Aerodynamic hazard mitigation for unmanned aircraft

Abstract

An unmanned aircraft system (UAS) 300 comprising: an interface 310 configured to interface with an onboard control system of an unmanned aircraft to supply restriction zone data to the onboard control system such that, in operation of the unmanned aircraft, the onboard control system of the unmanned aircraft is operative to modify inflight behaviour of the unmanned aircraft and / or provide information to an operator of the unmanned aircraft, based on the restriction zone data. Also provided is a method of providing restriction zone data to a UAS, performed by a modelling system external to the UAS. The method comprises: calculating, using a fluid dynamics simulation performed by the external modelling system, air flow field data based on a 3D model of a target operational environment for an unmanned aircraft and simulated wind conditions. Then determining hazard data from the air flow field data; and transmitting restriction zone data to a data platform or an unmanned aircraft system for use in modifying in-flight behaviour of an unmanned aircraft. The restriction zone data comprises the hazard data or wherein the restriction zone data defines restriction zones based on the hazard data.

Description

Field of the Invention The present disclosure relates to systems, methods and apparatus for operating an unmanned aircraft. In particular, the present disclosure relates to systems, methods and apparatus for aerodynamic hazard mitigation for unmanned aircraft. Background An unmanned aircraft system (UAS) typically comprises an unmanned aircraft (which may also be referred to as an unmanned aerial vehicle (UAV) or drone), a remote control station, and a communication link facilitating communication between the unmanned aircraft and the remote control station. Unmanned aircraft can take a variety of forms, from small recreational drones to large delivery systems. Additionally, a number of organisations are developing commercial unmanned passenger aircraft. Flight control in unmanned aircraft systems may be performed manually (where an operator controls the unmanned aircraft remotely) or autonomously (where the unmanned aircraft is given a mission and executes that mission without the direct control of an operator). Most commercial unmanned aircraft use an onboard flight control system that is based on one of a small number of autopilot / flight control software options such as ArdiPilot, PX4, iNavFIight, Libre Pilot or Paparazzi UAV. The onboard flight control system may include a collision avoidance system configured to detect physical hazards such as buildings or other unmanned aircraft (using information from onboard sensors such as radar sensors, LIDAR sensors, and optical cameras) and to control the unmanned aircraft to avoid such detected hazards. As the use of unmanned aircraft has expanded, the environments in which they operate have become more complex. For example, delivery drones may fly in urban environments, industrial inspection drones mayfly near large buildings and complex infrastructure such as wind turbines, and camera drones may fly near 5 large structures. As well as presenting physical hazards, these complex environments can create complex aerodynamic hazards, for example turbulence in regions around a large building. Aerodynamic hazards such as turbulence, wind, vortices, shear layers or other 10 aerodynamic features can have a major impact on unmanned aircraft. The inability of a flight control system to compensate for such aerodynamic hazards can lead to a loss of control of the unmanned aircraft, potentially leading to loss of the unmanned aircraft and / or damage to people and property. Current flight control systems and software for unmanned aircraft do not recognise the concept 15 of aerodynamic hazards, and existing unmanned aircraft do not have onboard sensors capable of sensing such hazards. Avoiding aerodynamic hazards thus currently relies on operator experience and may not be accounted for in mission planning. Summary The inventors have determined that an onboard control system of an unmanned aircraft may be modified to accept hazard data originating not from a physical sensor onboard the unmanned aircraft, but from a non-sensed hazard data source such as an external modelling system, e.g. a computational fluid dynamics (CFD) modelling system. Hazard data corresponding to aerodynamic hazards can be supplied to an unmanned aircraft in a range of formats (e.g. points, geometric primitives, bounded volume hierarchies, and others) via a communications link. In operation of the unmanned aircraft, the collision avoidance system of the unmanned aircraft can interpret the received hazard data as data indicative of a physical hazard to be avoided or otherwise mitigated, and can control operation of the unmanned aircraft accordingly. Additionally or alternatively, the onboard control system of the unmanned aircraft, or a remote control station for controlling the unmanned aircraft, may define one or more explicit restriction zones (e.g. prior to a flight or mission of the unmanned aircraft), based on the received hazard data, and may supply restriction zone data defining the restriction zones to the unmanned aircraft to enable the unmanned aircraft to avoid or mitigate aerodynamic hazards that may be present in the defined restriction zones that may not be detectable by its on-board sensors. As used herein, the term “restriction zone” refers to a zone or region of a target operational environment for the unmanned aircraft that may contain aerodynamic hazards such as turbulence, wind, vortices, shear layers or other aerodynamic features which should be avoided or otherwise mitigated by the unmanned aircraft. As used herein, the term “aerodynamic hazard” means any non-structural environmental condition that could affect unmanned aircraft flight and / or stability, such as (and without limitation) turbulence, wind, vortices, shear layers or other aerodynamic features. The unmanned aircraft is thereby able to safely avoid (e.g. navigate around) or otherwise mitigate hazards such as aerodynamic flow features that could potentially damage the unmanned aircraft and / or its payload, and / or endanger the surrounding environment or people. The systems, methods and apparatus of the present disclosure thus enable unmanned aircraft to avoid, mitigate or otherwise respond to aerodynamic hazards while flying. Thus, according to a first aspect, the invention provides an unmanned aircraft system comprising: an interface configured to interface with an onboard control system of an unmanned aircraft to supply restriction zone data to the onboard control system such that, in operation of the unmanned aircraft, the onboard control system of the unmanned aircraft is operative to modify in-flight behaviour of the unmanned aircraft and / or provide information to an operator of the unmanned aircraft, based on the restriction zone data. The restriction zone data may comprise hazard data generated by an external modelling system. The onboard control system of the unmanned aircraft may be operative to define a restriction zone based on the hazard data. The restriction zone data may define a restriction zone based on hazard data generated by an external modelling system. The restriction zone may be defined by a remote control station of the unmanned aircraft system based on the hazard data. The restriction zone data may define a restriction zone based on hazard data generated by an external modelling system. The restriction zone may be defined by the interface based on the hazard data. The hazard data may relate to one or more aerodynamic hazards that may be present in a target operating environment of the unmanned aircraft. Modifying in-flight behaviour of the unmanned aircraft may enable the unmanned aircraft to avoid or mitigate a hazard associated with the restriction zone data. Modifying in-flight behaviour of the unmanned aircraft may comprises one or more of: disabling manual control of the unmanned aircraft; causing the unmanned aircraft to hover; causing the unmanned aircraft to land; causing the unmanned aircraft to return to base; causing the unmanned aircraft to avoid a location; causing the unmanned aircraft to sound an auditory signal; causing the unmanned aircraft to display a visual signal; causing the unmanned aircraft to abandon a flight path; modifying a speed of the unmanned aircraft; modifying a flight path of the unmanned aircraft; and preventing the unmanned aircraft from taking off. Providing information to an operator of the unmanned aircraft may comprise providing a visual or auditory signal to a user via a remote control station. The visual or auditory signal may signify one or more of: the position or trajectory of the unmanned aircraft relative to a location described by the restriction zone data; and the position of a location described by the restriction zone data. In operation of the unmanned aircraft, the onboard processing system may be operative to determine a location or trajectory of the unmanned aircraft relative to a location described by the restriction zone data. According to a second aspect, the invention provides a method for operating an unmanned aircraft, performed by an unmanned aircraft system, comprising: receiving restriction zone data generated by a modelling system external to the unmanned aircraft system; modifying in-flight behaviour of the unmanned aircraft and / or providing information to an operator of the unmanned aircraft system, based on the restriction zone data. The restriction zone data may comprise hazard data generated by the external modelling system. The restriction zone data may be defined by the unmanned aircraft system based on the hazard data generated by the external modelling system. The hazard data may relate to one or more aerodynamic hazards. Modifying in-flight behaviour of the unmanned aircraft may enable the unmanned aircraft to avoid or mitigate a hazard associated with the restriction zone data. Modifying in-flight behaviour of the unmanned aircraft may comprise one or more of: disabling manual control of the unmanned aircraft; causing the unmanned aircraft to hover; causing the unmanned aircraft to land; causing the unmanned aircraft to return to base; causing the unmanned aircraft to avoid a location; causing the unmanned aircraft to sound an auditory signal; causing the unmanned aircraft to display a visual signal; causing the unmanned aircraft to abandon a flight path; modifying a speed of the unmanned aircraft; modifying a flight path of the unmanned aircraft; and preventing the unmanned aircraft from taking off. The visual or auditory signal may signify one or more of: the position or trajectory of the unmanned aircraft relative to a location described by the restriction zone data; and the position of a location described by the restriction zone data. The method may further comprise determining a location or trajectory of the unmanned aircraft relative to a location described by the restriction zone data. The restriction zone data may be retrieved from a database of restriction zone data based on one or more of: a geographic location; a hazard threshold level; a type of the unmanned aircraft; and one or more meteorological variables. The one or more meteorological variables may comprise one or more of: a wind speed; a wind direction; and an air temperature. According to a third aspect, the invention provides an unmanned aircraft comprising: an onboard control system; and an interface for receiving restriction zone data generated by an external modelling system, wherein the onboard control system is configured to modify in-flight behaviour of an unmanned aircraft and / or provide information to an operator of the unmanned aircraft, based on the restriction zone data. The restriction zone data may comprise hazard data generated by the external modelling system. The onboard control system of the unmanned aircraft may be operative to define a restriction zone based on the hazard data. The restriction zone data may define a restriction zone based on hazard data generated by the external modelling system. The hazard data may relate to one or more aerodynamic hazards. Modifying in-flight behaviour of the unmanned aircraft may enable the unmanned aircraft to avoid or mitigate a hazard associated with the restriction zone data. Modifying in-flight behaviour of the unmanned aircraft may comprise one or more of: disabling manual control of the unmanned aircraft; causing the unmanned aircraft to hover; causing the unmanned aircraft to land; causing the unmanned aircraft to return to base; causing the unmanned aircraft to avoid a location; causing the unmanned aircraft to sound an auditory signal; causing the unmanned aircraft to display a visual signal; causing the unmanned aircraft to abandon a flight path; modifying a speed of the unmanned aircraft; modifying a flight path of the unmanned aircraft; and preventing the unmanned aircraft from taking off. Providing information to an operator of the unmanned aircraft may comprise providing a visual or auditory signal to a user via the remote control station of the unmanned aircraft system, wherein the visual or auditory signal signifies one or more of: the position or trajectory of the unmanned aircraft relative to a location described by the restriction zone data; and the position of a location described by the restriction zone data. In operation of the unmanned aircraft the onboard control system may be operative to determine a location or trajectory of the unmanned aircraft relative to a location described by the restriction zone data. According to a fourth aspect, the invention provides a method of providing restriction zone data to an unmanned aircraft system (UAS), performed by a modelling system external to the UAS, the method comprising: calculating, using a fluid dynamics simulation performed by the external modelling system, airflow field data based on a 3D model of a target operational environment for an unmanned aircraft and simulated wind conditions; determining hazard data from the air flow field data; and transmitting restriction zone data to a data platform or an unmanned aircraft system for use in modifying in-flight behaviour of an unmanned aircraft, wherein the restriction zone data comprises the hazard data or wherein the restriction zone data defines restriction zones based on the hazard data. The hazard data may comprise a simplified representation of at least part of the air flow field data. The external modelling system may generate the 3D model based on data about the target operational environment of the unmanned aircraft. Throughout this specification the word "comprise", or variations such as "comprises" or "comprising", will be understood to imply the inclusion of a stated element, integer or step, or group of elements, integers or steps, but not the exclusion of any other element, integer or step, or group of elements, integers or steps. Brief Description of Drawings Embodiments of the invention will now be described, strictly by way of example only, with reference to the accompanying drawings, of which: Figure 1 is a schematic representation of a typical unmanned aircraft system (UAS); Figure 2 is a schematic representation of an architecture of a typical unmanned aircraft; Figure 3 is a is a schematic representation of an unmanned aircraft that is provided with an interface according to the present disclosure; Figure 4 is a schematic representation of an unmanned aircraft system, an external modelling system and a data platform according to the present disclosure; Figure 5 is a schematic representation of an example of data transfer between a data platform, a remote control station of an unmanned aircraft system, and an unmanned aircraft according to the present disclosure. Detailed Description The present disclosure provides the aspects mentioned above. Optional and preferred features of the various aspects are described below. Unless otherwise stated, any optional or preferred feature may be combined with any other optional or preferred feature, and with any of the aspects of the invention mentioned herein. Figure 1 is a schematic representation of a typical unmanned aircraft system. As shown in Figure 1, the unmanned aircraft system 100 in the illustrated example comprises an unmanned aircraft 110, a remote control station 120 and a first communication link 130 (which may be referred to as a direct communication link) between the remote control station 120 and the unmanned aircraft 110. The unmanned aircraft system 100 may further comprise a second communication link 140 (which may be referred to as an indirect communication link) between remote control station 120 and the unmanned aircraft 110, via one or more secondary unmanned aircraft 150 acting as a relay, mobile control system or sensor. Alternatively, the second communication link 140 may comprise a satellite link, radio access network link, or mesh network link between remote control station 120 and the unmanned aircraft 110. The unmanned aircraft 110 may comprise any aircraft without an onboard human crew, such as a drone, UAV, passenger drone or autonomous aircraft. The remote control station 120 may comprise computing or processing hardware for executing software capable of providing ground control, acting as a mission planner, and / or otherwise controlling the unmanned aircraft 110 remotely. For example, the remote control station 120 may comprise a computer 121 (e.g. a desktop or laptop computer or a server or similar computer processing system) executing suitable software, coupled to a handheld remote control device 122 and a transmitter / receiver 123. The unmanned aircraft 110 may be capable of operating manually or autonomously. When operating manually, an operator controls the unmanned aircraft remotely via the remote control station 120. When operating autonomously, the unmanned aircraft 110 may be provided with a mission, flight plan or set of instructions which it executes without the direct control of an operator. Alternatively, when operating autonomously, the unmanned aircraft 110 may be controlled remotely by the remote control station 120 according to a mission, flight plan, or set of instructions, without direct control of an operator. Figure 2 is a schematic representation of an architecture of an unmanned aircraft of the kind shown in in Figure 1. For the sake of clarity, only those features of the unmanned aircraft that are relevant to the present disclosure are shown, but the skilled person would appreciate that a practical implementation of an unmanned aircraft may include additional features. The unmanned aircraft 110 in this example comprises an onboard control system 111 (e.g. a flight controller), a sensing subsystem 114, a communication subsystem 115 and an actuator subsystem 116. The onboard control system 111 of the unmanned aircraft 110 in this example comprises a processing subsystem 112 and a flight plan memory 113. The processing subsystem 112 may comprise any suitable processing means for processing instructions to control operation of the unmanned aircraft 110. For example, the processing subsystem 112 may comprise any combination of one or more microprocessors, microcontrollers, application specific integrated circuits (ASICs), and / or field programmable gate arrays (FPGAs) executing suitable programming instructions. The processing subsystem 112 is operative to execute software instructions implementing a collision avoidance system and other functionality of the unmanned aircraft 110. The flight plan memory 113 may comprise any suitable memory for storing flight plan data defining a flight plan for the unmanned aircraft 110. In operation of the unmanned aircraft 110, the processing subsystem 112 reads flight plan data from the flight plan memory 113 and outputs control signals to the actuator subsystem 116 based on the flight plan data and sensor data received from the sensing subsystem 114 to control operation of the unmanned aircraft 110. The sensing subsystem 114 is coupled to the processing subsystem 112, and comprises one or more sensors, such as one or more radar sensors, LIDAR sensors, optical cameras, barometric pressure sensors, accelerometers, inertial sensors and GPS receivers for sensing operational parameters of the unmanned aircraft such as its position, altitude, speed and acceleration, and for detecting physical hazards that may be present in the vicinity of the aircraft. The processing subsystem 112 receives sensor data from the sensing subsystem 114 and controls operation of the unmanned aircraft 110 based at least in part on the received sensor data. The communication subsystem 115 is coupled to the processing subsystem 112 and comprises one or more transceivers configured to receive control and / or data signals from the remote control station 120 (optionally via an indirect link as discussed above) and / or the secondary unmanned aircraft 150 (if present), and to transmit data signals to the remote control station 120 (optionally via an indirect link as discussed above) and / or the secondary unmanned aircraft 150 (if present). The actuator subsystem 116 is coupled to the processing subsystem 112 and comprises one or more actuators for controlling in-flight behaviour of the unmanned vehicle. The one or more actuators may comprise, for example, one or more electric motors for driving one or more rotors or propellors of the unmanned vehicle, and / or one or more electromechanical actuators for controlling flight control surfaces of the unmanned aircraft. In operation of the unmanned aircraft 110 the actuator subsystem 116 receives control signals from the processing subsystem 112 to control operation of the unmanned aircraft 110. Figure 3 is a schematic representation of an unmanned aircraft with an interface according to the present disclosure. The unmanned aircraft, shown generally at 300 in Figure 3, is similar in construction and operation to the unmanned aircraft 110 of Figure 2, and so common reference numerals are used in Figures 2 and 3 to denote features that are common to the unmanned aircraft 110 of Figure 2 and the unmanned aircraft 300 of Figure 3. Such common features will not be described again here, for the sake of brevity and clarity. The unmanned aircraft 300 of Figure 3 differs from the unmanned aircraft 110 of Figure 2 in that it is provided with an interface, which in this example comprises a coprocessor 310, which is configured to permit restriction zone data to be supplied to the unmanned aircraft 300. Restriction zone data may comprise hazard data generated by an external modelling system 200, as will be described in detail below. Alternatively, restriction zone data may itself define one or more restriction zones based on hazard data generated by an external modelling system 200. A restriction zone may be a region of space within the target operational environment of the unmanned aircraft 300 in which an aerodynamic hazard exists or is predicted (e.g. by an external modelling system) to exist and thus should be avoided or otherwise mitigated by the unmanned aircraft 300. Restriction zone data may define or represent such a restriction zone as a 3D volume in space or as a 2D area on a map. Restriction zone data may define one or more restriction zones. The coprocessor 310 may be a modular component that can be coupled to and decoupled from the unmanned aircraft 300. For example, the coprocessor 310 may be configured to be coupled to the onboard control system 111 and / or communication subsystem 115 of the unmanned aircraft 300. A single connector may be used to effect a coupling of the coprocessor 310 to both the communication subsystem 115 and the onboard control system 111 of the unmanned aircraft 300. For example, the coprocessor 310 may be received in a socket of the unmanned aircraft 300 having connectors that are coupled to the onboard control system 111 and the communication subsystem 115. The coprocessor 310 may be configured to interface with the onboard control system 111 of the unmanned aircraft 300 in order to permit hazard data and / or restriction zone data to be input to the onboard control system 111, for example via an application programming interface (API) associated with the onboard control system 111. The coprocessor 310 may interface directly with the flight plan memory 113 or with the processing subsystem 112. In some examples, Taw” hazard data can be supplied to the onboard control system 111 (e.g. to the flight plan memory 113) of the unmanned aircraft 300 in a range of formats (e.g. points, geometric primitives, bounded volume hierarchies, and others), via the coprocessor 310. The onboard control system 111 of the unmanned aircraft 300 (e.g. the collision avoidance system ,which may be executed or implemented by the processing subsystem 112) processes this received “raw” hazard data during operation of the unmanned aircraft 300 and controls operation of the unmanned aircraft 300 accordingly, to avoid or otherwise mitigate aerodynamic hazards associated with or defined or represented by the “raw” hazard data. For example, the “raw” hazard data may represent an aerodynamic hazard as a set of points, geometric primitives, volumes or the like associated with a particular geographic location. The particular geographic location may be defined, for example, by GPS coordinates. In operation of the unmanned aircraft 300, the onboard control system 111 may monitor the position and / or trajectory of the unmanned aircraft 300. As the unmanned aircraft 300 approaches a particular location (as may be determined, for example, by the processing subsystem 112 based on a comparison of the GPS coordinates for the particular geographic location to a current location of the unmanned aircraft 300, as indicated, for example, by a GPS receiver of the sensing subsystem 114), the onboard control system 111 (for example, the collision avoidance system) of the unmanned aircraft 300 may interpret the points, geometric primitives, volumes or the like associated with the particular geographic location as a physical hazard, and cause the processing subsystem 112 to output appropriate control signals to the actuator subsystem 116 and / or the communication subsystem 115 to control the unmanned aircraft to take appropriate action to avoid or mitigate the aerodynamic hazard. Thus, in examples in which “raw” hazard data is used by the onboard control system 111, the onboard control system 111 (e.g. via the collision avoidance system) effectively treats aerodynamic hazards as physical hazards to be avoided or otherwise mitigated, in the same way as hazards detected based on outputs of the sensing subsystem 114 of the unmanned aircraft 300. In other examples, the onboard control system 111 of the unmanned aircraft 300, or a remote control station (e.g. the remote control station 120 of Figure 2) for controlling the unmanned aircraft 300, may determine one or more explicit restriction zones, e.g. prior to a flight or mission of the unmanned aircraft 300, based on the hazard data received from the external modelling system. Restriction zone data defining the restriction zone(s) (e.g. GPS coordinates of particular geographic locations associated with sets of points, geometric primitives, volumes or the like defining aerodynamic hazards) may be supplied to the onboard control system 111 (e.g. to the flight plan memory 113) of the unmanned aircraft 300. In examples in which data defining the restriction zone(s) is supplied by the remote control station 120, these data may be supplied to the onboard control system 111 via the coprocessor 310 for storage in the flight plan memory 113. In examples in which the onboard control system 111 itself defines the restriction zone(s), “raw” hazard data may be supplied to the onboard control system 111 via the coprocessor 310, and the onboard control system 111 (e.g. the processing subsystem 112) may generate the restriction zone data based on the received “raw” hazard data and output these data to the flight plan memory 113. In operation of the unmanned aircraft 300 in such examples, the onboard control system 111 (via the collision avoidance system implemented by the processing subsystem 112, for example) may read restriction zone data from the flight plan memory 113 and compare these data to the current location of the unmanned aircraft 300 (e.g. by comparing GPS coordinates defining the restriction zone to GPS coordinates output by a GPS receiver of the sensing subsystem 114) to determine if the unmanned aircraft 300 is approaching a restriction zone. If it is determined that the unmanned aircraft is approaching a restriction zone, the processing subsystem 112 outputs appropriate control signals to the actuator subsystem 116 and / or the communication subsystem 115 to control the unmanned aircraft 300 to take appropriate action to avoid or mitigate the aerodynamic hazard. Alternatively, a remote control station 120 may determine the position and / or trajectory of the unmanned aircraft 300 relative to an aerodynamic hazard or relative to a restriction zone, as appropriate, based on position data of the unmanned aircraft 300, which may be supplied to the remote control station 120 by the unmanned aircraft 300 or may otherwise be determined by the remote control station 120 itself. As a further alternative, the position and / or trajectory of the unmanned aircraft 300 relative to an aerodynamic hazard or relative to a restriction zone, as appropriate, may be determined by the coprocessor 310, based on position data of the unmanned aircraft 300 supplied to the coprocessor 310 by the sensing subsystem 114 (via the processing subsystem 112). The coprocessor 310 may receive hazard data or restriction zone data from an external source (e.g. a remote control station 120 or a modelling system external to the UAS 100) via the communication subsystem 115 of the unmanned aircraft 300. Alternatively, the coprocessor 310 may comprise its own wired or wireless communication means by which it receives hazard data and / or restriction zone data. The coprocessor 310 may be operative to update hazard data and / or restriction zone data stored in the flight plan memory 113 while the unmanned aircraft 300 is in flight, for example if local meteorological conditions change. This enables the unmanned aircraft 300 to respond to dynamically changing aerodynamic conditions to avoid or otherwise mitigate aerodynamic hazards that may arise due to changes in meteorological conditions during a flight or mission of the unmanned aircraft 300. Providing hazard data or restriction zone data to the onboard control system 111 of the unmanned aircraft 300 via the coprocessor 310 (e.g. via a flight controller API) permits aerodynamic hazards to be recognised and avoided or otherwise mitigated by the unmanned aircraft 110 regardless of the particular onboard control system 111 used by the unmanned aircraft 110. The proximity of the unmanned aircraft 300 to an aerodynamic hazard or a restriction zone and / or whether the unmanned aircraft is within or approaching a restriction zone may be determined periodically, at a frequency that is configurable by a user of the UAS 100 (e.g. once per second, ten times per second, one hundred times per second etc.). The onboard control system 111 may be operative to read hazard data or restriction zone data (as appropriate) from the flight plan memory 113 corresponding to the target operational environment of the unmanned aircraft 300 and determine the distance of the unmanned aircraft 300 to the nearest aerodynamic hazard or restriction zone, as appropriate. This distance determination may be repeated periodically at a user-configurable frequency. If the onboard control system 111 determines, based on a determination of the distance of the unmanned aircraft 300 from the nearest aerodynamic hazard or restriction zone, that the unmanned aircraft 300 is approaching an aerodynamic hazard or a boundary of a restriction zone during flight, the onboard control system 111 may transmit (using the communication subsystem 115) information such as an alert indicating that the unmanned aircraft 110 is approaching an aerodynamic hazard or a restriction zone to the remote control station 120. This information may be transmitted using the MAVLink2 protocol, for example, and may be intended to prompt an operator to take appropriate action to prevent the unmanned aircraft 110 from coming closer to the aerodynamic hazard or entering the restriction zone, as appropriate. In some examples, the remote control station 120 may, in response to receiving such information, autonomously cause the unmanned aircraft 300 to take a predetermined action such as entering a hover mode or returning to base. Additionally or alternatively, the onboard control system 111 may autonomously cause the unmanned aircraft 300 to modify its in-flight behaviour in response to detection by the onboard control system 111 that the unmanned aircraft is approaching an aerodynamic hazard or a boundary of a restriction zone during flight. For example, the onboard control system 111 may cause the unmanned aircraft 300 to take a predetermined action such as entering a hover mode or returning to base in response to detection by the onboard control system 111 that the unmanned aircraft 300 is approaching an aerodynamic hazard or a boundary of a restriction zone during flight. In such cases, the onboard control system 111 may also transmit information to the remote control station 120 to notify the operator of the detection of the aerodynamic hazard and / or the modification to its in-flight behaviour performed autonomously by the unmanned aircraft 300. Notifying the operator may comprise providing information such as a visual or auditory warning signal to the operator. The warning signal may signify that the unmanned aircraft is approaching a restriction zone, within a restriction zone, within a certain distance of a restriction zone, or in a certain position relative to a restriction zone (e.g. above or below). Information provided to the operator may be provided via the unmanned aircraft 110 or via the remote control station 120, for example via a screen, light or speaker of the remote control station 120. Modifying the in-flight behaviour of the unmanned aircraft may comprise calculating a flight path or modifying a flight path to ensure the unmanned aircraft does not enter a restriction zone, changing a speed of the unmanned aircraft, causing the unmanned aircraft to hover in place, causing the unmanned aircraft to return to base, changing an altitude of the unmanned aircraft, sounding an auditory signal, displaying a visual signal, abandoning a flight path of the unmanned aircraft and / or landing the unmanned aircraft. Modifying the in-flight behaviour of the unmanned aircraft may also comprise triggering preset unmanned aircraft behaviour if a pilot attempts to operate it, for example preventing take-off. Modifying the in-flight behaviour of the unmanned aircraft may comprise disabling manual control, switching from manual to automatic control, or modifying manual control of the unmanned aircraft (e.g. limiting or changing the speed, trajectory and / or altitude of the aircraft, or preventing an operator from flying the unmanned aircraft into a restriction zone). Additionally or alternatively, modifying the in-flight behaviour of the unmanned aircraft may comprise performing other actions to mitigate the aerodynamic hazard. For example modifying the in-flight behaviour may comprise increasing the power available to the actuator subsystem 116, to reduce the risk of disruption to the operation of the unmanned aircraft as it traverses or manoeuvres around the aerodynamic hazard, and / or (temporarily) degrading the performance of the unmanned aircraft, and / or reducing a user-driven workload of the unmanned aircraft, e.g. by disabling or limiting the functionality of user controlled tools such as camera, camera mounts and the like. Degrading the performance of the unmanned aircraft and / or reducing the user-driven workload may have effects such as increasing the power available to the actuator subsystem 116, increasing the stability or manoeuvrability of the unmanned aircraft, thus improving its ability to avoid or traverse the aerodynamic hazard. Figure 4 is a schematic representation of an unmanned aircraft system, an external modelling system, and a data platform according to the present disclosure. A shown in Figure 4, a modelling system 200 external to the UAS 100 can be used to simulate the airspace in a target operational environment of the unmanned aircraft 300 to predict locations of possible aerodynamic hazards for a given set of meteorological conditions. The target operational environment is an environment in which the unmanned aircraft will be operated to perform a mission or flight, and is typically a volume defined by a relatively small geographical area containing physical features, such as a small area of an urban environment containing buildings, an area containing a wind farm containing wind turbines or the like. In particular, the external modelling system 200 may use high-fidelity computational fluid dynamics (CFD) to identify aerodynamic hazards within the target operational environment of a scale that could impact unmanned aircraft flight. For example, the external modelling system 200 may generate datasets representing the target operational environment using a relatively small grid spacing, e.g. 20 metres, 10 metres, 5 metres, 1 metre or even less, as required by the particular application. Thus, the datasets generated by the external modelling system 200 are of a high resolution that allows features or aerodynamic hazards that would not be detected by lower resolution modelling (e.g. conventional weather forecasting models, which typically have a minimum resolution of the order of 300 metres). The external modelling system 200 uses a three-dimensional (3D) model of the target operational environment for the unmanned aircraft 300. The modelling system may obtain data from a number of sources (e.g. Open Street Map, OS Terrain 5, AccuCities) and use this to generate the 3D model of the target operational environment for the unmanned aircraft 300. The external modelling system 200 simulates airflow based on the 3D model and specified meteorological conditions, such as wind conditions. Based on this simulation, the external modelling system 200 determines air flow field data which may be indicative of aerodynamic hazards that may arise as a result of interaction between air and features of the target operational environment such as buildings (e.g. apartment blocks, office buildings, houses, parking lots), infrastructure (e.g. wind turbines, storage containers, bridges, tunnels, masts, power transmission equipment), machinery (e.g. cranes, excavators, boring machines, power shovels), vehicles (e.g. ships, aeroplanes), geographical features (e.g. hills, valleys, forests, bodies of water), and any other manmade or natural structures. The external modelling system 200 may generate a CFD mesh on the 3D model using a suitable tool, such as a proprietary mesh generator developed by the applicants and custom rules. This mesh is then used to run a CFD solver. A large number of CFD simulations may be completed for a range of different meteorological conditions to generate several air flow field data sets for the target operational environment for the range of different meteorological conditions. For example, a simulation may be completed for each of a plurality of values of a plurality of meteorological variables such as wind speed, wind direction and temperature. This process may generate a large amount of data, for example several hundred gigabytes of data containing calculated flow field data for the whole model. The modelling system may generate at least one validated 3D map of the airspace in the target operational environment. The external modelling system 200 may generate a plurality of flow field data sets, where each flow field data set corresponds to a particular meteorological condition (e.g. a particular set of values of meteorological variables such as temperature, wind speed and wind direction). Each flow field data set may itself be calculated via an ensemble averaging technique. Transm itting a large amount of air flow field data to a UAS requires a large amount of signalling overhead and / or may be slow, and the requirements of processing the data in the UAS (for example, onboard the unmanned aircraft 300) may exceed the hardware limitations of the unmanned aircraft and / or UAS. Therefore, the external modelling system 200 may transform airflow field data from a model into a simplified representation (hazard data) that can be interpreted by the software running on an unmanned aircraft 300 or UAS 100. This enables data about aerodynamic hazards to be transmitted to an unmanned aircraft 300 or UAS 100 quickly and in a computationally efficient way. For example, the external modelling system may process a large 3D set of airflow field data into a reduced form (e.g. using compression or other data reduction techniques) for loading into a remote control station 120 and / or an unmanned aircraft 300. As described above, restriction zone data used by the unmanned aircraft 300 may comprise hazard data generated by the external modelling system 200, or may itself define one or more restriction zones based on hazard data generated by the external modelling system 200. Both the “raw” hazard data generated by the external modelling system 200 and any restriction zones defined based on this hazard data may be substantially simplified versions of the airflow field data generated by the external modelling system 200. These simplified data representations reduce memory and storage requirements, reduce transmission overheads, and reduce computational requirements of an unmanned aircraft system. In more detail, transforming air flow field data into a simplified representation provides the ability to quickly transmit data about aerodynamic hazards in the target operational environment of an unmanned aircraft 300 (i.e. restriction zone data and / or hazard data) prior to or during a flight based on current or predicted local conditions in the target operational environment. This also enables restriction zone data to be quickly updated in flight if current or predicted local conditions in the target operational environment change. The simplified data representations reduce memory and storage requirements for onboard processing and thus allow for restriction zone data and / or hazard data to be rapidly and periodically transmitted between various parts of the UAS 100 (e.g. the unmanned aircraft 110 and the remote control station 120) as well as between the UAS 100, the external modelling system 200 and / or a data platform 400, which will be described later. Rapid transmission and processing of restriction zone data enables an unmanned aircraft 300 or remote control station 120 to periodically update hazard data at. For example, the remote control station 120 may query the external modelling system 200 or the data platform 400 for updated restriction zone data and / or hazard data for a target operating environment of the unmanned aircraft 300 and provide this data to the unmanned aircraft. In an alternative example, the unmanned aircraft 300 may query the remote control station 120, the external modelling system 200 or the data platform 400 for updated restriction zone data and / or hazard data for a target operating environment of the unmanned aircraft 300. As mentioned above, this enables the unmanned aircraft 300 to respond to dynamically changing aerodynamic conditions to avoid or otherwise mitigate aerodynamic hazards that may arise due to changes in meteorological conditions during a flight or mission of the unmanned aircraft 300. Moreover, the use of simplified data representations allows high-frequency realtime updating of the onboard control system 111, to allow the unmanned aircraft to respond rapidly to an aerodynamic hazard. For example, the onboard control system 111 may receive information about its location (e.g. from a GPS receiver of the sensing subsystem 114 or from the remote control station 120, via the communication subsystem 115) at a high frequency (e.g. 100MHz) and may compare this location information to the hazard data or restriction zone data as described above to determine if the unmanned aircraft 300 is approaching an aerodynamic hazard. The use of simplified data representations of aerodynamic hazards minimises (or at least reduces) the processing time required to perform this determination, thus allowing the unmanned aircraft 300 to respond rapidly to avoid or otherwise mitigate aerodynamic hazards. Calculation of hazard data may be based on the presence and / or severity of simulated aerodynamic hazards. Aerodynamic hazards may include turbulence, wind, vortices, shear layers or other aerodynamic features or conditions that can affect unmanned aircraft flight. Certain unmanned aircraft may be more susceptible to certain types of hazards. Therefore, a threshold level defined for certain hazard types may be configurable depending on the unmanned aircraft 300 that will use the data. For example, a threshold level may be defined for turbulence, wind speed, vortices and / or shear layers. The threshold level of turbulence may be configured for an unmanned aircraft 300 based on the mass, size, flight capabilities and / or value of the unmanned aircraft 300, or on the importance of its use case, or on other factors. For example, a lower threshold level of turbulence may be set for a lightweight unmanned aircraft which is less able to withstand turbulent conditions. Hazard data generated by the external modelling system 200 may depend on the configured threshold level for a hazard type. Air flow field data may be post-processed to extract hazard data. For example, air flow field data may be post-processed to extract one or more regions of turbulent flow. Hazard data may define or represent a hazard zone as a 3D volume in space or a 2D area on a map. The hazard data may be used by the UAS 100 or the onboard control system 111 of an unmanned aircraft 300 to define one or more restriction zones, as discussed above. Aerodynamic hazard data may be stored, e.g. in a database of or associated with the external modelling system 200, for each of one or more values of geographical location; threshold level; unmanned aircraft type; one or more meteorological variables such as wind direction, wind speed, and / or temperature; and / or other variables. Aerodynamic hazard data may be transmitted from the external modelling system 200 to a UAS 100, for example to an unmanned aircraft 300 or to a remote control station 120. Alternatively, hazard data may be transmitted to an external data platform 400 such as a web / data platform. Hazard data stored on the external data platform 400 may be selected and accessed by a UAS 100 via a service interface or web API or via file download. Software running on the UAS 100 may select and read hazard data based on current measured meteorological conditions. For example, current meteorological conditions may be reported to the unmanned aircraft 300, and software running on the unmanned aircraft 300 may select and read hazard data based on this information. In another example, the remote control station 120 of the UAS 100 may select and read hazard data based on current meteorological conditions. Current meteorological conditions may be measured by a secondary unmanned aircraft 150 and reported to the unmanned aircraft 300 and / or the remote control station 120. Figure 5 is a schematic representation of an example of data transfer according to the present disclosure. A UAS 100 may transmit a request for aerodynamic hazard data to an external data platform 400. For example, the remote control station 120 or the unmanned aircraft 110 may transmit the request. The request may specify a target operating environment; threshold level; unmanned aircraft type; one or more meteorological variables such as wind direction, wind speed, and / or temperature; and / or other variables. In response, the external data platform 400 selects aerodynamic hazard data corresponding to the variables specified in the request, and transmits the selected aerodynamic hazard data to the UAS 100. Aerodynamic hazard data can be provided to users as a service, to allow aerodynamic hazard data to be selected according to selected target operating environment; threshold level; unmanned aircraft type; one or more meteorological variables such as wind direction, wind speed, and / or temperature; and / or other variables. The correct dataset (e.g. an aerodynamic hazard dataset corresponding to a particular value of target operating environment; threshold level; unmanned aircraft type; one or more meteorological variables such as wind direction, wind speed, and / or temperature; and / or other variables) may be selected by the operator from the external data platform 400 and stored in the UAS 100, for example on the internal storage of the unmanned aircraft 300 or on the internal storage of the remote control station 120. In the foregoing description, a system is described in which an unmanned aircraft is adapted by the addition of an interface such as a coprocessor that allows restriction zone data (e.g. “raw” hazard data) to be supplied to the onboard control system of the unmanned aircraft. The present disclosure also extends to an unmanned aircraft which is not provided with such an interface, but whose own onboard control system is specifically adapted to be able to receive restriction zone data and perform the functions of the coprocessor as described above. The unmanned aircraft is thus similar in construction to unmanned aircraft 110 of Figure 2 and similar in operation to the unmanned aircraft 300 of Figure 3. In the foregoing description a single unmanned aircraft 300 has been described. It is envisioned that an unmanned aircraft system according to the present disclosure may include two or more unmanned aircraft operating in a cluster, with one of the unmanned aircraft being configured and / or operative to detect aerodynamic hazards in accordance with the foregoing disclosure, and operating as a control node to control all the unmanned aircraft in the cluster to avoid or otherwise mitigate such aerodynamic hazards. The skilled person will recognise that some aspects of the above-described apparatus and methods may be embodied as processor control code, for example on a non-volatile carrier medium such as a disk, CD- or DVD-ROM, programmed memory such as read only memory (Firmware), or on a data carrier such as an optical or electrical signal carrier. Note that as used herein the term subsystem shall be used to refer to a functional unit or block which may be implemented at least partly by dedicated hardware components such as custom defined circuitry and / or at least partly be implemented by one or more software processors or appropriate code running on a suitable general-purpose processor or the like. A subsystem may itself comprise other subsystems or functional units. A subsystem may be provided by multiple components or sub-subsystems which need not be co-located and could be provided on different integrated circuits and / or running on different processors. This disclosure encompasses all changes, substitutions, variations, alterations, and modifications to the example embodiments herein that a person having ordinary skill in the art would comprehend. Similarly, where appropriate, the appended claims encompass all changes, substitutions, variations, alterations, and modifications to the example embodiments herein that a person having ordinary skill in the art would comprehend. Moreover, reference in the appended claims to an apparatus or system or a component of an apparatus or system being adapted to, arranged to, capable of, configured to, enabled to, operable to, or operative to perform a particular function encompasses that apparatus, system, or component, whether or not it or that particular function is activated, turned on, or unlocked, as long as that apparatus, system, or component is so adapted, arranged, capable, configured, enabled, operable, or operative. Accordingly, modifications, additions, or omissions may be made to the systems, apparatuses, and methods described herein without departing from the scope of the disclosure. For example, the components of the systems and apparatuses may be integrated or separated. Moreover, the operations of the systems and apparatuses disclosed herein may be performed by more, fewer, or other components and the methods described may include more, fewer, or other steps. Additionally, steps may be performed in any suitable order. As used in this document, “each” refers to each member of a set or each member of a subset of a set. Although exemplary embodiments are illustrated in the figures and described below, the principles of the present disclosure may be implemented using any number of techniques, whether currently known or not. The present disclosure should in no way be limited to the exemplary implementations and techniques illustrated in the drawings and described above. Unless otherwise specifically noted, articles depicted in the drawings are not necessarily drawn to scale. All examples and conditional language recited herein are intended for pedagogical objects to aid the reader in understanding the disclosure and the concepts contributed by the inventor to furthering the art, and are construed as being without limitation to such specifically recited examples and conditions. Although embodiments of the present disclosure have been described in detail, it should be understood that various changes, substitutions, and alterations could be made hereto without departing from the spirit and scope of the disclosure. Although specific advantages have been enumerated above, various embodiments may include some, none, or all of the enumerated advantages. Additionally, other technical advantages may become readily apparent to one of ordinary skill in the art after review of the foregoing figures and description. It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. The word “comprising” does not exclude the presence of elements or steps other than those listed in a claim, “a” or “an” does not exclude a plurality, and a single feature or other unit may fulfil the functions of several units recited in the claims. Any reference numerals or labels in the claims shall not be construed so as to limit their scope.

Claims

1. An unmanned aircraft system comprising:an interface configured to interface with an onboard control system of an unmanned aircraft to supply restriction zone data to the onboard control system such that, in operation of the unmanned aircraft, the onboard control system of the unmanned aircraft is operative to modify in-flight behaviour of the unmanned aircraft and / or provide information to an operator of the unmanned aircraft, based on the restriction zone data.

2. The unmanned aircraft system of claim 1, wherein the restriction zone data comprises hazard data generated by an external modelling system3. The unmanned aircraft system of claim 2, wherein the onboard control system of the unmanned aircraft is operative to define a restriction zone based on the hazard data.

4. The unmanned aircraft system of claim 1, wherein the restriction zone data defines a restriction zone based on hazard data generated by an external modelling system, and wherein the restriction zone is defined by a remote control station of the unmanned aircraft system based on the hazard data.

5. The unmanned aircraft system of claim 1, wherein the restriction zone data defines a restriction zone based on hazard data generated by an external modelling system, and wherein the restriction zone is defined by the interface based on the hazard data.

6. The unmanned aircraft system of any of claims 2-5, wherein the hazard data relates to one or more aerodynamic hazards that may be present in a target operating environment of the unmanned aircraft.

7. The unmanned aircraft system of any of the preceding claims, wherein modifying in-flight behaviour of the unmanned aircraft enables the unmanned aircraft to avoid or mitigate a hazard associated with the restriction zone data.

8. The unmanned aircraft system of any of the preceding claims, wherein modifying in-flight behaviour of the unmanned aircraft comprises one or more of: disabling manual control of the unmanned aircraft;causing the unmanned aircraft to hover;causing the unmanned aircraft to land;causing the unmanned aircraft to return to base;causing the unmanned aircraft to avoid a location;causing the unmanned aircraft to sound an auditory signal;causing the unmanned aircraft to display a visual signal;causing the unmanned aircraft to abandon a flight path;modifying a speed of the unmanned aircraft;modifying a flight path of the unmanned aircraft; andpreventing the unmanned aircraft from taking off.

9. The unmanned aircraft system of any of the preceding claims, wherein providing information to an operator of the unmanned aircraft comprises providing a visual or auditory signal to a user via a remote control station, wherein the visual or auditory signal signifies one or more of:the position or trajectory of the unmanned aircraft relative to a location described by the restriction zone data; andthe position of a location described by the restriction zone data.

10. The unmanned aircraft system of any of the preceding claims, wherein in operation of the unmanned aircraft the onboard processing system is operative to determine a location or trajectory of the unmanned aircraft relative to a location described by the restriction zone data.

11. A method for operating an unmanned aircraft, performed by an unmanned aircraft system, comprising:receiving restriction zone data generated by a modelling system external to the unmanned aircraft system;modifying in-flight behaviour of the unmanned aircraft and / or providing information to an operator of the unmanned aircraft system, based on the restriction zone data.

12. The method of claim 11, wherein the restriction zone data comprises hazard data generated by the external modelling system.

13. The method of claim 12, wherein the restriction zone data is defined by the unmanned aircraft system based on the hazard data generated by the external modelling system.

14. The method of claim 12 or claim 13, wherein the hazard data relates to one or more aerodynamic hazards.

15. The method of any of claims 11 - 14, wherein modifying in-flight behaviour of the unmanned aircraft enables the unmanned aircraft to avoid or mitigate a hazard associated with the restriction zone data.

16. The method of any of claims 11 - 15, wherein modifying in-flight behaviour of the unmanned aircraft comprises one or more of:disabling manual control of the unmanned aircraft;causing the unmanned aircraft to hover;causing the unmanned aircraft to land;causing the unmanned aircraft to return to base;causing the unmanned aircraft to avoid a location;causing the unmanned aircraft to sound an auditory signal;causing the unmanned aircraft to display a visual signal;causing the unmanned aircraft to abandon a flight path;modifying a speed of the unmanned aircraft;modifying a flight path of the unmanned aircraft; andpreventing the unmanned aircraft from taking off.

17. The method of claim 16, wherein the visual or auditory signal signifies one or more of:the position or trajectory of the unmanned aircraft relative to a location described by the restriction zone data; andthe position of a location described by the restriction zone data.

18. The method of any of claims 11 - 17, further comprising determining a location or trajectory of the unmanned aircraft relative to a location described by the restriction zone data.

19. The method of any of claims 11 - 18, wherein the restriction zone data is retrieved from a database of restriction zone data based on one or more of:a geographic location;a hazard threshold level;a type of the unmanned aircraft; and one or more meteorological variables.

20. The method of claim 19, wherein the one or more meteorological variables comprise one or more of:a wind speed;a wind direction; and an air temperature.

21. An unmanned aircraft comprising: an onboard control system; and an interface for receiving restriction zone data generated by an external modelling system;wherein the onboard control system is configured to modify in-flight behaviour of an unmanned aircraft and / or provide information to an operator of the unmanned aircraft, based on the restriction zone data.

22. The unmanned aircraft of claim 21, wherein the restriction zone data comprises hazard data generated by the external modelling system23. The unmanned aircraft of claim 22, wherein the onboard control system of the unmanned aircraft is operative to define a restriction zone based on the hazard data.

24. The unmanned aircraft of claim 21, wherein the restriction zone data defines a restriction zone based on hazard data generated by the external modelling system.

25. The unmanned aircraft of claim 22 or claim 23, wherein the hazard data relates to one or more aerodynamic hazards.

26. The unmanned aircraft of any of any of claims 21 - 25, wherein modifying in-flight behaviour of the unmanned aircraft enables the unmanned aircraft to avoid or mitigate a hazard associated with the restriction zone data.

27. The unmanned aircraft of any of claims 21 - 26, wherein modifying in-flight behaviour of the unmanned aircraft comprises one or more of:disabling manual control of the unmanned aircraft;causing the unmanned aircraft to hover;causing the unmanned aircraft to land;causing the unmanned aircraft to return to base;causing the unmanned aircraft to avoid a location;causing the unmanned aircraft to sound an auditory signal;causing the unmanned aircraft to display a visual signal;causing the unmanned aircraft to abandon a flight path;modifying a speed of the unmanned aircraft;modifying a flight path of the unmanned aircraft; andpreventing the unmanned aircraft from taking off.

28. The unmanned aircraft of any of claims 21 - 27, wherein providing information to an operator of the unmanned aircraft comprises providing a visual or auditory signal to a user via the remote control station of the unmanned aircraft system, wherein the visual or auditory signal signifies one or more of:the position or trajectory of the unmanned aircraft relative to a location described by the restriction zone data; andthe position of a location described by the restriction zone data.

29. The unmanned aircraft of any of claims 21 - 28, wherein in operation of the unmanned aircraft the onboard control system is operative to determine a location or trajectory of the unmanned aircraft relative to a location described by the restriction zone data.

30. A method of providing restriction zone data to an unmanned aircraft system (UAS), performed by a modelling system external to the UAS, the method comprising:calculating, using a fluid dynamics simulation performed by the external modelling system, air flow field data based on a 3D model of a target operational environment for an unmanned aircraft and simulated wind conditions;determining hazard data from the airflow field data; andtransmitting restriction zone data to a data platform or an unmanned aircraft system for use in modifying in-flight behaviour of an unmanned aircraft, wherein the restriction zone data comprises the hazard data or wherein the restriction zone data defines restriction zones based on the hazard data.

31. The method of claim 30, wherein the hazard data comprises a simplified representation of at least part of the air flow field data.

32. The method of claim 30 or claim 31, wherein the external modelling system generates the 3D model based on data about the target operational environment of the unmanned aircraft.

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