CN110568852A - Automatic driving system and control method thereof - Google Patents
Automatic driving system and control method thereof Download PDFInfo
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- 230000004927 fusion Effects 0.000 claims abstract description 58
- 230000016776 visual perception Effects 0.000 claims abstract description 17
- 230000007246 mechanism Effects 0.000 claims abstract description 13
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- 230000008447 perception Effects 0.000 claims description 13
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Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0278—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
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- G—PHYSICS
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0285—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using signals transmitted via a public communication network, e.g. GSM network
Abstract
The invention relates to an automatic driving system and a control method thereof, which comprises a sensor, a vehicle-mounted computing unit and a line control execution mechanism, wherein the vehicle-mounted computing unit comprises a visual perception processor, a fusion decision unit and a safety control unit; the visual perception processor directly processes the data collected by the sensor and reasonably distributes the data to the fusion decision unit and the safety control unit; the fusion decision unit combines the vehicle body state data and the line control part data to make decision planning and transmits decision planning information to the safety controller; the safety controller sends a motion control instruction to the drive-by-wire executing mechanism according to the decision planning information, and the invention skillfully distributes the calculation processing tasks of the sensors with different data characteristics to different component modules of the calculation platform. On the basis of ensuring the safety, redundancy and high efficiency of the system, the manufacturing cost of the automatic driving automobile is greatly reduced, and the direction is indicated for the mass production of the automatic driving automobile.
Description
Technical Field
The invention relates to the field of automatic driving, in particular to an automatic driving system and a control method thereof.
background
At present, many automatic driving vehicle-making enterprises do not have the capability of reasonably optimizing, fusing and using sensors with different characteristics, the adopted vehicle-mounted sensors are not only various, but also a plurality of sensors with certain types are adopted, and in order to ensure that a computing platform has high-efficiency and strong data computing and processing performance matched with the computing platform, the computing platform usually adopts a single chip processor with high manufacturing cost to take charge of fusion decision of all data and motion control of automatic driving vehicles, such as a Huacheng MDC600 automatic driving system, a Driver PX2 automatic driving system of Yingwei Dada and a hundred-degree apollo automatic driving system. Therefore, from the viewpoint of system design, reducing the cost of the whole automatic driving automobile on the basis of ensuring the redundancy, the high efficiency and the safety of the automatic driving system becomes an urgent problem to be solved by the whole industry.
an existing invention patent CN201810015286 discloses an automatic driving system, so as to improve the stability and reliability of the automatic driving system and ensure safe automatic driving of a vehicle. This automatic system of driving includes: the sensor is used for acquiring environmental information around the vehicle; the data exchange controller is used for preprocessing and calculating the original data acquired by the sensor to obtain environment information; the main decision unit is used for obtaining decision information through fusion calculation according to the environmental information obtained by the data exchange controller and sending the decision information to the controller; the alternative decision unit is used for obtaining decision information through fusion calculation according to the environmental information obtained by the data exchange controller when the main decision unit is monitored to be abnormal, and sending the decision information to the controller; and the controller is used for calculating to obtain vehicle control information according to the received decision information and sending the vehicle control information to the vehicle bottom layer controller to control the motion of the automatic driving automobile. The invention provides a decision unit and a control unit which distribute all data calculation processing tasks related to the automatic driving function of a vehicle to an on-board calculation unit. In order to improve the redundancy and the safety of the system, an alternative decision unit is added under the main decision unit; adding under the master controller
A verification unit and an alternative control unit. Undoubtedly, the presence of alternative units not only does not reduce the cost of an autonomous vehicle, but rather increases the cost.
Disclosure of Invention
the invention aims to overcome the defects of the prior art and provide an automatic driving system which is economical and applicable and can enable a vehicle to realize an L4 automatic driving function under SAE grading standard; in order to achieve the above purpose, the present invention provides the following technical solutions:
An automatic driving system is characterized by comprising a sensor, an on-board computing unit and a drive-by-wire executing mechanism:
The sensor is a generalized sensor and comprises a vehicle-mounted sensor, a GPS and a detection element, wherein the GPS and the detection element are used for positioning and navigation; the system also comprises a man-machine interaction system and a communication system which can obtain data through environment perception capability;
The vehicle-mounted computing unit comprises a visual perception processor, a fusion decision unit and a safety control unit;
The visual perception processor directly processes the data acquired by the sensor and reasonably distributes the data to the fusion decision unit and the safety control unit;
The fusion decision unit combines the vehicle body state data and the line control part data to make decision planning and transmits decision planning information to the safety controller;
And the safety controller sends a motion control instruction to the line control executing mechanism according to the decision planning information and transmits the vehicle body state data to the fusion decision unit.
the vision perception processor consists of five independent units, namely a forward binocular camera, a forward monocular camera, a driver behavior detection camera, a panoramic camera and a laser radar.
The fusion decision unit receives and processes data preprocessed by the visual perception processor and information data transmitted by the sensor, and also receives and processes information data transmitted by the communication system and the human-computer interaction system.
The safety control unit directly receives millimeter wave radar data and ultrasonic radar data, the vehicle body state data is connected with the safety controller through the CAN bus, the wire control part data is connected with the safety controller through the LIN interface, and the safety controller transmits the information to the fusion decision unit.
the communication system comprises a 4G or 5G communication system and a V2X communication system.
The vehicle-mounted sensor comprises a traditional camera, a millimeter wave radar, a laser radar, an ultrasonic radar, an infrared night vision, a GPS and inertial measurement unit for positioning and navigation, a high-precision map and a V2X vehicle networking device; the data obtained by the vehicle-mounted sensors include not only vehicle surrounding information but also traffic condition information.
A control method adopting the automatic driving system is characterized in that:
A, a sensor senses information around a vehicle and receives traffic condition information, and transmits the information to a fusion decision unit,
b, the fusion decision unit calculates all external input information and sends the decision information to the safety controller;
And C, the safety controller sends a specific control command to the execution structure of vehicle motion control by combining the vehicle body state data on the basis of the decision information.
and reasonably distributing the data processing tasks of the sensors to a fusion decision unit and a safety controller for data processing according to the characteristics of the data acquired by the sensors.
The information exchange between the fusion decision unit and the safety controller is bidirectional, and the fusion decision unit CAN receive the vehicle body state data transmitted from the vehicle body CAN bus through the safety controller.
The millimeter wave radar data are simultaneously transmitted to the fusion decision unit and the safety controller, and when the fusion decision unit stops working, the safety controller can also send an instruction to the execution mechanism.
The automatic driving system of the invention skillfully distributes the calculation processing tasks of the sensors with different data characteristics to different component modules of the calculation platform by reasonably and optimally selecting the vehicle-mounted sensors and building the calculation platform matched with the vehicle-mounted sensors. The component modules of the computing platform are physically independent and cannot influence each other to work normally, an organic whole is formed through data transmission interaction, and automatic driving of the automatic driving vehicle based on the L4 level (according to the SAE (society of International AutoEngineers) classification standard) in functions such as environment perception, fusion decision, motion control and the like is completed. Through the creative design, the automatic driving system provided by the invention greatly reduces the manufacturing cost of the automatic driving automobile on the basis of ensuring the safety, redundancy and high efficiency of the system, and indicates the direction for the landing yield of the automatic driving automobile.
Drawings
The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.
FIG. 1 is a block diagram of an autopilot system architecture of the present invention;
FIG. 2 is a conventional logic execution diagram of an autonomous driving system;
Fig. 3 is a schematic diagram of an information transfer control method in a normal case of the automatic driving system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments that can be derived by one of ordinary skill in the art from the embodiments given herein are intended to be within the scope of the present invention.
The invention discloses an automatic driving system, which comprises a sensor, a vehicle-mounted computing unit and a drive-by-wire executing mechanism: the vehicle-mounted computing unit comprises a visual perception processor, a fusion decision unit and a safety control unit; the visual perception processor directly processes the data acquired by the sensor and reasonably distributes the data to the fusion decision unit and the safety control unit; the fusion decision unit combines the vehicle body state data and the line control part data to make decision planning and transmits decision planning information to the safety controller; and the safety controller sends a motion control instruction to the line control executing mechanism according to the decision planning information and transmits the vehicle body state data to the fusion decision unit.
The vision perception processor consists of five independent units, namely a forward binocular camera, a forward monocular camera, a driver behavior detection camera, a panoramic camera and a laser radar for collecting data related to environmental information. The fusion decision unit receives and processes data preprocessed by the visual perception processor and information data transmitted by the sensor, and also receives and processes information data transmitted by the communication system and the human-computer interaction system. The safety control unit directly receives millimeter wave radar data and ultrasonic radar data, the vehicle body state data is connected with the safety controller through the CAN bus, the wire control part data is connected with the safety controller through the LIN interface, and the safety controller transmits the information to the fusion decision unit. The communication system comprises a 4G or 5G communication system and a V2X communication system. The vehicle-mounted sensor comprises a traditional camera, a millimeter wave radar, a laser radar, an ultrasonic radar, an infrared night vision, a GPS and inertial measurement unit for positioning and navigation, a high-precision map and a V2X vehicle networking device; the data obtained by the on-vehicle sensors include not only vehicle surroundings information but also traffic condition information.
Fig. 1 is a structural framework diagram of an automatic driving system of the present invention, wherein a vehicle-mounted computing unit of the automatic driving system includes three modules of a visual perception processor, a fusion decision unit and a safety control unit, wherein the visual perception processor is connected with and processes the following five independent units, which are respectively used for processing a forward binocular camera, a forward monocular camera, a driver behavior detection camera, a panoramic camera and a laser radar for collecting data related to environmental information, and each independent unit is correspondingly connected with one visual perception processor. The fusion decision unit receives data preprocessed by the visual perception processor through PCIe Switch and Lan Switch, directly receives information of the high-precision positioning and inertial navigation unit, directly receives information of a high-precision map and information of a millimeter wave radar, and directly carries out information communication with the human-computer interaction system, the 4G/5G communication system and the V2X communication system. The safety control unit directly receives the millimeter wave radar data and the ultrasonic radar data. The vehicle body state data is connected with the safety control unit through a CAN bus; the data of the drive-by-wire components (not shown) are connected to the safety control unit via a LIN interface. And the safety control unit transmits the information to the fusion decision unit. The fusion decision unit makes accurate perception understanding on the surrounding environment of the vehicle according to environment data information received from the modules including the visual perception processor, the safety control unit and each external unit directly contacted with the fusion decision unit. Furthermore, the fusion decision unit fuses the vehicle body state data and the line control part data according to the cognitive understanding of the fusion decision unit on the environment to make decision planning on the next behavior of the vehicle. And the fusion decision unit transmits the decision planning information to the safety control unit. The safety control unit carries out calculation processing according to the decision planning information transmitted from the fusion decision unit to obtain control information and sends a control instruction to the linear control executing mechanism to carry out actions which all human drivers should do in the same or similar environment, such as driving, braking, accelerating, decelerating, steering and the like.
The sensor is a generalized sensor, and comprises a vehicle-mounted sensor in the traditional sense, such as a camera, a millimeter wave radar, a laser radar, an ultrasonic radar, an infrared night vision sensor, a bioelectricity sensor and the like, active detection elements such as a Global Positioning System (GPS) and an Inertial Measurement Unit (IMU) for positioning and navigation, and a cooperative global auxiliary data device which can expand the environment perception capability of the automatically-driven vehicle, such as a high-precision map information device, a V2X vehicle networking technology device and the like. The system also comprises a man-machine interaction system and a communication system which can obtain data through environment perception capability. The obtained data includes not only the vehicle surroundings information but also traffic condition information. The vehicle-mounted sensors are not required to be of the same type and number, but are based on the advantages and disadvantages of the sensors
The points are reasonably matched. Referring to fig. 2, a conventional logic implementation diagram of an autonomous driving system, in which case the computational logic in operation can be divided as follows:
the sensors for detecting the peripheral objects perform behavior prediction through calculation, the layer forms a perception layer G, the perception layer G detects and calculates the objects and the attributes of the peripheral environment through various sensor data, and the object information is transmitted to a decision layer directly or after being processed by a preprocessing unit. In some cases, the sensing layer G may perform behavior prediction on the detected object, and specifically convert the prediction result into a time-space dimensional trajectory, and transmit the time-space dimensional trajectory to the decision layer J, which makes a behavior decision and plans an action for the next step. Generally, the object information outputted by the sensing layer G includes physical attributes such as position, speed, orientation, and object classification (e.g. road block, vehicle, pedestrian, bicycle). The object attributes computed and output by these perception layers G are biased towards objective physical attributes. By using these output attributes, in combination with objective physics laws, an instantaneous prediction of the object trajectory can be made in a very short time. And the decision layer J combines the body state and the input path of the automatic driving vehicle on the basis of fusing the environment perception information to make the most reasonable behavior decision and action plan for the vehicle. Behavioral decisions macroscopically determine how autonomous vehicles will make their decisions, including normal following on roads, waiting for avoidance when encountering traffic lights and pedestrians, and interactive passing of other vehicles at intersections, etc. Action planning the problem addressed here, relative behavioral decision, is still more specific in one step. The action planning needs to plan the intermediate path points from A to B in a short temporary time t specifically on the premise of making behavior decisions at a decision layer, and comprises selecting specific path points to pass through, and automatically driving the speed, the orientation, the acceleration and the like of the vehicle when reaching each path point. And the decision layer J sends the action command of the automatic driving vehicle at the next moment made by the action plan to the execution layer Z. The execution layer Z converts the action command into specific signals of a vehicle body system, an accelerator system, a brake system, a steering system and the like of the automatic driving drive-by-wire system through a series of dynamic calculations combined with vehicle body attributes and external physical factors.
Fig. 3 is a schematic diagram of an information transmission control method of the automatic driving system in a normal condition, and the control operation method of the automatic driving system is as follows: firstly, the information around the vehicle is sensed through a sensor, the traffic condition information is received, the information is transmitted to a fusion decision unit, the information related to vision is preprocessed through a vision processor, and the information is transmitted to the fusion decision unit through different interfaces and channels. Then the fusion decision unit outputs all the external signals
The input information is calculated and processed, and the decision information is sent to a safety controller, wherein the safety controller comprises vehicle body state data transmitted by a safety control unit through a CAN bus. And finally, the safety controller sends a specific control instruction to a drive-by-wire execution mechanism for controlling the vehicle motion by combining the vehicle body state data on the basis of the decision information.
and reasonably distributing the data processing tasks of the sensors to the fusion decision unit and the safety controller for data processing according to the characteristics of the data acquired by the sensors. And the fusion decision processor makes decision planning by combining the vehicle body state data and the line control part data on the basis of accurately recognizing the environment, and transmits decision planning information to the safety controller. And the safety controller sends a motion control instruction to the line control unit according to the decision planning information. The information exchange between the fusion decision unit and the safety control unit is bidirectional, and the fusion decision unit CAN receive the vehicle body state data transmitted from the vehicle body CAN bus through the safety control unit. The millimeter wave radar data are simultaneously transmitted to the fusion decision unit and the safety control unit, and when the fusion decision unit stops working, the safety control unit can also send an instruction to the execution mechanism. The drive-by-wire actuator controls the operation of the autonomous vehicle in a PID control mode.
The automatic driving system of the invention skillfully distributes the calculation processing tasks of the sensors with different data characteristics to different component modules of the calculation platform by reasonably and optimally selecting the vehicle-mounted sensors and building the calculation platform matched with the vehicle-mounted sensors. The component modules of the computing platform are physically independent and cannot influence each other to work normally, an organic whole is formed through data transmission interaction, and automatic driving of the automatic driving vehicle based on the L4 level (according to the SAE (society of International AutoEngineers) classification standard) in functions such as environment perception, fusion decision, motion control and the like is completed. Through the creative design, the automatic driving system provided by the invention greatly reduces the manufacturing cost of the automatic driving automobile on the basis of ensuring the safety, redundancy and high efficiency of the system, and indicates the direction for the landing yield of the automatic driving automobile.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that are within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. an automatic driving system is characterized by comprising a sensor, an on-board computing unit and a drive-by-wire executing mechanism:
The sensor is a generalized sensor and comprises a vehicle-mounted sensor, a GPS and a detection element for positioning and navigation; the system also comprises a man-machine interaction system and a communication system which can obtain data through environment perception capability;
The vehicle-mounted computing unit comprises a visual perception processor, a fusion decision unit and a safety control unit;
The visual perception processor directly processes the data acquired by the sensor and reasonably distributes the data to the fusion decision unit and the safety control unit;
the fusion decision unit combines the vehicle body state data and the line control part data to make decision planning and transmits decision planning information to the safety controller;
and the safety controller sends a motion control instruction to the line control executing mechanism according to the decision planning information and transmits the vehicle body state data to the fusion decision unit.
2. The autopilot system of claim 1 wherein the visual perception processor is comprised of five separate units, respectively a forward binocular camera, a forward monocular camera, and a driver behavior detection camera, a look-around camera, a lidar.
3. The autopilot system of claim 1 wherein the fusion decision unit receives and processes data including data pre-processed by the visual perception processor and information data transmitted from the sensors, and further includes information data transmitted from the communication system and the human-computer interaction system.
4. an autopilot system according to claim 1, characterized in that the safety control unit receives the millimeter wave radar data and the ultrasonic radar data directly, the body state data are connected to the safety controller via a CAN bus, the drive-by-wire component data are connected to the safety controller via a LIN interface, and the safety controller transmits the above information to the fusion decision unit.
5. An autopilot system according to claim 1 wherein the communication system includes a 4G or 5G communication system and a V2X communication system.
6. The autopilot system of claim 1 wherein the onboard sensors include conventional cameras, millimeter wave radar, lidar, ultrasonic radar, infrared night vision, and GPS and inertial measurement units for positioning and navigation, and further including high precision maps, V2X car networking equipment; the data obtained by the on-vehicle sensors include not only vehicle surroundings information but also traffic condition information.
7. a control method of the automatic driving system is characterized in that:
a, the sensor senses the information around the vehicle and receives the traffic condition information, and transmits the information to the fusion decision unit,
b, the fusion decision unit calculates all external input information and sends the decision information to the safety controller;
And C, the safety controller sends a specific control command to the execution structure of vehicle motion control by combining the vehicle body state data on the basis of the decision information.
8. the control method of the automatic driving system according to claim 7, wherein: and reasonably distributing the data processing tasks of the sensors to a fusion decision unit and a safety controller for data processing according to the characteristics of the data acquired by the sensors.
9. The control method of the automatic driving system according to claim 7, wherein: the information exchange between the fusion decision unit and the safety controller is bidirectional, and the fusion decision unit CAN receive the vehicle body state data transmitted from the vehicle body CAN bus through the safety controller.
10. The control method of the automatic driving system according to claim 7, wherein: the millimeter wave radar data are simultaneously transmitted to the fusion decision unit and the safety controller, and when the fusion decision unit stops working, the safety controller can also send an instruction to the execution mechanism.
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| CN111240335A (en) * | 2020-01-20 | 2020-06-05 | 中汽数据(天津)有限公司 | Automatic driving system of intelligent integrated vehicle |
| CN111432017A (en) * | 2020-03-31 | 2020-07-17 | 河南工业大学 | Special platform truck of intelligence grain commodity circulation based on car networking and intelligent driving technique |
| CN111984015A (en) * | 2020-08-26 | 2020-11-24 | 扬州大学 | Hybrid-enhanced-intelligence-based automatic driving vehicle implementation method |
| CN112249033A (en) * | 2020-10-30 | 2021-01-22 | 广州小鹏自动驾驶科技有限公司 | Automatic driving system and method for vehicle |
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| CN112277842A (en) * | 2020-09-15 | 2021-01-29 | 惠州市德赛西威智能交通技术研究院有限公司 | Data acquisition system based on automatic driving platform |
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| CN113814989A (en) * | 2020-06-19 | 2021-12-21 | 周世海 | Deformable combined robot and control system thereof |
| CN113815533A (en) * | 2020-06-19 | 2021-12-21 | 上海网车科技有限公司 | Forward ADAS and automatic parking fusion controller |
| CN113895450A (en) * | 2021-10-27 | 2022-01-07 | 东风汽车集团股份有限公司 | Safety redundancy system and control method for unmanned vehicle sensing system |
| CN113954879A (en) * | 2021-04-15 | 2022-01-21 | 上海丰豹商务咨询有限公司 | Vehicle-mounted intelligent unit with fusion perception and collaborative decision function and control method |
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