An unmanned aerial vehicle manages storage of data and transfer between other connected devices. The unmanned aerial vehicle captures sensor data from sensors on the unmanned aerial vehicle. The unmanned aerial vehicle transfers the captured sensor data from the unmanned aerial vehicle to a remote controller via a wireless interface. The captured data may be transferred via a TCP link, a UDP link, or a combination thereof. If a loss of link is detected, the captured sensor data is stored to a buffer and a battery level of the unmanned aerial vehicle and a flight status of the unmanned aerial vehicle is monitored. The stored sensor data is transferred from the buffer to a non-volatile storage responsive to the battery level dropping below a predefined threshold or detecting that the unmanned aerial vehicle is stationary and a shutdown may be imminent.

A utility vehicle includes: a travel structure including a front wheel, a rear wheel, a steering structure mounted to the front wheel, and a drive source that drives the front wheel and/or the rear wheel; circuitry that controls the travel structure to effect autonomous travel without manned operation in a given travel area; a route setter that sets a travel route for the autonomous travel; a vehicle location detector that detects a location of the utility vehicle; and a target detector that detects a monitoring target in the travel area. In case that the monitoring target is detected at a location during the autonomous travel, the circuitry stores the location of the monitoring target as history information. The route setter sets a reference point at the location where the monitoring target was detected and sets the travel route based on the reference point.

Overall efficiency and/or flight time of UAVs and Drones can be increased by adding elements containing lighter-than-air gasses; and/or by reducing and/or eliminating the power supplied to any combination of the motors to reduce overall power consumption. In an aspect the configuration of a blimp drone include at least one air cavity/chamber/container filled with lighter-than-air gasses. The 3D chambers are made from swept or extruded closed 2D geometry and are detachable from the Drone and can be transparent or camouflaged in color. To maintain control and altitude of the aircraft, lifting surfaces can be incorporated. Such lifting surfaces may include active and/or passive control surfaces to maintain flight stability. Additionally, cavities, fissures, orifices and valves may be added to the surface of the flying vehicle to gain other efficiency advantages.

A vehicle control system includes: an on-board control module, configured to control driving of the vehicle according to a control instruction sent by a vehicle dispatching command platform; a vehicle state module, configured to collect state information of the vehicle; an environment sensing module, configured to collect first road environment information of the vehicle; a UAV scanning module, configured to collect second road environment information of the vehicle; a data center module, configured to generate fusion information according to the state information, the first road environment information, and the second road environment information; a map module, configured to generate a driving route map of the vehicle according to the fusion information; and a vehicle dispatching command platform, configured to generate the control instruction according to the fusion information and the driving route map.

A modular aerial vehicle for inspection of enclosed and open space environments. The aerial vehicle is employed for inspection of various environments in remotely controlled and autonomous fashions. The aerial vehicle is capable of carrying different sensory modules depending on the specific application including surface inspection. Aerial vehicle may be connected to a tether cable for electrical power delivery and transmission of control commands. The aerial vehicle may utilize a landing structure which allows landing on any angled metallic or non-metallic surface.

A method and apparatus for aiding a police officer in writing a report by creating a depiction of an incident scene is provided herein. During operation a drone will photograph an incident scene from above. Relevant objects will be identified and a depiction of the incident scene will be created by overlaying the relevant photographed real world objects onto a map retrieved from storage. The depiction of the incident scene will be made available to police officers to increase the officers' efficiency in report writing. More particularly, officers will no longer need to re-create the depiction of the incident scene by hand. Instead, the officer will be able to use the depiction of the incident scene.

A system for an automated ML-based design of a wireless network. The system includes a processor of a design server node connected to at least one local, edge, or cloud server node over a network and a memory on which are stored machine-readable instructions that when executed by the processor, cause the processor to: acquire aerial 3-D mapping data of a target area from an unmanned aircraft system (UAS) flying over the target area; acquire surface 3-D mapping data from a ground robotic crawler; parse the 3-D mapping data to derive an at least one feature vector; provide the at least one feature vector to a machine learning (ML) module residing on the at least one local, edge, or cloud server node for generating a predictive model of a wireless network for some or all of the target area; receive outputs of the predictive model; and generate a wireless network design for the some or all of the target area based on the predictive outputs.

A method may include receiving a request for drone-assisted media capture from a vehicle located at a first location, the request specifying one or more user preferences, selecting an unmanned aerial vehicle that is able to perform the drone-assisted media capture based on the user preferences, causing the selected unmanned aerial vehicle to travel to the first location, and causing the selected unmanned aerial vehicle to capture media at the first location based on the user preferences.

Methods and apparatus are provided for allocating tasks to be performed by one or more autonomous vehicles to achieve a mission objective. Generally, a task allocation system identifies a final task associated with a given mission objective, identifies predecessor tasks necessary to complete the final task, generates one or more candidate tasks sequences to accomplish the mission objective, generates a task allocation tree based on the candidate task sequences, and searches the task allocation tree to find a task allocation plan that meets a predetermined selection criteria (e.g., lowest cost). Based on the task allocation plan, the task allocation system determines a task execution plan and generates control data for controlling one or more autonomous vehicles to complete the task execution plan.

A facility for automated modelling of the cutting process for a particular material to be cut by a beam cutting tool, such as a waterjet cutting system, from empirical data to predict aspects of the waterjet's effect on the workpiece across a range of material thicknesses, across a range of cutting geometries, and across a range of cutting quality levels, all of which may be broader than, and independent of the actual requirements for a target workpiece, is described.