CN114935939A - Real-time path planning system and planning method based on accompanying unmanned aerial vehicle - Google Patents
Real-time path planning system and planning method based on accompanying unmanned aerial vehicle Download PDFInfo
- Publication number
- CN114935939A CN114935939A CN202210498241.8A CN202210498241A CN114935939A CN 114935939 A CN114935939 A CN 114935939A CN 202210498241 A CN202210498241 A CN 202210498241A CN 114935939 A CN114935939 A CN 114935939A
- Authority
- CN
- China
- Prior art keywords
- data
- vehicle
- unmanned aerial
- aerial vehicle
- angle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 22
- RZVHIXYEVGDQDX-UHFFFAOYSA-N 9,10-anthraquinone Chemical compound C1=CC=C2C(=O)C3=CC=CC=C3C(=O)C2=C1 RZVHIXYEVGDQDX-UHFFFAOYSA-N 0.000 claims abstract description 38
- 230000000007 visual effect Effects 0.000 claims description 18
- 230000002123 temporal effect Effects 0.000 claims description 8
- 238000007499 fusion processing Methods 0.000 claims description 6
- 238000012546 transfer Methods 0.000 claims description 2
- 238000005457 optimization Methods 0.000 abstract description 2
- 238000004891 communication Methods 0.000 description 7
- 230000005540 biological transmission Effects 0.000 description 4
- 238000013480 data collection Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000011217 control strategy Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000004806 packaging method and process Methods 0.000 description 1
- 238000004886 process control Methods 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Landscapes
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention provides a real-time path planning system and a planning method based on a flying unmanned aerial vehicle, which solve the technical problem of insufficient real-time information acquisition capability. The system comprises: the airborne computer establishes a relay data link with the vehicle-mounted ground station, forwards the high-view-angle acquisition data and the flight control state data to the vehicle-mounted ground station, and receives a control instruction; the flight control computer is used for forming flight control state data, forwarding the flight control state data to the onboard computer, receiving the control instruction and sending the flight control data corresponding to the control instruction; the airborne sensor is used for acquiring high-visual-angle data according to the corresponding control instruction; the vehicle-mounted ground station receives the high-view-angle collected data and the flight control state data and sends a control instruction through the relay data link; the vehicle-mounted sensor is used for acquiring low-view-angle data according to the corresponding control instruction; and the vehicle-mounted computer is used for fusing the high-view-angle and low-view-angle collected data to form road data and forming a control command according to the data requirement. The method can acquire road information in a wider range, thereby improving the quality and the real-time performance of path optimization.
Description
Technical Field
The invention relates to the technical field of positioning, in particular to a real-time path planning system and a planning method based on a flying unmanned aerial vehicle.
Background
The key technology path planning for realizing unmanned driving can be divided into global path planning and local path planning. The global path planning is a static planning based on complete prior information, and the global path planning means that as much as possible road information needs to be mastered through a high-precision map, the map updating frequency is too slow, so that negative effects are caused on the global path planning, and the manpower and material resource costs are increased when the updating frequency is too fast. To address the above, local path planning may be employed. Local path planning is a dynamic planning based on sensor information. The method comprises the steps of collecting surrounding road information in real time through a sensor, and determining vehicle positioning information and surrounding obstacle information so as to generate a reasonable path. For local path planning, road information acquired by a sensor is crucial, and the more the acquired information is, the more accurate the vehicle positioning information and the surrounding obstacle information is, and the more reasonable the generated path is.
However, there is a limitation in collecting road information only by a sensor mounted on the vehicle itself. First, the sensing range of the sensor may be affected by the shape, size and structure of the vehicle, resulting in a limited sensing range of the sensor. Secondly, under some special terrains, the sensing range of the vehicle-mounted sensor can be greatly compressed, so that the acquired road information is insufficient, and the vehicle positioning information and the surrounding obstacle information are not accurate enough, thereby affecting the path planning effect.
Disclosure of Invention
In view of the above problems, embodiments of the present invention provide a real-time path planning system and a planning method based on a flight accompanying unmanned aerial vehicle, which solve the technical problem that the real-time information acquisition capability of the existing local path planning is insufficient.
The real-time path planning system based on the accompanying unmanned aerial vehicle comprises:
the airborne computer is used for being deployed on the accompanying unmanned aerial vehicle, establishing a relay data link with the vehicle-mounted ground station, forwarding the high-view-angle acquisition data of the airborne sensor and the flight control state data of the accompanying unmanned aerial vehicle to the vehicle-mounted ground station through the relay data link, and receiving control instructions of the flight control computer and the airborne sensor;
the flight control computer is used for being deployed on the accompanying unmanned aerial vehicle, acquiring the state of an executing mechanism of the accompanying unmanned aerial vehicle to form flight control state data, forwarding the flight control state data to the onboard computer, receiving the control instruction and sending the flight control data corresponding to the control instruction to the executing mechanism of the accompanying unmanned aerial vehicle;
the airborne sensor is used for being deployed on the accompanying unmanned aerial vehicle, performing high-view-angle data acquisition according to sensor control data corresponding to the control instruction and feeding back the data to the airborne computer;
the vehicle-mounted ground station is used for being deployed on a vehicle to establish a relay data link with an onboard computer, receiving high-view-angle acquired data and flight control state data through the relay data link and sending a control instruction;
the vehicle-mounted sensor is used for being deployed on a vehicle, acquiring low-view-angle data according to sensor control data corresponding to the control instruction and feeding the low-view-angle data back to a vehicle-mounted computer;
and the vehicle-mounted computer is used for being deployed on a vehicle, fusing the high visual angle acquisition data and the low visual angle acquisition data to form road data, and forming a control instruction accompanying the unmanned aerial vehicle and various sensors according to data requirements.
In an embodiment of the present invention, the accompanying unmanned aerial vehicle is a tethered unmanned aerial vehicle or a non-tethered unmanned aerial vehicle.
In an embodiment of the invention, the airborne sensor comprises an altimeter, an airspeed head, a camera, a laser radar or a satellite positioning device.
In an embodiment of the present invention, the relay data link is formed by a data transfer station, a wifi network, a 4G network, or a 5G network.
In an embodiment of the invention, the vehicle-mounted sensor comprises a camera, a laser radar, a millimeter wave radar, an ultrasonic radar, a combined inertial navigation device, a satellite positioning instrument or a strapdown inertial navigation device.
In an embodiment of the present invention, the accompanying unmanned aerial vehicle and the vehicle keep speed synchronization.
In an embodiment of the present invention, the flight control computer, the airborne computer, the vehicle-mounted computer or the vehicle-mounted ground station may adopt a DSP, an FPGA, an MCU system board, an SoC system board or a PLC minimum system including an input/output port.
The real-time path planning method based on the accompanying unmanned aerial vehicle of the embodiment of the invention utilizes the real-time path planning system based on the accompanying unmanned aerial vehicle, and comprises the following steps:
the vehicle-mounted sensor acquires low visual angle acquisition data during the running process of the vehicle, the accompanying unmanned aerial vehicle is launched, the accompanying unmanned aerial vehicle flies above the vehicle, and the vehicle-mounted sensor acquires high visual angle acquisition data and transmits the high visual angle acquisition data to the vehicle-mounted computer through a relay data link;
the vehicle-mounted computer performs fusion processing on the time sequence and the coordinates of the current high-view-angle collected data and the current low-view-angle collected data to form road data in a general data space;
and planning a path according to the road data in the universal data space.
In an embodiment of the present invention, the fusing, by the vehicle-mounted computer, the time sequence and the coordinates of the current high view angle data and the current low view angle data to form road data in a general data space includes:
acquiring a vehicle driving position through positioning data in low-visual-angle acquisition data, and establishing a spatial clustering mass center and a temporal clustering mass center in a universal data space according to coordinate information and time information in the positioning data;
performing spatial clustering and temporal clustering on the high-view acquired data in the general data space according to the coordinate information and the time information in the high-view acquired data to form a position data set and a time data set;
performing type data association in a position data set of the determined position to form data dimensionality of the road data;
and updating type data in a time data set with determined time to form updating of road data.
In an embodiment of the invention, in the process of launching the accompanying unmanned aerial vehicle, the control instruction includes an unmanned aerial vehicle height adjustment instruction, an unmanned aerial vehicle pointing instruction or an airborne sensor pointing instruction.
According to the real-time path planning system and the planning method based on the accompanying unmanned aerial vehicle, disclosed by the embodiment of the invention, on the basis of the existing road data acquisition, when the sensing range of the vehicle-mounted sensor is limited, the sensing range of a vehicle is expanded by using the sensor carried by the accompanying unmanned aerial vehicle, and road information in a wider range can be acquired, so that the quality and the real-time property of path optimization are improved.
Drawings
Fig. 1 is a schematic structural diagram of a real-time path planning system based on a flying drone according to an embodiment of the present invention.
Fig. 2 is a schematic flow chart of a real-time path planning method based on a flying drone according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer and more obvious, the present invention is further described below with reference to the accompanying drawings and the detailed description. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
An embodiment of the invention is a real-time path planning system based on a companion unmanned aerial vehicle, as shown in fig. 1. In fig. 1, the present embodiment includes:
and the airborne computer 11 is configured to be deployed on the accompanying unmanned aerial vehicle 01, establish a relay data link with the vehicle-mounted ground station 21, forward the high-view-angle acquisition data of the airborne sensor 13 and the flight control state data of the accompanying unmanned aerial vehicle 01 to the vehicle-mounted ground station 21 through the relay data link, and receive control instructions of the flight control computer 12 and the airborne sensor 13.
Those skilled in the art will appreciate that the companion drone may select a tethered drone or a non-tethered drone depending on the duration and the perceived range of demand. Tethered drones form wired communication lines with tethered cables to establish relay data links, and non-tethered drones utilize wireless communication channels to establish relay data links. The accompanying unmanned aerial vehicle comprises a carried effective load, wherein the effective load comprises but is not limited to professional sensors, business processors and the like, and the accompanying unmanned aerial vehicle body comprises an electromechanical execution system necessary for flight control. The real-time state of the electromechanical execution system reflects the flight control state of the accompanying unmanned aerial vehicle.
Those skilled in the art will appreciate that relay data link establishment requires corresponding communication hardware support. The types of the relay data link which can be formed by the communication hardware which is configured end to end on the accompanying unmanned aerial vehicle and the vehicle include but are not limited to a data transmission radio station, a wifi data transmission, a 4G/5G data transmission and the like.
And the flight control computer 12 is configured to be deployed on the accompanying unmanned aerial vehicle 01, acquire the state of the execution mechanism of the accompanying unmanned aerial vehicle 01 to form flight control state data, forward the flight control state data to the onboard computer 11, receive the control instruction, and send the flight control data corresponding to the control instruction to the execution mechanism of the accompanying unmanned aerial vehicle 01.
Those skilled in the art will appreciate that there is a data connection between the flight control computer and the actuator. Quantitative data on the real-time flight control state can be obtained through a sensor or a physical parameter register in an actuating mechanism. The necessary data connection also exists between the flight control computer and the airborne computer. The flight control computer is internally provided with a flight overall control strategy and has a data processing function of converting the relative abstract control instruction into concrete control data of a concrete execution mechanism. The abstract control instruction and the specific accompanying unmanned aerial vehicle type specific flight control process control data can be decoupled through the flight control computer, the data volume of the control instruction is reduced, and the reliability of the control instruction is improved.
And the airborne sensor 13 is used for being deployed on the accompanying unmanned aerial vehicle 01, acquiring high-view data according to the sensor control data corresponding to the control instruction and feeding back the high-view data to the airborne computer 11.
Those skilled in the art will appreciate that the necessary data connections exist between the on-board sensors and the on-board computers. The airborne sensor can form high visual angle, multi-visual distance, multi-focus and multi-type road data collection with different elevations along with the accompanying unmanned aerial vehicle through initialization and real-time control. Airborne sensors include, but are not limited to, altimeters, airspeeds, cameras, lidar, satellite positioning devices, and the like. The sensor control data corresponding to the control instruction is usually preset in a control component of the airborne sensor module, and the corresponding sensor control data is triggered to control the airborne sensor according to the corresponding control instruction.
And the vehicle-mounted ground station 21 is used for being deployed on the vehicle 02 to establish a relay data link with the onboard computer 11, receiving the high-view-angle collected data and the flight control state data through the relay data link, and sending a control instruction.
Those skilled in the art will appreciate that the vehicle itself has a local area communication network thereon. The relay data link of the local area communication network extension can be formed by the cooperation of the vehicle-mounted ground station and the airborne computer. The relay data link has the characteristics of necessary bandwidth and time delay, and can meet the data transmission requirement between the accompanying unmanned aerial vehicle and the vehicle.
And the vehicle-mounted sensor 22 is used for being deployed on the vehicle 02, acquiring low-view-angle data according to sensor control data corresponding to the control instruction and feeding the low-view-angle data back to the vehicle-mounted computer 22.
Those skilled in the art will appreciate that the necessary data connections exist between the in-vehicle sensors and the in-vehicle computer. The vehicle-mounted sensor can form high visual angle, multiple visual distances, multiple focuses and multiple types of road data collection in the same elevation along with the vehicle through initialization and real-time control. The vehicle-mounted sensor includes, but is not limited to, a camera, a laser radar, a millimeter wave radar, an ultrasonic radar, a combined inertial navigation device, a satellite positioning device, a strapdown inertial navigation device, and the like.
And the vehicle-mounted computer 23 is used for being deployed on the vehicle 02, fusing the high-view-angle collected data and the low-view-angle collected data to form road data, and forming a control instruction of the accompanying unmanned aerial vehicle 01 and various sensors according to data requirements.
It will be appreciated by those skilled in the art that real-time high view acquisition data and low view acquisition data may be obtained via a local area communication network on the vehicle. The vehicle-mounted computer performs fusion processing on the collected data in three-dimensional space and time sequence to form road data in a unified packaging form. And forming a real-time path plan according to the road data. Meanwhile, the data requirements for the high-visual-angle data acquisition are formed according to the path planning distance, the accuracy and the interference factors, and the acquisition of the high-visual-angle data is adjusted by the control instructions of the accompanying unmanned aerial vehicle and various sensors.
In one embodiment of the invention, the companion unmanned aerial vehicle maintains equal ratio or equal ratio synchronization of speed with the vehicle
According to the embodiment of the invention, on the basis of the existing road data acquisition, when the sensing range of the vehicle-mounted sensor is limited, the sensing range of the vehicle is expanded by using the sensor carried by the accompanying unmanned aerial vehicle, and road information in a wider range can be acquired, so that the accuracy of vehicle positioning information and surrounding obstacle information is improved.
An embodiment of the invention is a real-time path planning method based on a companion unmanned aerial vehicle, as shown in fig. 2. In fig. 2, in the present embodiment, the real-time path planning system of the foregoing embodiment is utilized, and the method includes:
step 100: the vehicle-mounted sensor acquires low visual angle acquisition data during the running process of the vehicle, the accompanying unmanned aerial vehicle is launched, the accompanying unmanned aerial vehicle flies above the vehicle, and the vehicle-mounted sensor acquires high visual angle acquisition data and transmits the high visual angle acquisition data to the vehicle-mounted computer through a relay data link;
when the vehicle is started, the vehicle-mounted sensor starts to collect road information of low visual angles around the vehicle. Meanwhile, the accompanying unmanned aerial vehicle is put in due time according to the collection limitation of the road information. And collecting road information of high visual angles around the vehicle through an onboard sensor.
The control instruction in the process of launching the accompanying unmanned aerial vehicle comprises an unmanned aerial vehicle height adjusting instruction, an unmanned aerial vehicle pointing instruction or an airborne sensor pointing instruction.
Step 200: the vehicle-mounted computer performs fusion processing on the time sequence and the coordinates of the current high-view-angle collected data and the current low-view-angle collected data to form road data in a general data space;
the vehicle-mounted computer performs fusion processing on the high-view-angle collected data and the low-view-angle collected data through dimensions such as data formats, data dimensions and data indexes to form generalized road data in a unified time sequence and a unified coordinate space.
Step 300: and planning a path according to the road data in the universal data space.
And forming real-time path planning by using the established road data and a mature path planning model and combining the vehicle condition and the destination.
The real-time path planning method based on the accompanying unmanned aerial vehicle, disclosed by the embodiment of the invention, utilizes the high-visual-angle airborne sensor to obtain a larger and more flexible acquisition range, obtains real-time geographic terrain data in a wider range around the vehicle, and improves the accuracy of determining the positioning information of the vehicle and the information of surrounding obstacles, thereby ensuring the quality and real-time performance of real-time path planning.
As shown in fig. 2, in an embodiment of the present invention, the fusion process of step 200 includes:
step 210: acquiring a vehicle driving position through positioning data in low-visual-angle acquisition data, and establishing a spatial clustering mass center and a temporal clustering mass center in a general data space according to coordinate information and time information in the positioning data;
the spatial clustering centroid can be a road node coordinate in the earlier-stage path planning and can also be an obstacle outline coordinate in the earlier-stage path planning. The temporal clustering centroid may be a time period node or a timing node.
Step 220: performing spatial clustering and temporal clustering on the high-view acquired data in the general data space according to coordinate information and time information in the high-view acquired data to form a position data set and a time data set;
and carrying out data clustering by utilizing a spatial clustering mass center and/or a temporal clustering mass center through coordinate information and time information in the high-view-angle collected data, so that the high-view-angle collected data and the low-view-angle collected data can be subjected to data fusion around a coordinate position and/or a time node.
Step 230: performing type data association in a position data set of the determined position to form data dimensionality of the road data;
and integrally processing the same type of data in the high-view acquired data and the low-view acquired data to form single-dimensional data, and distinguishing the different types of data to form other determined dimensional data.
Step 240: and updating type data in a time data set with determined time to form updating of road data.
And updating single-dimensional data in the high-view-angle collected data and the low-view-angle collected data according to a time sequence to realize the ordered updating of the road data.
According to the real-time path planning method based on the accompanying unmanned aerial vehicle, the high-view-angle collected data and the low-view-angle collected data are formed by clustering the data coordinates and the time dimensions, so that the collected data of various types and the spatial position data can be orderly fused, the effective association of various information dimensions of local roads is directly reflected, and the data availability and the data application efficiency during path planning are improved.
In an embodiment of the present invention, the flight control computer, the onboard computer, or the onboard ground station may adopt a dsp (digital Signal processor), an FPGA (Field-Programmable Gate Array), an mcu (microcontroller unit) system board, an soc (system on a chip) system board, or a plc (Programmable Logic controller) minimum system including I/O.
While the invention has been described with reference to specific preferred embodiments, it will be understood by those skilled in the art that various changes and modifications may be made without departing from the spirit and scope of the invention as defined in the following claims. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.
Claims (10)
1. A real-time path planning system based on a companion unmanned aerial vehicle is characterized by comprising:
the airborne computer is used for being deployed on the accompanying unmanned aerial vehicle, establishing a relay data link with the vehicle-mounted ground station, forwarding the high-view-angle acquisition data of the airborne sensor and the flight control state data of the accompanying unmanned aerial vehicle to the vehicle-mounted ground station through the relay data link, and receiving control instructions of the flight control computer and the airborne sensor;
the flight control computer is used for being deployed on the accompanying unmanned aerial vehicle, acquiring the state of the executing mechanism of the accompanying unmanned aerial vehicle to form flight control state data, forwarding the flight control state data to the onboard computer, receiving the control instruction and sending the flight control data corresponding to the control instruction to the executing mechanism of the accompanying unmanned aerial vehicle;
the airborne sensor is used for being deployed on the accompanying unmanned aerial vehicle, performing high-view-angle data acquisition according to sensor control data corresponding to the control instruction and feeding back the data to the airborne computer;
the vehicle-mounted ground station is used for being deployed on a vehicle to establish a relay data link with an onboard computer, receiving high-view-angle acquired data and flight control state data through the relay data link and sending a control instruction;
the vehicle-mounted sensor is used for being deployed on a vehicle, acquiring low-view-angle data according to sensor control data corresponding to the control instruction and feeding the low-view-angle data back to a vehicle-mounted computer;
the vehicle-mounted computer is used for being deployed on a vehicle, integrating the high visual angle acquisition data and the low visual angle acquisition data to form road data, and forming a control instruction of the accompanying unmanned aerial vehicle and various sensors according to data requirements.
2. The real-time path planning system based on companion unmanned aerial vehicle of claim 1, wherein the companion unmanned aerial vehicle employs a tethered unmanned aerial vehicle or a non-tethered unmanned aerial vehicle.
3. The companion unmanned aerial vehicle-based real-time path planning system of claim 1, wherein the onboard sensor comprises an altimeter, an airspeed tube, a camera, a lidar, or a satellite positioning device.
4. The accompanying unmanned aerial vehicle-based real-time path planning system of claim 1, wherein the relay data link is formed by a data transfer station, a wifi network, a 4G network, or a 5G network.
5. The real-time path planning system based on a companion unmanned aerial vehicle of claim 1, wherein the onboard sensor comprises a camera, a lidar, a millimeter wave radar, an ultrasonic radar, a combined inertial navigation device, a satellite positioning unit, or a strapdown inertial navigation device.
6. The companion unmanned aerial vehicle based real-time path planning system of claim 1 wherein said companion unmanned aerial vehicle maintains speed synchronization with said vehicle.
7. The accompanying unmanned aerial vehicle-based real-time path planning system of claim 1, wherein the flight control computer, the onboard computer or the onboard ground station may employ a DSP, an FPGA, an MCU system board, an SoC system board or a PLC minimum system including input and output ports.
8. A method for planning a real-time path based on a companion unmanned aerial vehicle, which is characterized in that the real-time path planning system based on the companion unmanned aerial vehicle as claimed in any one of claims 1 to 7 is utilized, and comprises:
the vehicle-mounted sensor acquires low visual angle acquisition data during the running process of the vehicle, the accompanying unmanned aerial vehicle is launched, the accompanying unmanned aerial vehicle flies above the vehicle, and the vehicle-mounted sensor acquires high visual angle acquisition data and transmits the high visual angle acquisition data to the vehicle-mounted computer through a relay data link;
the vehicle-mounted computer performs fusion processing on the time sequence and the coordinates of the current high-visual-angle acquired data and the current low-visual-angle acquired data to form road data in a general data space;
and planning a path according to the road data in the universal data space.
9. The method as claimed in claim 8, wherein the step of fusing the timing and coordinates of the current high view angle data and the current low view angle data by the vehicle-mounted computer to form road data in a general data space comprises:
acquiring a vehicle driving position through positioning data in low-visual-angle acquisition data, and establishing a spatial clustering mass center and a temporal clustering mass center in a universal data space according to coordinate information and time information in the positioning data;
performing spatial clustering and temporal clustering on the high-view acquired data in the general data space according to the coordinate information and the time information in the high-view acquired data to form a position data set and a time data set;
performing type data association in a position data set of the determined position to form data dimensionality of the road data;
and updating type data in a time data set with determined time to form updating of road data.
10. The method according to claim 8, wherein the control command comprises a command for adjusting the height of the drone, a command for directing the drone, or a command for directing an onboard sensor during the launching of the drone.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210498241.8A CN114935939A (en) | 2022-05-09 | 2022-05-09 | Real-time path planning system and planning method based on accompanying unmanned aerial vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210498241.8A CN114935939A (en) | 2022-05-09 | 2022-05-09 | Real-time path planning system and planning method based on accompanying unmanned aerial vehicle |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114935939A true CN114935939A (en) | 2022-08-23 |
Family
ID=82864218
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210498241.8A Pending CN114935939A (en) | 2022-05-09 | 2022-05-09 | Real-time path planning system and planning method based on accompanying unmanned aerial vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114935939A (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110779496A (en) * | 2018-07-30 | 2020-02-11 | 阿里巴巴集团控股有限公司 | Three-dimensional map construction system, method, device and storage medium |
| CN111169479A (en) * | 2020-01-14 | 2020-05-19 | 中国第一汽车股份有限公司 | Cruise control method, device and system, vehicle and storage medium |
| WO2021196529A1 (en) * | 2020-04-02 | 2021-10-07 | 同济人工智能研究院(苏州)有限公司 | Air-ground cooperative intelligent inspection robot and inspection method |
-
2022
- 2022-05-09 CN CN202210498241.8A patent/CN114935939A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110779496A (en) * | 2018-07-30 | 2020-02-11 | 阿里巴巴集团控股有限公司 | Three-dimensional map construction system, method, device and storage medium |
| CN111169479A (en) * | 2020-01-14 | 2020-05-19 | 中国第一汽车股份有限公司 | Cruise control method, device and system, vehicle and storage medium |
| WO2021196529A1 (en) * | 2020-04-02 | 2021-10-07 | 同济人工智能研究院(苏州)有限公司 | Air-ground cooperative intelligent inspection robot and inspection method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11846510B2 (en) | Feature matching and correspondence refinement and 3D submap position refinement system and method for centimeter precision localization using camera-based submap and LiDAR-based global map | |
| CN111448476B (en) | Technique for sharing mapping data between unmanned aerial vehicle and ground vehicle | |
| EP3620959B1 (en) | Image data acquisition logic of an autonomous driving vehicle for capturing image data using cameras | |
| CN110606071A (en) | Parking method, parking device, vehicle and storage medium | |
| US11029165B2 (en) | Sensor integration and synchronization unit for an autonomous driving vehicle | |
| JP2020527500A (en) | Methods and equipment for calibrating external parameters of onboard sensors | |
| US10228691B1 (en) | Augmented radar camera view for remotely operated aerial vehicles | |
| US11269077B2 (en) | Flexible test board to improve sensor i/o coverage for autonomous driving platform | |
| CN108520640B (en) | Ultra-wideband-based unmanned aerial vehicle navigation method, navigation equipment and unmanned aerial vehicle | |
| US10966069B1 (en) | Systems and methods for HD map generation using an edge server network | |
| CN105022405A (en) | Street view map production method, control server, unmanned aerial vehicle and production device | |
| WO2022116000A1 (en) | Communication method and apparatus | |
| US11754415B2 (en) | Sensor localization from external source data | |
| CN108319292A (en) | A kind of control method of unmanned vehicle, console, aircraft and control system | |
| AU2021106247A4 (en) | Vehicle fusion positioning method based on V2X and laser point cloud registration for advanced automatic driving | |
| US11204248B2 (en) | Navigating using electromagnetic signals | |
| EP3642684B1 (en) | Data transfer logic for transferring data between sensors and planning and control of autonomous driving vehicle | |
| WO2020220199A1 (en) | Multiple sensor data storage with compressed video stream in autonomous driving vehicles | |
| CN114047760A (en) | Path planning method and device, electronic equipment and automatic driving vehicle | |
| CN109163718A (en) | A kind of unmanned plane autonomous navigation method towards groups of building | |
| CN114935939A (en) | Real-time path planning system and planning method based on accompanying unmanned aerial vehicle | |
| CN205080435U (en) | Control server, unmanned aerial vehicle and streetscape map making devices | |
| CN217435657U (en) | Electrical system of automatic driving vehicle and automatic driving vehicle | |
| CN114415489B (en) | Time synchronization method, device, equipment and medium for vehicle-mounted sensor | |
| US20240068838A1 (en) | Methods and systems for distributing high definition map using edge device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |