CN114153203A - Unmanned equipment control method, device, equipment and storage medium - Google Patents
Unmanned equipment control method, device, equipment and storage medium Download PDFInfo
- Publication number
- CN114153203A CN114153203A CN202111315342.9A CN202111315342A CN114153203A CN 114153203 A CN114153203 A CN 114153203A CN 202111315342 A CN202111315342 A CN 202111315342A CN 114153203 A CN114153203 A CN 114153203A
- Authority
- CN
- China
- Prior art keywords
- unmanned equipment
- risk
- unmanned
- information
- risk area
- 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.)
- Withdrawn
Links
- 238000000034 method Methods 0.000 title claims abstract description 68
- 238000003860 storage Methods 0.000 title claims abstract description 21
- 238000004590 computer program Methods 0.000 claims description 16
- 230000007613 environmental effect Effects 0.000 claims description 9
- 238000002372 labelling Methods 0.000 claims description 3
- 238000001514 detection method Methods 0.000 description 19
- 230000001276 controlling effect Effects 0.000 description 14
- 238000010586 diagram Methods 0.000 description 13
- 230000006870 function Effects 0.000 description 10
- 230000006872 improvement Effects 0.000 description 10
- 230000005540 biological transmission Effects 0.000 description 9
- 230000008569 process Effects 0.000 description 9
- 238000012545 processing Methods 0.000 description 7
- 230000000875 corresponding effect Effects 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 6
- 230000002596 correlated effect Effects 0.000 description 5
- 238000004891 communication Methods 0.000 description 4
- 238000005259 measurement Methods 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000000007 visual effect Effects 0.000 description 3
- 230000002776 aggregation Effects 0.000 description 2
- 238000004220 aggregation Methods 0.000 description 2
- 230000001934 delay Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000007123 defense Effects 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000005055 memory storage Effects 0.000 description 1
- 229920001296 polysiloxane Polymers 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000003068 static 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
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
-
- 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
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Aviation & Aerospace Engineering (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Electromagnetism (AREA)
- Traffic Control Systems (AREA)
Abstract
The specification discloses a method, a device, equipment and a storage medium for controlling unmanned equipment, wherein the distance between the unmanned equipment and a risk area is determined according to acquired information of a pre-marked risk area and position information of the unmanned equipment, and the unmanned equipment is controlled according to the distance. The unmanned equipment is automatically controlled based on the distance between the unmanned equipment and the risk area, so that even if a security officer does not intervene in time, the security risk caused by the risk area can be avoided, and the safety of automatic driving of the unmanned equipment is improved.
Description
Technical Field
The present disclosure relates to the field of unmanned driving technologies, and in particular, to an unmanned device control method, apparatus, device, and storage medium.
Background
At present, unmanned equipment is widely applied to multiple fields such as national defense and national economy, and the unmanned equipment is further developed along with the continuous improvement of technological level, so that more convenience is brought to the life of people. The drone may perceive the road environment and automatically plan a route and reach a predetermined target according to the road environment. However, during unmanned autonomous driving, some risk areas are encountered that are not suitable for autonomous driving.
In the prior art, in the case of the risk area, a security officer can only take over the unmanned equipment in time, and a method for controlling the unmanned equipment to stop in an emergency way or remotely control the unmanned equipment to pass through the risk area is adopted.
However, this control method requires the security officer to track the status of the unmanned device in real time, and if the security officer does not perform the first time processing, the unmanned device performs unmanned automatic driving in the risk area, and accidents are very likely to occur.
Disclosure of Invention
The present specification provides an unmanned aerial vehicle control, apparatus, device, and storage medium and apparatus that partially solve the above-mentioned problems of the prior art.
The technical scheme adopted by the specification is as follows:
the present specification provides an unmanned device control method, which is applied to an unmanned device, the method including:
acquiring information of a pre-labeled risk area sent by a server; the risk area is marked according to the position information of each type of event reported by each unmanned device history;
acquiring real-time position information of the unmanned equipment;
determining the distance between the current unmanned equipment and the risk area based on the information of the risk area and the real-time position information of the unmanned equipment;
and controlling the unmanned equipment according to the distance.
Optionally, controlling the unmanned device according to the distance specifically includes:
if the distance is larger than the distance threshold determined by the unmanned equipment, the unmanned equipment keeps the current driving state;
and if the distance is not greater than the distance threshold determined by the unmanned equipment, the unmanned equipment sends early warning information to the server and/or stops driving.
Optionally, the determining, by the unmanned device, the distance threshold specifically includes:
acquiring environmental information of the current position of the unmanned equipment according to the real-time position information of the unmanned equipment;
according to the information of the pre-labeled risk areas, determining the risk level of each type of risk area;
and determining the distance threshold according to the environmental information of the current position of the unmanned equipment and the risk level of the risk area.
Optionally, controlling the unmanned device according to the distance specifically includes:
acquiring the self state information of the current unmanned equipment;
according to the information of the pre-labeled risk areas, determining the risk level of each type of risk area;
determining a driving strategy of the unmanned equipment for dealing with the risk area according to the state information of the unmanned equipment, the risk level of the risk area and the distance between the unmanned equipment and the risk area;
and controlling the unmanned equipment according to the driving strategy.
The specification provides an unmanned equipment control method, which is applied to a server and comprises the following steps:
acquiring information of a pre-marked risk area; the risk area is marked according to the position information of each type of event reported by each unmanned device history;
and sending the information of the risk area to unmanned equipment so that the unmanned equipment controls the unmanned equipment according to the real-time position information of the unmanned equipment and the information of the risk area.
Optionally, the pre-labeling of the risk area specifically includes:
receiving each event reported by each unmanned device in advance;
aiming at each event type, selecting the type of event from the received events;
for each type of event, determining the position of the unmanned equipment when the type of event occurs as the type of risk position;
and determining an area containing at least one risk position of the type according to the type of risk position determined aiming at each type of event, and marking the area as a risk area.
The present specification provides an unmanned aerial vehicle control apparatus, the apparatus being applied to an unmanned aerial vehicle, the apparatus including:
the first acquisition module is used for acquiring information of a pre-labeled risk area sent by the server; the risk area is marked according to the position information of each type of event reported by each unmanned device history;
the second acquisition module is used for acquiring the real-time position information of the unmanned equipment;
the distance determining module is used for determining the distance between the current unmanned equipment and the risk area based on the information of the risk area and the real-time position information of the unmanned equipment;
and the control module is used for controlling the unmanned equipment according to the distance.
The present specification provides an unmanned equipment control apparatus, the apparatus being applied to a server, the apparatus including:
the third acquisition module is used for acquiring information of the pre-labeled risk area; the risk area is marked according to the position information of each type of event reported by each unmanned device history;
and the sending module is used for sending the information of the risk area to the unmanned equipment so that the unmanned equipment can control the unmanned equipment according to the real-time position information of the unmanned equipment and the information of the risk area.
The present specification provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the above-mentioned unmanned device control method when executing the program.
The present specification provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the above-described unmanned aerial device control method.
The embodiment of the specification adopts at least one technical scheme which can achieve the following beneficial effects:
the method determines the distance between the unmanned equipment and the risk area according to the information of the risk area marked in advance and the position information of the unmanned equipment, and controls the unmanned equipment according to the distance. The method automatically controls the unmanned equipment based on the distance between the unmanned equipment and the risk area, so that the safety risk caused by the risk area can be avoided even if a safety worker does not intervene in time, and the safety of automatic driving of the unmanned equipment is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the specification and are incorporated in and constitute a part of this specification, illustrate embodiments of the specification and together with the description serve to explain the specification and not to limit the specification in a non-limiting sense. In the drawings:
fig. 1 is a schematic flow chart of an unmanned aerial vehicle control method in the present specification;
FIG. 2 is a schematic flow chart of another method for controlling an unmanned aerial vehicle according to the present disclosure;
FIG. 3 is a schematic diagram of an unmanned aerial vehicle control apparatus provided herein;
FIG. 4 is a schematic view of another drone controlling device provided herein;
fig. 5 is a schematic diagram of an electronic device provided in this specification.
Detailed Description
In order to make the objects, technical solutions and advantages of the present disclosure more clear, the technical solutions of the present disclosure will be clearly and completely described below with reference to the specific embodiments of the present disclosure and the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present disclosure, and not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present specification without any creative effort belong to the protection scope of the present specification.
The technical solutions provided by the embodiments of the present description are described in detail below with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of an unmanned aerial vehicle control method provided in an embodiment of the present specification, which specifically includes the following steps:
s100: acquiring information of a pre-labeled risk area sent by a server; and marking the risk area according to the position information of each type of event reported by each unmanned device history.
In the embodiment of the present specification, the method for controlling an unmanned aerial vehicle as shown in fig. 1 may be applied to an unmanned aerial vehicle, which may be an unmanned vehicle or an autonomous device such as an unmanned aerial vehicle. The unmanned equipment senses the road environment through the configured sensors, and automatically plans a route according to the road environment and reaches a preset target.
In practical application, in the process of automatic driving, the unmanned equipment can meet a risk area which is not suitable for automatic driving, and the unmanned equipment carries out unmanned automatic driving in the risk area, so that accidents are easily caused. The unmanned equipment acquires the information of the pre-marked risk area, controls the unmanned equipment according to the information of the risk area, and can ensure the safety of automatic driving of the unmanned equipment.
The information of the risk area may include information of the risk type, location, size, etc. of the risk area. Wherein the position of the risk area is determined by the position (including longitude, latitude, altitude) of the edge of the area on the map. The risk area may be of any geometric shape, which the present specification does not limit.
The server is in communication connection with the unmanned device. Specifically, the unmanned device may obtain information and instructions sent by the server, or may upload event information. The information sent by the server may include information of risk areas sent by the server to the drone; the instructions sent by the server can comprise control instructions for remotely controlling the unmanned equipment to run; the events may include positioning errors, transmission delays, target detection, take-over, etc. of the unmanned device during autonomous driving. The communication connection may comprise various connection types, including wired, wireless communication links, and the like.
S102: and acquiring the real-time position information of the unmanned equipment.
In practical applications, in order to obtain the position information of the unmanned aerial device, the unmanned aerial device may include a positioning device. The Positioning device includes a Positioning module (e.g., a Global Positioning System (GPS)), and an environment data acquisition module (e.g., a laser radar, a camera sensor, etc.) and an Inertial measurement module (e.g., an Inertial Measurement Unit (IMU)) communicatively connected to the Positioning module. The positioning module in the unmanned equipment determines the position information of the unmanned equipment according to the data acquired by the environment data acquisition module and the inertia measurement module.
S104: and determining the distance between the current unmanned equipment and the risk area based on the information of the risk area and the real-time position information of the unmanned equipment.
When determining the distance between the current unmanned equipment and the risk area, determining the relation between the edge of the risk area and the automatic driving route of the unmanned equipment.
For example, since the autonomous driving route of the unmanned aerial vehicle passes through the risk area a and the unmanned aerial vehicle needs to be controlled according to the distance between the unmanned aerial vehicle itself and the risk area a, the distance between the leading end of the unmanned aerial vehicle and the overlapping position B of the edge of the risk area a and the autonomous driving route is taken as the distance, and the unmanned aerial vehicle is controlled according to the distance. It should be noted that the above scenario is only one case of the embodiment of the present specification, and is not a limitation on the actual determination method of the distance between the unmanned device itself and the risk area at present, and the distance may be determined according to the actual situation.
S106: and controlling the unmanned equipment according to the distance.
Optionally, the distance is compared with a distance threshold determined by the unmanned device, and the unmanned device is controlled according to a comparison result. If the distance is larger than the distance threshold determined by the unmanned equipment, the unmanned equipment keeps the current driving state; and if the distance is not greater than the distance threshold determined by the unmanned equipment, the unmanned equipment sends early warning information to the server and/or stops driving. That is, when the distance between the drone and the risk area is less than the distance threshold, then the autonomous driving of the drone is considered to be at a safety risk. The number of the distance thresholds, specific numerical values, and the like are not limited in the present specification.
Specifically, when the distance is smaller than a first set distance threshold, the unmanned equipment sends early warning information to the server; if the server does not respond to the early warning information before the unmanned equipment reaches the second set distance threshold, stopping running of the unmanned equipment when the distance is not greater than the second set distance threshold. Wherein the first set distance threshold is greater than the second set distance threshold.
Optionally, the distance threshold is determined according to environmental information of the current location of the unmanned aerial vehicle and a risk level of a risk area.
Specifically, the unmanned equipment acquires the environmental information of the current position of the unmanned equipment through sensors such as a laser radar and a camera configured on the unmanned equipment according to the real-time position information of the unmanned equipment. The environmental information may include weather information, temperature information, etc. of the current location of the unmanned aerial device. Due to the fact that the normal work of sensors such as a laser radar and a camera can be influenced by the environments such as fog, rain, snow, strong light, dust and low temperature, even the conditions of failure can occur, the environment severity is determined according to the environment information of the current position of the unmanned equipment. When the environment of the position where the unmanned equipment is located is severe, the distance threshold value is properly increased, so that the server receives early warning information sent by the unmanned equipment earlier, and then responds to the early warning information sent by the unmanned equipment earlier. The distance threshold is positively correlated with the environmental severity.
And the unmanned equipment determines the risk level of each type of risk area according to the information of the risk areas pre-labeled by the server. The distance threshold is positively correlated with the risk level. That is, the risk area of high risk level needs to transmit the warning information to the server earlier than the risk area of low risk level in order for the server to respond to the warning information transmitted by the unmanned device.
In practical applications, the sending of the warning information to the server by the unmanned device may include taking over request information. For each piece of early warning information, determining the priority of the early warning information according to the time for sending the early warning information by the unmanned equipment, the risk level of the risk area, the distance between the unmanned equipment and the risk area and the response condition of the server to the early warning information; the priority of the early warning information is positively correlated with the time when the unmanned equipment sends the early warning information and the risk level of the risk area, and is negatively correlated with the distance between the unmanned equipment and the risk area.
Aiming at each early warning information, determining an early warning mode of the early warning information according to the priority of the early warning information; the early warning mode comprises visual signal early warning, acousto-optic signal early warning and the like; the strength of the early warning mode is positively correlated with the priority of the early warning information.
For example, the first distance threshold is determined to be 100 meters and the second distance threshold is determined to be 20 meters based on the information of the risk area and the information of the unmanned device itself. When the distance between the unmanned equipment and the risk area is more than 100 meters, the unmanned equipment continues to drive along the current driving path; when the distance between the unmanned equipment and the risk area is 100 meters, the unmanned equipment sends early warning information to a server and sends out visual signal early warning; when the distance between the unmanned equipment and the risk area is 20-100 meters, if the server does not respond to the early warning information sent by the unmanned equipment, the unmanned equipment starts to decelerate and stop at the side at the position 20 meters away from the risk area, and the early warning is upgraded from the visual signal early warning to the acousto-optic signal early warning until the server sends information or instructions.
Optionally, determining a driving strategy of the unmanned equipment for dealing with the risk area according to the state information of the unmanned equipment, the risk level of the risk area and the distance between the unmanned equipment and the risk area; and controlling the unmanned equipment according to the driving strategy. The driving strategy for dealing with the risk area comprises the steps of bypassing the risk area, passing through the risk area, stopping driving, sending early warning information and the like.
In practical application, acquiring the self state information of the current unmanned equipment; the state information of the unmanned device can include information such as the remaining power, the driving mileage, and the load degree of the unmanned device.
For example, when the current remaining capacity of the unmanned aerial vehicle cannot support the unmanned aerial vehicle to bypass the risk area, the driving strategy of the unmanned aerial vehicle for dealing with the risk area may be to cross the risk area or stop driving and send warning information; when the unmanned equipment is fully loaded, the unmanned equipment cannot safely pass through the risk area in an unmanned mode, and the driving strategy of the unmanned equipment for dealing with the risk area can be to bypass the risk area or send early warning information and stop driving.
According to the information of the pre-labeled risk areas, determining the risk level of each type of risk area; the higher the risk level of the risk area is, the higher the probability of accidents occurring when the unmanned equipment is unmanned in the risk area is.
For example, for a risk area with a high risk level, if the unmanned device cannot safely drive through the risk area, the unmanned device can choose to bypass the risk area or stop driving to send early warning information according to the state information of the unmanned device; the unmanned equipment further comprises a path planning device; the path planning device is configured to re-plan a driving path according to the pre-marked information of the risk area, the distance between the unmanned equipment and the risk area and the state information of the unmanned equipment; the unmanned equipment bypasses the risk area according to the re-planned path; for the risk area with low risk level, the unmanned device can select to keep the driving state and pass through the risk area according to the state information of the unmanned device.
The method determines the distance between the unmanned equipment and the risk area according to the information of the risk area marked in advance and the position information of the unmanned equipment, and controls the unmanned equipment according to the distance. The method controls the unmanned equipment to send out early warning information or stop driving before entering the risk area, ensures that the unmanned equipment does not carry out unmanned automatic driving in the risk area, avoids safety risks caused by emergency events which are not processed by a security officer at the first time, and improves the safety of the unmanned equipment automatic driving.
The above steps describe an unmanned equipment control method as shown in fig. 1, and the present specification embodiment also provides a corresponding unmanned equipment control method applied to a server, as shown in fig. 2. Fig. 2 is a schematic flow chart of another unmanned aerial vehicle control method provided in an embodiment of this specification, which specifically includes the following steps:
s200: acquiring information of a pre-marked risk area; and marking the risk area according to the position information of each type of event reported by each unmanned device history.
In practical application, a server receives each event reported by each unmanned device in advance; aiming at each event type, selecting the type of event from the received events; the events may include positioning errors, transmission delays, target detection, take-over, etc. of the unmanned device during autonomous driving.
For each type of event, determining the position of the unmanned equipment when the type of event occurs as the type of risk position; and determining an area containing at least one risk position of the type according to the type of risk position determined aiming at each type of event, and marking the area as a risk area.
S202: and sending the information of the risk area to unmanned equipment so that the unmanned equipment controls the unmanned equipment according to the real-time position information of the unmanned equipment and the information of the risk area.
In this embodiment of the present specification, the risk area pre-labeled as shown in step S200 in fig. 2 may be a positioning risk area, and is specifically labeled in the following manner.
Specifically, it is necessary to receive events reported by the respective unmanned devices in advance, and select a positioning error event from the received events. And each event reported by each unmanned device comprises the type information of the event and the position information of the event.
The positioning error comprises position information output by each positioning module of the unmanned equipment, the position information is compared with position information output by other positioning modules, and the unmanned equipment is determined to have the positioning error if the obtained distance difference is larger than a preset threshold distance. The specific setting of the threshold distance can be set correspondingly according to actual conditions. For the positioning method, reference is made to the positioning method for acquiring the real-time position information of the unmanned device itself in the foregoing step S102, and details are not described here.
And determining the position of the unmanned equipment when the positioning error event occurs as a positioning risk position for each positioning error event.
And determining an area containing at least one positioning risk position according to the positioning risk position determined aiming at each positioning error event, and marking the area as a risk area.
In practical applications, the risk regions may be determined according to the number of the pre-divided regions containing the positioning risk positions or the aggregation degree of the positioning risk positions.
When the positioning risk regions are determined according to the number of the positioning risk positions contained in the pre-divided regions, the number of the positioning risk positions contained in each pre-divided region can be counted, and the regions with the number larger than the number threshold value are marked as risk regions.
When the positioning risk regions are determined according to the aggregation degree of the positioning risk positions, clustering can be performed on the positioning risk positions according to the distance between the positioning risk positions to obtain a plurality of positioning risk position clusters, and for each positioning risk position cluster, a minimum region which is in a specified shape and contains all the positioning risk positions in the positioning risk position cluster is determined to serve as a risk region. In clustering the localized risk locations, a clustering algorithm such as k-means may be employed, which is not limited by the present description.
In this embodiment of the present specification, the risk area pre-labeled as shown in step S200 in fig. 2 may be a delay risk area, and is specifically labeled in the following manner.
Specifically, it is necessary to receive events reported by the respective unmanned devices in advance, and select a transmission delay event from the received events.
The transmission delay includes a time due to network transmission from a time when the server sends the instruction or information to a time when the drone receives the instruction or information.
And determining the position of the unmanned equipment when the transmission delay event occurs as a delay risk position for each transmission delay event.
And determining a region containing at least one delay risk position according to the delay risk position determined aiming at each transmission delay event, and marking the region as a risk region. The method for determining the risk area is similar to the method for determining the positioning risk area, and is not described herein again.
In this embodiment of the present specification, the risk area pre-labeled as shown in step S200 in fig. 2 may be a missed detection risk area, and is specifically labeled in the following manner.
Specifically, it is necessary to receive events reported by each piece of unmanned equipment in advance, and select a target object detection event from the received events.
And aiming at each target object detection event, judging whether the target object detection event is a missed detection event or not according to target object information detected by unmanned equipment contained in the target object detection event, the position of the target object detection event and preset target object information corresponding to the position of the target object detection event.
Specifically, for a target object detection event reported by each piece of unmanned equipment, target object information automatically detected by the unmanned equipment in the target object detection event is compared with preset target object information corresponding to the position where the target object detection event occurs, and a target object detection event in which the unmanned equipment does not automatically detect at least one target object is determined as a detection missing event.
In practical application, the target object detection event includes that the unmanned equipment automatically detects the target object at the position of each position where the unmanned equipment is located in the automatic driving process. The object may comprise a priori road information stored in a high precision map, i.e. the road information may be collected in advance and not changed in a short time. Specifically, the target object may include data of a gradient, a curvature, a heading, a roll of each lane, and road information such as a kind and a color of a lane line; traffic regulation information such as speed limit requirements and recommended speeds of each lane; traffic lights, pedestrian crossings and other traffic participants.
Determining the position of the unmanned equipment when the missed detection event occurs as a missed detection risk position for each missed detection event;
and determining an area containing at least one undetected risk position according to the undetected risk position determined aiming at each undetected event, and marking the area as a risk area. The method for determining the risk area is similar to the method for determining the positioning risk area, and is not described herein again
In this embodiment of the present specification, the risk area pre-labeled as shown in step S200 in fig. 2 may be a takeover risk area, and is specifically labeled in the following manner.
Specifically, it is necessary to determine in advance a takeover event for the drone, and determine, for each takeover event, a location where the drone is located when the takeover event occurs, as a takeover risk location.
The take over includes switching between unmanned equipment controlled by an autopilot system and controlled by a security officer. Since the unmanned equipment encounters some situations which are not suitable for unsupervised automatic driving during automatic driving, switching to safer control is required. The takeover may be an autopilot-initiated passive takeover
For passive takeover initiated by an automatic driving system, because the current unmanned technology cannot ensure that unmanned equipment can safely drive under any weather condition and in any road environment, an Operation Design Domain (ODD) of the automatic driving system needs to be set in advance according to the technical capability of the automatic driving system. The ODD of the autopilot system includes preconditions and application ranges for the operation of the autopilot system. The autopilot system can only guarantee normal operation when all conditions are met. I.e. lacking any preconditions, the system needs to initiate a take-over request.
For example, the unmanned device-equipped autopilot system is designed so that the number of pedestrians in a range detectable by the sensor of the unmanned device when passing through the intersection is not more than 10. If the number of pedestrians in the range which can be detected by the sensor of the unmanned device is 11 when the unmanned device passes through a certain intersection, and the current situation is beyond the ODD of the automatic driving system, the unmanned device sends a take-over request to a security officer.
And determining the position of the unmanned equipment when the takeover event occurs as a takeover risk position for each takeover event.
And determining an area containing at least one takeover risk position according to the takeover risk position determined for each takeover event, and marking the area as a risk area. The method for determining the risk area is similar to the method for determining the positioning risk area, and is not described herein again.
The method may determine four types of risk regions, and after the four types of risk regions are determined, may further combine all the determined risk regions, and specifically, for each risk region, determine, according to a position and a range of the risk region, at least one other risk region at least partially overlapping with the range of the risk region, and set a region where a union of the range of the risk region and the ranges of the other risk regions is located as a risk region, that is, the finally determined risk region may only include one type of risk position, or may include multiple types of risk positions.
Based on the same idea, the present specification further provides a corresponding unmanned aerial vehicle control apparatus, as shown in fig. 3 and 4.
Fig. 3 is a schematic structural diagram of an unmanned equipment control device provided in this specification, which specifically includes:
a first obtaining module 300, configured to obtain information of a pre-labeled risk area sent by a server; the risk area is marked according to the position information of each type of event reported by each unmanned device history;
a second obtaining module 302, configured to obtain real-time location information of the unmanned device itself;
a distance determining module 304, configured to determine, based on the information of the risk area and the real-time location information of the unmanned aerial vehicle, a distance between the current unmanned aerial vehicle and the risk area;
a control module 306, configured to control the unmanned device according to the distance.
Optionally, the control module 306 is specifically configured to, if the distance is greater than a set distance threshold, keep the current driving state of the unmanned aerial vehicle; and if the distance is not greater than the set distance threshold, the unmanned equipment sends early warning information to the server and/or stops driving.
Optionally, the apparatus further comprises:
a distance threshold determining module 308, configured to specifically obtain, according to the real-time location information of the unmanned device itself, environment information of a current location of the unmanned device; according to the information of the pre-labeled risk areas, determining the risk level of each type of risk area; and determining the distance threshold according to the environmental information of the current position of the unmanned equipment and the risk level of the risk area.
Optionally, the control module 306 is specifically configured to obtain state information of the current unmanned device; according to the information of the pre-labeled risk areas, determining the risk level of each type of risk area; determining a driving strategy of the unmanned equipment for dealing with the risk area according to the state information of the unmanned equipment, the risk level of the risk area and the distance between the unmanned equipment and the risk area; and controlling the unmanned equipment according to the driving strategy.
Fig. 4 is a schematic structural diagram of another unmanned equipment control device provided in this specification, which specifically includes:
a third obtaining module 400, configured to obtain information of a pre-labeled risk area; the risk area is marked according to the position information of each type of event reported by each unmanned device history;
a sending module 402, configured to send the information of the risk area to an unmanned device, so that the unmanned device controls the unmanned device according to its own real-time location information and the information of the risk area.
Optionally, the apparatus further comprises:
a risk area labeling module 404, configured to specifically receive each event reported by each piece of unmanned equipment in advance; aiming at each event type, selecting the type of event from the received events; for each type of event, determining the position of the unmanned equipment when the type of event occurs as the type of risk position; and determining an area containing at least one risk position of the type according to the type of risk position determined aiming at each type of event, and marking the area as a risk area.
The present specification also provides a computer-readable storage medium storing a computer program operable to execute the above-described drone controlling method provided in fig. 1 and 2.
This specification also provides a schematic block diagram of the electronic device shown in fig. 5. As shown in fig. 5, at the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, but may also include hardware required for other services. The processor reads a corresponding computer program from the non-volatile memory into the memory and then runs the computer program to implement the drone control method provided in fig. 1 and 2. Of course, besides the software implementation, the present specification does not exclude other implementations, such as logic devices or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may be hardware or logic devices.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the various elements may be implemented in the same one or more software and/or hardware implementations of the present description.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of the present specification, and is not intended to limit the present specification. Various modifications and alterations to this description will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification should be included in the scope of the claims of the present specification.
Claims (10)
1. An unmanned equipment control method, wherein the method is applied to an unmanned equipment, and wherein the method comprises:
acquiring information of a pre-labeled risk area sent by a server; the risk area is marked according to the position information of each type of event reported by each unmanned device history;
acquiring real-time position information of the unmanned equipment;
determining the distance between the current unmanned equipment and the risk area based on the information of the risk area and the real-time position information of the unmanned equipment;
and controlling the unmanned equipment according to the distance.
2. The method of claim 1, wherein controlling the drone according to the distance specifically comprises:
if the distance is larger than the distance threshold determined by the unmanned equipment, the unmanned equipment keeps the current driving state;
and if the distance is not greater than the distance threshold determined by the unmanned equipment, the unmanned equipment sends early warning information to the server and/or stops driving.
3. The method of claim 2, wherein the determining of the distance threshold by the drone specifically comprises:
acquiring environmental information of the current position of the unmanned equipment according to the real-time position information of the unmanned equipment;
according to the information of the pre-labeled risk areas, determining the risk level of each type of risk area;
and determining the distance threshold according to the environmental information of the current position of the unmanned equipment and the risk level of the risk area.
4. The method of claim 1, wherein controlling the drone according to the distance specifically comprises:
acquiring the self state information of the current unmanned equipment;
according to the information of the pre-labeled risk areas, determining the risk level of each type of risk area;
determining a driving strategy of the unmanned equipment for dealing with the risk area according to the state information of the unmanned equipment, the risk level of the risk area and the distance between the unmanned equipment and the risk area;
and controlling the unmanned equipment according to the driving strategy.
5. An unmanned equipment control method is applied to a server, and the method comprises the following steps:
acquiring information of a pre-marked risk area; the risk area is marked according to the position information of each type of event reported by each unmanned device history;
and sending the information of the risk area to unmanned equipment so that the unmanned equipment controls the unmanned equipment according to the real-time position information of the unmanned equipment and the information of the risk area.
6. The method of claim 5, wherein pre-labeling risk regions specifically comprises:
receiving each event reported by each unmanned device in advance;
aiming at each event type, selecting the type of event from the received events;
for each type of event, determining the position of the unmanned equipment when the type of event occurs as the type of risk position;
and determining an area containing at least one risk position of the type according to the type of risk position determined aiming at each type of event, and marking the area as a risk area.
7. An unmanned aerial device control apparatus, characterized in that the apparatus is applied to an unmanned aerial device, the apparatus comprising:
the first acquisition module is used for acquiring information of a pre-labeled risk area sent by the server; the risk area is marked according to the position information of each type of event reported by each unmanned device history;
the second acquisition module is used for acquiring the real-time position information of the unmanned equipment;
the distance determining module is used for determining the distance between the current unmanned equipment and the risk area based on the information of the risk area and the real-time position information of the unmanned equipment;
and the control module is used for controlling the unmanned equipment according to the distance.
8. An unmanned equipment control device, wherein the device is applied to a server, the device comprises:
the third acquisition module is used for acquiring information of the pre-labeled risk area; the risk area is marked according to the position information of each type of event reported by each unmanned device history;
and the sending module is used for sending the information of the risk area to the unmanned equipment so that the unmanned equipment can control the unmanned equipment according to the real-time position information of the unmanned equipment and the information of the risk area.
9. A computer-readable storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, implements the method of any of the preceding claims 1 to 6.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any of claims 1 to 6 when executing the program.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111315342.9A CN114153203A (en) | 2021-11-08 | 2021-11-08 | Unmanned equipment control method, device, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111315342.9A CN114153203A (en) | 2021-11-08 | 2021-11-08 | Unmanned equipment control method, device, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114153203A true CN114153203A (en) | 2022-03-08 |
Family
ID=80459320
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111315342.9A Withdrawn CN114153203A (en) | 2021-11-08 | 2021-11-08 | Unmanned equipment control method, device, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114153203A (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160140851A1 (en) * | 2014-11-18 | 2016-05-19 | Ziv LEVY | Systems and methods for drone navigation |
| US20200117203A1 (en) * | 2018-12-10 | 2020-04-16 | Beijing Baidu Netcom Science Technology Co., Ltd. | Vehicle control method and apparatus, device, vehicle and storage medium |
| CN112622930A (en) * | 2020-12-22 | 2021-04-09 | 北京百度网讯科技有限公司 | Unmanned vehicle driving control method, device and equipment and automatic driving vehicle |
| CN112799411A (en) * | 2021-04-12 | 2021-05-14 | 北京三快在线科技有限公司 | Control method and device of unmanned equipment |
| WO2021179340A1 (en) * | 2020-03-12 | 2021-09-16 | 博睿泰克科技（宁波）有限公司 | Vehicle driving-based danger early-warning method and system, and storage medium |
-
2021
- 2021-11-08 CN CN202111315342.9A patent/CN114153203A/en not_active Withdrawn
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160140851A1 (en) * | 2014-11-18 | 2016-05-19 | Ziv LEVY | Systems and methods for drone navigation |
| US20200117203A1 (en) * | 2018-12-10 | 2020-04-16 | Beijing Baidu Netcom Science Technology Co., Ltd. | Vehicle control method and apparatus, device, vehicle and storage medium |
| WO2021179340A1 (en) * | 2020-03-12 | 2021-09-16 | 博睿泰克科技（宁波）有限公司 | Vehicle driving-based danger early-warning method and system, and storage medium |
| CN112622930A (en) * | 2020-12-22 | 2021-04-09 | 北京百度网讯科技有限公司 | Unmanned vehicle driving control method, device and equipment and automatic driving vehicle |
| CN112799411A (en) * | 2021-04-12 | 2021-05-14 | 北京三快在线科技有限公司 | Control method and device of unmanned equipment |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10730521B2 (en) | System for autonomous lane merging | |
| EP3809226B1 (en) | Method and system for development and verification of autonomous driving features | |
| JP6419666B2 (en) | Automatic driving device | |
| US11622228B2 (en) | Information processing apparatus, vehicle, computer-readable storage medium, and information processing method | |
| CN111959499B (en) | Vehicle control method and device | |
| CN113064451B (en) | Unmanned equipment control method and device, storage medium and electronic equipment | |
| CN111984018A (en) | Automatic driving method and device | |
| JP2020095594A (en) | Vehicle control device and vehicle control method | |
| CN112327864A (en) | Control method and control device of unmanned equipment | |
| CN113037576A (en) | Fault detection method and device, storage medium and electronic equipment | |
| CN113968243A (en) | Obstacle trajectory prediction method, device, equipment and storage medium | |
| CN116564133A (en) | Vehicle early warning method and device for tidal lane and electronic equipment | |
| CN114153203A (en) | Unmanned equipment control method, device, equipment and storage medium | |
| US20220388506A1 (en) | Control apparatus, movable object, control method, and computer-readable storage medium | |
| CN113031656B (en) | Unmanned aerial vehicle control method and device | |
| CN112764431B (en) | Unmanned aerial vehicle control method and device, computer readable storage medium and unmanned aerial vehicle | |
| CN114590249A (en) | Unmanned equipment control method, device, equipment and storage medium | |
| CN114852103A (en) | Method and device for determining vehicle driving strategy and vehicle | |
| CN114118904A (en) | Unmanned vehicle distribution method and device | |
| CN111681435B (en) | Traffic control method and device based on edge calculation, electronic equipment and storage medium | |
| CN114153190A (en) | Unmanned equipment control method and device, storage medium and electronic equipment | |
| CN112799412A (en) | Control method and control device of unmanned equipment | |
| CN113641170B (en) | Method and device for intelligently detecting unmanned driving takeover problem | |
| CN114530044B (en) | Vehicle running scheduling processing method and device | |
| CN114019959B (en) | Method and device for determining longitudinal decision of unmanned equipment |
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 | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20220308 |