234 results about "Flight direction" patented technology

The invention discloses an unmanned aerial vehicle flight control method and system based on a target image, and relates to the field of unmanned aerial vehicle flight control, and the method comprises the steps: obtaining the relative position of an unmanned aerial vehicle in a flight region based on the target image and a position calculation algorithm, and judging the yaw state of the unmanned aerial vehicle through a position comparison method; analyzing the target image by using an identification processing technology based on yaw state judgment to determine a flight yaw angle of the unmanned aerial vehicle, and generating a yaw control quantity according to the flight yaw angle to control the flight state of the unmanned aerial vehicle; collecting a real-time target image of the unmanned aerial vehicle after the flight state is adjusted, analyzing the flight height of the unmanned aerial vehicle according to the real-time target image, and planning a landing track of the unmanned aerial vehicle based on the flight height; and generating an autonomous landing control instruction according to the unmanned aerial vehicle landing trajectory and a preset flight demand to complete autonomous landing flight control of the unmanned aerial vehicle. By collecting the target image in real time and analyzing the flight height, the landing track of the unmanned aerial vehicle can be accurately planned.

A heavier-than-air aircraft is attached to at least one VTOL aircraft by tethers: the tethers are attached to the heavier-than-air aircraft at points spaced laterally from the center of gravity of the heavier-than-air aircraft. the tethers comprising winches, and a control system programmed to control the direction of flight of the heavier-than-air aircraft by controlling the winches.

The invention relates to the technical field of multi-screen display, in particular to a multi-screen display picture control method and system for an unmanned aerial vehicle, and the method comprises the following steps: comparing the flight height with an obstacle position parameter according to the flight path planning data of the unmanned aerial vehicle and real-time obstacle information; and performing path segmentation calculation of adjacent areas by combining the speed and the flight direction of the unmanned aerial vehicle, evaluating the minimum safety distance of the obstacle, and outputting a path planning safety coefficient. According to the invention, through multi-parameter dynamic comparison of the flight height, the obstacle position, the speed and the direction, the flexibility of path adjustment and the obstacle avoidance precision are improved, and the dynamic distribution of the flight picture and state information is combined with the view angle switching position parameters, so that efficient distribution of multiple devices is realized; real-time environment data processing is combined with image frame feature extraction and region division scheduling, navigation data priority distribution is optimized, information synchronization is optimized through path overlapping parameters and communication delay, and multi-machine cooperation efficiency and task execution reliability are improved.

The present invention relates to the field of electronic fence technology, specifically to an electronic fence monitoring method and system for unmanned aerial vehicles, comprising the following steps: based on the real-time positioning data of the unmanned aerial vehicle, by analyzing the positioning changes of the unmanned aerial vehicle within a period of time, calculating the flight speed of the unmanned aerial vehicle, and analyzing the change trend of the flight speed of the unmanned aerial vehicle according to the flight speed data of the unmanned aerial vehicle within a period of time, and obtaining the speed information of the unmanned aerial vehicle. The present invention can analyze the distance between the unmanned aerial vehicle and the electronic fence in real time and estimate the crossing time by continuously tracking the flight speed and flight direction, thereby providing scientific data support for preventing potential safety risks, and by adjusting the warning threshold and matching the reaction time of the operator, improving the adaptability and practicality of the early warning, making the warning more timely and effective, significantly reducing the possibility of false alarms and missed alarms, enhancing the response speed and accuracy of the unmanned aerial vehicle electronic fence system, and effectively preventing the illegal flight of the unmanned aerial vehicle and the occurrence of safety accidents.

The invention provides a multi-source information fusion unmanned aerial vehicle marine target tracking method and system, and relates to the technical field of data processing, and the method comprises the steps: obtaining image data, and extracting the features of a target region; unmanned aerial vehicle attitude data, radar position detection data and AIS identification data are obtained, attitude disturbance correction is executed, and time axis alignment is performed on the data; calculating the visual feature matching offset of the adjacent frames, and comparing the visual feature matching offset with the radar azimuth change trend; constructing a candidate target spatial position set, and executing distance convergence screening and spatial overlapping constraint processing of a geometric projection range on the candidate target spatial position set; motion direction continuity comparison is executed, and target position data is generated; generating a track control instruction for controlling the flight direction and speed of the unmanned aerial vehicle according to the target position data, and adjusting the subsequent flight path of the unmanned aerial vehicle according to the track control instruction; according to the invention, autonomy and accuracy of unmanned aerial vehicle marine target tracking are improved.

The invention discloses an unmanned aerial vehicle continuous speed space gesture control system and method based on a somatosensory glove. The system comprises a gesture data acquisition module, a data transmission module and a flight control execution module. The gesture data acquisition module comprises a palm data acquisition module and a palm data resolving module. The current attitude quaternion is used for calculating the thumb orientation to control the flight direction, the finger bending angle is converted into the flight speed, the thumb direction is used as the flight direction, the finger bending degree is converted into the flight speed, unmanned aerial vehicle glove control of continuous speed direction space and large and small space is achieved, computing resource overhead is reduced, and the working efficiency is improved. Meanwhile, the limitation of a traditional unmanned aerial vehicle remote controller is overcome, the control efficiency is improved, the method has the advantages of being visual and convenient to operate, rapid in response, accurate in control and the like, the method is suitable for flexible control scenes of the unmanned aerial vehicle, interaction immersion and friendliness are enhanced, and user experience and flight safety are improved.

The invention belongs to the field of flight network and channel planning, particularly relates to a ground network point and air channel planning method for urban low-altitude traffic, and aims to solve the problems that in an urban traffic scene, flight of a large number of aircrafts is difficult to manage in a standardized manner, and flight trajectories intersect randomly to easily cause aircraft conflicts in a dense flight scene. The method comprises the following steps: setting a plurality of aircraft flight ground base stations based on a honeycomb structure; determining an initial website and an end website; acquiring a website flight path through a path approximation selection algorithm; an air channel planning path is formed by the starting point-initial network point of the aircraft, the network point flight path and the ending network point-ending point of the aircraft; and carrying out flight height layering according to the flight direction in the branch flight path. The air traffic flight system solves the problems that the flight of a large number of aircrafts is difficult to standardize and the flight tracks are crossed randomly to easily cause aircraft conflicts, and is high in flight efficiency, high in flight safety and convenient to manage.

The invention is suitable for the technical field of image processing, and provides a visual obstacle avoidance method and device for an unmanned aerial vehicle, and the method comprises the steps: collecting a plurality of real-time depth images based on a preset sampling frequency, and determining whether a dynamic obstacle exists or not according to the real-time depth images; when the existence of the dynamic obstacle is determined, constructing a current obstacle avoidance space sphere according to the depth value in the real-time depth image, the speed of the unmanned aerial vehicle and the actual estimated length of the obstacle; when the flight direction of the unmanned aerial vehicle intersects with the current obstacle avoidance space sphere, calculating an obstacle avoidance bypassing route based on the surface edge of the current obstacle avoidance space sphere; and controlling the unmanned aerial vehicle to perform obstacle avoidance flight based on the obstacle avoidance bypassing route. Compared with a traditional obstacle avoidance method, the method can more intelligently plan the detour route of the unmanned aerial vehicle, and guarantees the stability and safety of the flight process.

The invention discloses an unmanned aerial vehicle path optimization method based on a bionic growth optimization process. The method comprises the following steps: establishing an unmanned aerial vehicle perception model; establishing an unmanned aerial vehicle control model; and unmanned aerial vehicle path planning based on a bionic growth optimization process. According to the invention, artificial intelligence, machine learning, cognitive calculation and simulation of an event-related potential loop development mode of a human brain are fused. Establishing a sensing model, and enabling the unmanned aerial vehicle to sense and recognize surrounding obstacle information; establishing a control model, allowing the unmanned aerial vehicle to select eight basic flight directions on a two-dimensional plane, and forming an obstacle avoidance strategy; path planning is combined with an artificial potential field method and a bionic growth mechanism, so that the unmanned aerial vehicle perceives obstacles in real time and optimizes a navigation path in the flight process; along with the accumulation of flight experience, the unmanned aerial vehicle knowledge base is continuously updated, and a more efficient and safer path plan is formed. According to the invention, the adaptability and decision ability of the unmanned aerial vehicle in an unknown environment are significantly improved, and the autonomous obstacle avoidance ability and task execution efficiency of the unmanned aerial vehicle in a complex environment are improved.

The invention discloses a meta universe task offloading and resource scheduling method based on deep reinforcement learning, and relates to the technical field of wireless communication, and the method comprises the steps: 1, putting an unmanned aerial vehicle cluster in a user dense region, and enabling a fixed edge server to obtain the position coordinates of the fixed edge server, each user and each unmanned aerial vehicle; 2, a user sends a rendering request to the fixed edge server through the unmanned aerial vehicle cluster; step 3, constructing an optimization target, converting the optimization target into a Markov decision process, solving the optimization target through a PPO algorithm, and obtaining a horizontal flight rate, a flight direction and a vertical direction rate of the unmanned aerial vehicle and a computing resource set available for edge equipment; step 4, the fixed edge server issues a decision result to the user and the unmanned aerial vehicle, and the user and the unmanned aerial vehicle execute a decision; and step 5, after the unmanned aerial vehicle completes the rendering task, returning a result to the user. The method has the characteristics of multi-node collaborative optimization, energy consumption optimization and resource utilization rate optimization.

The invention relates to the technical field of aircrafts, in particular to a master-slave multi-rotor unmanned aerial vehicle which comprises a control system and a storage battery. The device further comprises a structure assembly. The structural assembly comprises a tetrahedral shell, coaxial reverse dual motors, two main rotors, three branch pipes, three driving mechanisms and three slave rotors. The control system controls operation of the whole, and the storage battery supplies power to the whole. The large-size main rotor is used for replacing a traditional multi-rotor to provide main lifting force, the efficiency can be improved, the energy utilization level can be improved, and meanwhile the loading capacity is higher compared with the multi-rotor; a combined triangle is used as a main structural form, so that the structural stability and reliability under various stress conditions are ensured, and the use is more stable under a complex scene; the flight direction, attitude and stability are controlled by three small-size slave rotors; therefore, the problems that an existing multi-rotor unmanned aerial vehicle is low in energy utilization efficiency and poor in loading capacity are solved.

The invention relates to a community low altitude-oriented aircraft path planning and traffic capacity evaluation system. The system comprises an airspace facility modeling module, a facility relation judgment module, a hierarchical airspace segmentation module, a noise-speed-safe distance constraint calculation module, a dynamic obstacle marking module, a multi-target path planning module and a bottleneck identification and traffic capacity evaluation module. The method comprises the following steps: modeling airspace facilities, and judging a facility relationship based on spatial geometric attributes and function use requirements of the facilities; performing hierarchical grid division on the low altitude of the community, calculating a safety distance along the movement direction and a safety distance perpendicular to the flight direction, and performing obstacle marking on grids around the building based on the safety distances and the flight direction; and performing path search based on an improved A * algorithm, identifying a bottleneck region, extracting parameters, and calculating the maximum allowable speed of the bottleneck region and the total traffic capacity of the bottleneck region. The system can relieve environmental troubles such as safety compliance dispute and noise pollution caused by operation of the low-altitude aircraft.

The invention discloses an airship type unmanned aerial vehicle inspection system and inspection method, and belongs to the field of inspection unmanned aerial vehicles. The system comprises a laser radar, an image acquisition device, an airship capsule filled with helium, a standby safety airbag, a communication module and a ground control center, in the method, the ground control center sets an inspection path and issues the inspection path, and the unmanned aerial vehicle flies according to a preset path. During fault detection, the high-definition camera collects images to recognize line cracks and broken strands, the thermal infrared imager monitors the joint temperature, the gas sensor detects abnormal gas, and multi-source data fusion assists in defect positioning. The routing inspection takes a starting point-terminal point connecting line of a power transmission line as a reference, identifies main obstacles and surrounding nodes to perform global planning, performs key routing inspection on a risk area in combination with historical data, and initializes and guides a flight direction through a Q value to reduce invalid exploration. The four-rotor unmanned aerial vehicle solves the problems of short flight time and poor stability of a four-rotor unmanned aerial vehicle, improves the inspection stability and cruising ability, and improves the inspection efficiency of a power transmission line and the reliability of a power system.

The invention discloses a flight management equipment route intelligent generation method, and belongs to the technical field of flight control, and the method comprises the following steps: 1, a basic route is generated through flight management equipment, and the basis conditions for generating the basic route at least comprise a takeoff airport, a landing airport, a flight direction, a civil aviation route and a navigation database; step 2, optimizing the basic route by using a deep learning network model: obtaining meteorological information and air traffic control information corresponding to the basic route according to historical route generation experience and correlation learning rules in combination with a network, optimizing and adjusting the route, and generating a flight route meeting safety requirements; and 3, completing three-dimensional route three-dimensional obstacle avoidance by using global high-precision terrain elevation data. According to the invention, the efficiency and accuracy of route input and the efficiency and safety of flight management are improved.

The invention discloses a distribution network unmanned aerial vehicle ground simulation flight method and device based on AI vision and a medium, and the method comprises the steps: collecting a first real-time image in a flight direction in real time in a height calibration stage before an unmanned aerial vehicle flies to a next target tower pole; dynamically adjusting the height of the unmanned aerial vehicle according to the image width ratio of the distribution wire in the first real-time image until the target tower safety height is reached; after the unmanned aerial vehicle flies over the target tower pole according to the target safety height, a second real-time image in the flight direction is collected in real time through the visual sensor; and according to the image width ratio of the power distribution wire in each second real-time image and the real-time positioning information of the unmanned aerial vehicle, controlling the unmanned aerial vehicle to perform flight height change with the height fluctuation of the power distribution wire in the flight direction by taking the target tower pole as a starting point, and according to the technical scheme of the embodiment of the invention, autonomous height adjustment of the unmanned aerial vehicle is realized through visual intelligent analysis; the equipment cost and the operation complexity are greatly reduced, and the inspection efficiency and quality of the unmanned aerial vehicle are remarkably improved.

The embodiment of the invention provides a rocket vertical recovery method and system and a rocket, and the method comprises the steps: after a first-stage rocket is separated, the thrust of a central engine of the first-stage rocket is adjusted to a preset proportion of rated thrust so as to provide positive overload for a propellant in a storage tank; the propellant can be gathered to an outlet in the bottom of the storage tank through positive overload; the flying direction of the first-stage rocket deviates from the current flying direction by performing bidirectional swinging on the central engine, and the posture of downward diving of the first-stage rocket towards the earth direction is kept; tangential force in two different directions tangent to the current flight direction of the first-stage rocket can be generated at the same time by swinging the center engine in two directions, the posture of the first-stage rocket is adjusted to the upward flight posture from the downward diving posture, and speed reduction is conducted till the first-stage rocket lands on the earth. The thrust of the center engine of the first-stage rocket is adjusted to be small, and attitude control and propellant management of first-stage rocket recovery are achieved.

The invention discloses an air confrontation simulation platform based on unity 3D, which relates to the technical field of air confrontation simulation training and comprises a flight controller, a data interaction module, a data analysis module and a terrain design and construction module. Wherein the flight controller is used for controlling the flight attitude, the flight speed and the flight direction of the confrontation simulation aircraft; the data interaction module is used for obtaining the confrontation simulation control instruction through the interaction interface, sending the confrontation simulation control instruction to the confrontation simulation aircraft and returning state information; the data analysis module is used for simulating aerodynamic data in a real environment based on an aerodynamic model and calculating the motion state and the load state of the confrontation simulation aircraft and the missile in real time; and the terrain design and construction module is used for carrying out terrain editing based on unity 3D and generating an adversarial simulation terrain. The technical problem that in the prior art, confrontation training of combination of multiple unmanned aerial vehicles and manned vehicles cannot be carried out is solved.

The invention relates to a control method, a control system and a traction system of a traction unmanned aerial vehicle. The traction unmanned aerial vehicle comprises a plurality of vertical rotors and two tension rotors. The rotation axis direction of each tension rotor wing is the first direction. The traction drone is configured to be connected to the unpowered aircraft through a traction rope. The control method comprises the following steps: acquiring a preset flight direction of the unpowered aircraft; the traction unmanned aerial vehicle is controlled to move to the front upper portion of the unpowered aircraft in the preset flight direction; and controlling the traction unmanned aerial vehicle to pull the unpowered aircraft to rise to a preset height through the traction rope. Wherein the step of controlling the traction unmanned aerial vehicle to pull the unpowered aircraft to rise to the preset height through the traction rope comprises the substeps that when the unpowered aircraft climbs, the angle between the first direction and the direction of the traction rope is controlled to be smaller than or equal to 20 degrees.

The invention discloses an unmanned aerial vehicle autonomous route planning method and system capable of adapting to environmental changes. The method comprises the steps of obtaining a dynamic three-dimensional situation map of a flight area of an unmanned aerial vehicle based on multi-source data of the flight area of the unmanned aerial vehicle; acquiring a current no-fly zone and weather forecast information of the flight area of the unmanned aerial vehicle, and analyzing and acquiring a flight risk distribution condition of the flight area of the unmanned aerial vehicle based on the dynamic three-dimensional situation map; considering the flight risk distribution condition of the unmanned aerial vehicle flight area, the unmanned aerial vehicle flight task and the unmanned aerial vehicle self-state information to generate an unmanned aerial vehicle reference route; and automatically adjusting the flight speed, the flight height and the flight course of the unmanned aerial vehicle according to a preset flight parameter adjustment model based on the acquired multi-source data and the state information of the unmanned aerial vehicle in the process of flying along the reference route. According to the invention, the reliability and safety of flight task execution of the unmanned aerial vehicle in a complex dynamic environment can be improved.

The multi-degree-of-freedom bionic bird flapping-wing aircraft comprises a flight assembly and a fuselage, and a driving assembly and a direction control assembly are arranged on the fuselage; a motor of the driving assembly drives a rotating shaft through a gear transmission mechanism. The flying assembly comprises wing modules which are symmetrically arranged and a linkage driving mechanism, and the linkage driving mechanism converts the rotating motion of the rotating shaft into vertical flapping of the wing modules and different folding angles of the wing modules; the direction control assembly comprises an empennage connected with the fuselage, an empennage steering device, an empennage lifting device and a wing twisting device; the empennage steering device drives the empennage to deflect around the vertical axis of the fuselage to adjust the flight direction of the aircraft; the empennage lifting device drives the empennage to deflect around the transverse axis of the fuselage to adjust the flight height of the aircraft; the wing twisting device drives the wing module to rotate around the longitudinal axis of the wing to adjust the pitch angle of the wing module. According to the invention, flapping folding and twisting can be realized, and a flying function which is extremely similar to that of a real bird is provided.

The invention provides an unmanned aerial vehicle autonomous inspection method and system based on distribution line electromagnetic characteristic driving, an electromagnetic sensor array is carried on an unmanned aerial vehicle, three electromagnetic sensors are adopted to form a triangular arrangement, the two electromagnetic sensors are arranged along the flight direction of the unmanned aerial vehicle, and the connecting line points to the direction of the head of the unmanned aerial vehicle. The relative attitude of the unmanned aerial vehicle and the distribution line is judged; the third electromagnetic sensor is arranged on the other side of the triangle formed by the third electromagnetic sensor and the connecting line and is used for estimating the transverse distance between the unmanned aerial vehicle and the distribution line; the flight height of the unmanned aerial vehicle is obtained by an airborne barometer, and the flight height of the unmanned aerial vehicle is set according to the height of the distribution line in the area. The unmanned aerial vehicle has the advantages that the electromagnetic sensor array is used for collecting electromagnetic signals of the distribution line, the relative position relation between the unmanned aerial vehicle and the distribution line is estimated according to the electromagnetic field distribution condition, autonomous navigation flight of the unmanned aerial vehicle is achieved, GNSS dependence is reduced, and effective routing inspection is conducted in GNSS signal attenuation or interruption zones.

The invention provides a variable step route planning method and system based on unmanned aerial vehicle performance, and relates to the technical field of aeronautical engineering.The method comprises the following steps that flight information of an unmanned aerial vehicle is obtained, the position of a starting point of the unmanned aerial vehicle is initialized, and the course of the starting point serves as the initial flight direction of the unmanned aerial vehicle; the starting point position of the unmanned aerial vehicle is added to a preset to-be-explored node storage list, and a node with the minimum search cost is selected from the to-be-explored node storage list to serve as a current node; and moving the current node into a preset explored node storage list, expanding a neighborhood point of the current node by using a waypoint neighborhood search method, and updating the current node in combination with the search cost and the list position of the neighborhood point. According to the invention, route planning can be carried out on the premise of considering the kinetic energy of the fixed-wing unmanned aerial vehicle, and the traceability of the planned route is ensured.

The invention belongs to the technical field of multi-modal vehicle obstacle avoidance, and relates to a multi-modal vehicle 4D dynamic obstacle avoidance method, which comprises the following steps: taking an air-ground amphibious vehicle, namely a multi-modal vehicle as a center, constructing a plurality of concentrically increasing sphere safety domains which respectively correspond to a collision avoidance area, an early warning area and a trajectory prediction area, the space-time position and the movement track of a dynamic obstacle are monitored and predicted in real time, a three-dimensional space is divided into eight quadrants according to the flight direction based on the current course of a multi-mode vehicle, different sensing priorities and obstacle avoidance strategies are given to the front quadrant, the side quadrant and the rear quadrant, and particularly, the front quadrant, the side quadrant and the rear quadrant have different sensing priorities and obstacle avoidance strategies. Dynamically adjusting the risk level and the obstacle avoidance response according to the relative speed and the movement trend of the obstacle, and carrying out hierarchical and regional risk perception and management on the dynamic obstacle in different space directions and distance ranges; the method is scientific and reliable in principle, and is suitable for a multi-body cooperative obstacle avoidance scene in an urban low-altitude traffic environment.

A method of operating a Synthetic Aperture Radar ‘SAR’ to acquire image data of a swath comprising one or more subswath(s) is provided, wherein the SAR is carried on a platform moving along a flight direction and a radiated beam is directed towards the swath, the method comprising: electronically steering the beam in azimuth direction along one subswath for each burst; and mechanically steering the beam in a direction opposite to the flight direction during each burst. The method allows to obtain an improved swath to resolution ratio.

The present invention discloses a metaverse task offloading and resource scheduling method based on deep reinforcement learning, which relates to the field of wireless communication technology, including: step 1, placing a drone cluster in a user-dense area, and a fixed edge server obtaining the position coordinates of itself, each user and each drone; step 2, the user sends a rendering request to the fixed edge server through the drone cluster; step 3, constructing an optimization target, and converting the optimization target into a Markov decision process, solving the optimization target through the PPO algorithm, and obtaining the horizontal flight rate, flight direction, vertical direction rate and computing resource set available to the drone; step 4, the fixed edge server sends the decision result to the user and the drone, and the user and the drone execute the decision; step 5, after the drone completes the rendering task, the result is transmitted back to the user. The present invention has the characteristics of multi-node collaborative optimization, optimized energy consumption and resource utilization.

This invention proposes a method for fusing multiple interferometric SAR observation data, which can simultaneously perform InSAR data fusion and geolocation, and finally complete the fusion of DEM data in the orthorectified domain. Specifically, this invention combines conventional image registration methods with joint calibration methods, employing a weighted averaging method to fuse multiple InSAR observation data in the orthorectified DEM domain. It can fuse multiple interferometric SAR observation data from different flights, different flight directions, and different perspectives, thereby reducing random errors in the DEM and improving the accuracy of interferometric SAR elevation inversion.

The invention discloses an unmanned helicopter landing guide method based on an offshore motion platform, and the method comprises the following steps: 1) determining a landing guide region according to the position of an unmanned helicopter parking apron on the offshore motion platform; (2) when the unmanned helicopter flies into the landing guide area, recording the position, the flight speed and the flight direction of the unmanned helicopter at the moment of switching to the landing guide stage, and the position, the movement speed and the movement direction of the offshore movement platform; 3) based on the acquired information in the step 2), planning a route of a landing guide stage; 4) calculating an expected track angle of the unmanned helicopter in the vertical direction according to the height of the offshore platform unmanned helicopter parking apron and the height of the unmanned helicopter at the M point; and 5) guiding the unmanned helicopter to land. The invention provides a method for planning the track and the flight speed of an unmanned helicopter in a landing guide stage. The success rate of landing of the unmanned helicopter on an offshore platform in a moving state can be improved in space and time.

The present application relates to the technical field of low-altitude aircraft, in particular to a pre-turning flight ball car control method and a pre-turning flight ball car, wherein the pre-turning flight ball car control method comprises the following steps: S1, obtaining a pre-turning direction and a current direction; S2, calculating a pre-turning angle and a pre-turning adjustment direction based on the pre-turning direction and the current direction; S3, controlling the pre-turning device to drive the flight driving device or the combination of the flight driving device and the cabin to turn relative to the landing gear to face the pre-turning direction according to the pre-turning angle and the pre-turning direction. In this way, the problems of the existing golf cart, such as limitation, and the traditional aircraft, such as increased flight distance and poor passenger experience caused by adjusting the flight direction after take-off, are solved.

In the aerospace industry, the Laval nozzle is primarily used. This nozzle has the problem of not being able to adapt to changes in ambient pressure. Therefore, it loses efficiency as the vehicle ascends. Aerospike nozzles solve this problem, but are more difficult to cool, so they are not a viable alternative to the Laval nozzle. By means of a fixed arrangement of several Laval nozzles, consisting of nozzles (16) directed parallel to the object's flight direction and several nozzles (17) directed at an angle to this jet, the nozzle assembly creates an effect similar to an aerospike. Therefore, at decreasing pressure, such a nozzle assembly exhibits greater efficiency than conventional Laval nozzles. Since the assembly consists entirely of Laval nozzles, it is no more difficult to manufacture and cool than these. Furthermore, the thrust vector exerted by the nozzle assembly, and thus the direction of motion of the object being accelerated, can be controlled by throttling certain secondary nozzles (e.g., 17.2). The resulting fixed connection between the nozzles and combustion chambers allows for higher operating pressure within the combustion chambers, allowing for more efficient fuel use. Since the fixed connection allows for better thrust transfer, the thrust vector can be changed more radically and quickly.

A camera 16 onboard an airborne or spaceborne platform 12, moving in a flight direction 14 around the earth at a flight velocity Vgsat, is pivotable about a roll axis 18 in line with the flight direct