Systems and methods to maintain a fleet of aerial vehicles may include a maintenance system, a charging power source, and a control system. For example, the maintenance system may include a plurality of workstations to perform maintenance tasks, a charging rail that connects the workstations with the charging power source, and a plurality of platforms that move along the charging rail. The control system may instruct a platform to receive an aerial vehicle, couple the aerial vehicle to the charging rail, move the aerial vehicle among the workstations, and charge a battery of the aerial vehicle via the charging rail during movement and/or performance of various maintenance tasks.

Embodiments of the present disclosure are directed to systems and methods for autonomously performing and/or facilitating drone diagnostic functions. Prior to a mission of a UAV, an inspection station comprising at least one imaging sensor and at least one directional force sensor may be used to perform a plurality of air worthiness inspections and/or maintenance checks with little to no human intervention. Once the UAV has been determined to be air worthy, it is approved for a subsequent mission.

The invention is intended for the organization of an automated process for spraying of liquid means of chemical treatment from unmanned vehicles, for example, in precise farming systems. The use of a replaceable, marked and hermetically sealed liquid subsystem in the spray device of the invention, along with an integrated self-diagnosis system, using compressed gas energy and a pressure regulator instead of standard pumps, reduces the weight of the spraying device, improves spraying accuracy, ensures personnel safety and accounting of the accumulated life resource of the main units of spraying devices. All this in combination enables to create fully automated spraying systems.

Intermodal vehicles may be loaded with items and an aerial vehicle, and directed to travel to areas where demand for the items is known or anticipated. The intermodal vehicles may be coupled to locomotives, container ships, road tractors or other vehicles, and equipped with systems for loading one or more items onto the aerial vehicle, and for launching or retrieving the aerial vehicle while the intermodal vehicles are in motion. The areas where the demand is known or anticipated may be identified on any basis, including but not limited to past histories of purchases or deliveries to such areas, or events that are scheduled to occur in such areas. Additionally, intermodal vehicles may be loaded with replacement parts and/or inspection equipment, and configured to conduct repairs, servicing operations or inspections on aerial vehicles within the intermodal vehicles, while the intermodal vehicles are in motion.

Systems and methods are provided for autonomous robotic surgery which is preferably integrated with autonomous-assisted intraoperative real-time single modality and/or multi-modality fusion imaging/electrophysiological diagnostics. The robotic surgery systems and methods can be integrated with autonomous-assisted intraoperative body/limb positioning, and integrated with autonomous-assisted land and unmanned aerial vehicular patient transportation.

Intermodal vehicles may be loaded with items and an aerial vehicle, and directed to travel to areas where demand for the items is known or anticipated. The intermodal vehicles may be coupled to locomotives, container ships, road tractors or other vehicles, and equipped with systems for loading one or more items onto the aerial vehicle, and for launching or retrieving the aerial vehicle while the intermodal vehicles are in motion. The areas where the demand is known or anticipated may be identified on any basis, including but not limited to past histories of purchases or deliveries to such areas, or events that are scheduled to occur in such areas. Additionally, intermodal vehicles may be loaded with replacement parts and/or inspection equipment, and configured to conduct repairs, servicing operations or inspections on aerial vehicles within the intermodal vehicles, while the intermodal vehicles are in motion.

System and methods for managing one or more unmanned aerial vehicles. The system can include an unmanned aerial vehicle, a landing station for the unmanned aerial vehicle, and a loading station for receiving a package and unmanned aerial vehicle. The unmanned aerial vehicle can be configured to: (i) determine a first confidence level for landing on the landing station, (ii) travel, based on the first confidence level, to the landing station, and (iii) determine a second confidence level for delivering the package to a delivery destination. The loading station can be configured to: (i) receive the second confidence level to deliver the package to the delivery destination from the unmanned aerial vehicle, and (ii) confirm, based on the second confidence level, the unmanned aerial vehicle is capable of delivering the package to the delivery destination.

In one embodiment, a self-describing fiducial includes a communication element that optically communicates navigation-aiding information. The navigation-aiding information may include a position of the self-describing fiducial with respect to one or more coordinate systems and the communication element communicates the navigation-aiding information to one or more navigating objects in the vicinity of the self-describing fiducial. In another embodiment, the communication element is further configured to communicate supplementary information describing a spatial relationship between the self-describing fiducial and the surrounding environment.

The disclosure describes embodiments for selecting, for a flying autonomous robot (a flying drone), a connected vehicle to land on so that a flying range of the flying autonomous robot is improved (e.g., increased). In some embodiments, a method includes receiving, by the flying autonomous robot, a Vehicle-to-Everything (V2X) message including digital data describing the connected vehicle. The method includes modifying a flight path of the flying autonomous robot based on the digital data so that the flight path approaches the connected vehicle.

In some examples, an unmanned aerial vehicle (UAV) may determine a first acceleration of the UAV based at least on information from an onboard accelerometer received at least one of prior to or during takeoff. The UAV may determine a second acceleration of the UAV based at least on location information received via a satellite positioning system receiver at least one of prior to or during takeoff. The UAV may further determine a relative heading of the UAV based at least in part on the first acceleration and the second acceleration, and may be directed to navigate an environment based at least on the determined relative heading.