Methods and apparatus to guide an unmanned aerial vehicle for recovery thereof are disclosed. A disclosed example apparatus to recover an aircraft or a payload thereof includes a tether line, and markers supported by the tether line at different positions of the tether line, the markers to be detected by the aircraft, the aircraft to be guided to engage the tether line by determining positions of the markers and calculating a position of at least a portion of the tether line based on the determined position of the markers.

A system performs a control method to launch an unmanned aerial vehicle, UAV. The control method includes calculating a selected altitude, relative to a reference level, for launching the UAV, operating a lifting arrangement to vertically elevate the UAV to the selected altitude, and causing the UAV to be launched from the selected altitude. Elevating the UAV may improve the performance of the UAV in terms of range, power consumption, ability to carry payload, transit time to destination, etc. The selected altitude may be calculated as a function of parameter data representing any of the UAV, the lifting arrangement, or surrounding conditions. An apparatus is further provided to determine an optimal location of the system in relation to a plurality of destinations of UAVs to be elevated by the system.

Disclosed here are methods and systems for automatically operating automated vehicles moving through vegetation obstacles with minimal damage, comprising receiving image(s) depicting vegetation obstacle(s) blocking at least partially a path of an automated vehicle executing a mission, analyzing the image(s) to extract one or more obstacle attributes of the vegetation obstacle(s), computing a plurality of movement patterns for operating the automated to cross the vegetation obstacle(s) based on one or more vehicle attributes of the automated vehicle with respect to one or more of the obstacle attributes where each movement pattern defines one or more movement parameters of the automated vehicle, selecting one of the movement patterns estimated to reduce a cost of damage to the automated vehicle and/or to the one or more vegetation obstacles, and outputting instructions for operating the automated vehicle to move through the vegetation obstacle(s) according to the selected movement pattern.

An autonomous vehicle system includes a body and a plurality of sensors coupled to the body and configured to generate a plurality of sensor measurements corresponding to the plurality of sensors. The system also includes a control unit configured to: receive inputs from a plurality of sources wherein the plurality sources comprise the plurality of sensors, the inputs comprise the plurality of sensor measurements; determine a confidence level of each input based on other inputs; prioritize, based on the confidence level associated with each input, the inputs; generate, based on the prioritization of the inputs and the confidence level, a combined input with a combined confidence level; and determine, based on the combined input and the combined confidence level, a mission task to be performed.

A system for an unmanned aerial vehicle can include an altitude control system, which further includes a compressor assembly, a valve assembly, and an electronics assembly. The compressor assembly may include a driveshaft and a bearing assembly configured to rotate the driveshaft. The driveshaft may be formed from a first material and a compressor housing may be formed from a second material. The first and second materials may have different rates of thermal expansion. A dynamic preloading mechanism, such as a flexible plate, may be provided within the compressor assembly to exert a preloading force on the bearing assembly. Throughout the duration of the flight of the unmanned aerial vehicle, the preloading mechanism can continually compensate for differences in rates of thermal expansion between the first and second materials throughout.

A semiautonomous robot. The robot includes at least two powered locomotion devices and a monocular capture unit. The at least two locomotion devices are designed to rotate at least the capture unit about a rotational axis, which is situated in a fixed position relative to the capture unit, the capture unit and the rotational axis being set apart from each other. The robot further includes at least one control and/or regulating unit for ascertaining a distance traveled. As a function of a movement of the capture unit about the rotational axis fixed during the movement, in particular, at a known distance from the rotational axis and/or in a known orientation relative to the rotational axis, the control and/or regulating unit is configured to determine a distance conversion parameter, which is provided for ascertaining the distance traveled.

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.

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.