some aspects, a drone with ducted rotors may comprise a control vane or cone that may direct airflow within the drone as a mechanism to control flight path. In some implementations, a drone may comprise expandable landing gear than may allow for controlled landing, even in the event of rotor failure. In some aspects, a drone may comprise rotatable ducted rotors.

Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an area surrounding a property, and collect data related to property. A location for an inspection of a property to be conducted by a UAV may be received, and one or more images depicting a view of the location may be displayed via a user interface. Additionally, a geofence boundary may be determined based on an area corresponding to a property boundary, where the geofence boundary represents a geospatial boundary in which to limit flight of the UAV. Furthermore, a navigation route may be determined which corresponds to the geofence boundary for inspection of the property by the UAV, the navigation route having waypoints, each waypoint indicating a location for the UAV to obtain drone data. The UAV may be directed around the property using the determined navigation route.

There is a remote control device or drone, which has software and a combination of lights or LED on an lighting ring or apparatus that can move independently of the drone; the drone can be programmed or be reactive to sound or other stimulus to create the effect of writing shapes or words in the air and typically at nighttime against a dark sky.

An apparatus for visual navigation of a UAV includes a geo-fiducial mat and a plurality of geo-fiducials. The geo-fiducial mat includes a landing pad region that provides a location for aligning with a landing pad of a UAV. The geo-fiducials each includes a two-dimensional (2D) pattern that visually conveys a code. The 2D pattern has a shape from which a visual navigation system of the UAV can visually triangulate a position of the UAV.

The present disclosure provides a method for detection of soil heavy metal pollution using an unmanned aerial vehicle (UAV) and an X-ray fluorescence (XRF) technology. Based. Based on hardware equipment such as the UAV, XRF analyzer, and embedded equipment, the present disclosure develops an altitude hold module of the system and a ground-contact monitoring module, and assists the UAV to achieve safe and accurate fixed-point hovering, and develops a driving device for data acquisition to replace manual control and realize the automatic acquisition of XRF data. The data inversion method is realized by using embedded equipment, and after the data is acquired by the portable XRF analyzer near the ground, the algorithm research of inversion processing of contents of heavy metal elements in soil is realized, such that the portable XRF analyzer can automatically and accurately detect the contents of heavy metals in soil at a certain distance.

An aerially controlled sludge level detection system is for determining a sludge level in a wastewater reservoir. The system may have a drone and a sludge level detection tool suspended from the drone. The drone may be operable to lower the sludge level detection tool into the wastewater reservoir and raise the sludge level detection tool out of the wastewater reservoir. The sludge level detection tool may have a longitudinally extending gauge. At least a portion of the gauge at a distal end may be hollow to allow a volume of a fluid and a volume of the sludge from within the wastewater reservoir to enter the gauge when lowered into the wastewater reservoir. The sludge level detection tool may also have an analyzer connected to the gauge for analyzing the volume of the fluid and the volume of the sludge within the gauge.

A method of inspection or maintenance of a curved ferromagnetic surface using an unmanned aerial vehicle (UAV) having a releasable crawler is provided. The method includes: flying the UAV from an initial position to a pre-perching position in a vicinity of the ferromagnetic surface; autonomously perching the UAV on the ferromagnetic surface; maintaining magnetic attachment of the perched UAV to the ferromagnetic surface; releasing the crawler from the magnetically attached UAV onto the ferromagnetic surface; moving the crawler over the curved ferromagnetic surface while maintaining magnetic attachment of the released crawler to the ferromagnetic surface; inspecting or maintaining the ferromagnetic surface using the magnetically attached crawler; and re-docking the released crawler with the perched UAV.

Unmanned aerial vehicles (UAVs) may be configured and deployed to maintain inventory and retrieve products for delivery. The UAVs can be equipped with a plurality of sensors used to assess the condition of inventory items, report the condition to a central control, and to retrieve inventory items. The UAVs can scan fruits and vegetables, for example, to determine the current ripeness. The UAV can then harvest the items if ready or provide a status update if they are not ready. The UAVs can be used in conjunction with transporters and harvesters to deliver products from the field or warehouse to a central control or directly to the customer. In scanning the products for readiness, the UAVs can also detect issues such as spoilage, fungus, and pests. This information can be used for the specific application of treatments.

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.