CN113442856B - Control method and device based on adaptive platform and ROS2 and storage medium - Google Patents
Control method and device based on adaptive platform and ROS2 and storage medium Download PDFInfo
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Abstract
The application discloses a control method, a device and a storage medium based on an adaptive platform and a ROS2, wherein the method comprises the following steps: collecting data; the self-adaptive platform processes the acquired data to obtain a processing result; and the self-adaptive platform sends the processing result to a computing platform for intelligent driving. The software development speed can be improved, and the safety of intelligent driving is guaranteed.
Description
Technical Field
The application belongs to the technical field of intelligent driving, and particularly relates to a control method and device based on a self-adaptive platform and a ROS2, and a storage medium.
Background
In order to support complex application programs and meet the high-performance requirement of processing a large amount of data, the self-adaptive platform follows a service-oriented architecture; since the service-oriented architecture is composed of a set of services that can be invoked by each other and applications for these services, distributed computing and information communication are very important. ROS2 is just one distributed multi-process software framework based on message-passing communication. The main components of the ROS include ROS Node, ROS Service, etc. Different functions can be realized by different nodes, messages can be transmitted among the nodes through publishing and subscribing topics, and the essence of the nodes is a Socket communication mechanism based on TCP/IP.
The loose coupling of the self-adaptive platform internal service, the extremely high requirement on parallel processing and the characteristic of dynamically managing resources and communication are all natural to the ROS2 communication framework, and the ROS2 has the following problems:
firstly, the ROS2 does not have the mechanisms of dynamic discovery, survival detection, access control and the like, and needs to be combined with a platform with high safety;
secondly, when one node communicates with a plurality of nodes, messages can be copied for a plurality of times, which is a great waste to system resources, so that the nodes need to be combined with a platform with a shared memory mode.
Disclosure of Invention
The embodiment of the application provides a control method, a control device and a storage medium based on a self-adaptive platform and a ROS2, which can improve the software development rate and ensure the safety of intelligent driving.
In order to solve the above technical problem, an embodiment of the present application provides the following technical solutions:
in a first aspect, an embodiment of the present application provides a control method based on an adaptive platform and an ROS2, including:
the data is collected through the camera, and the camera can collect data information of the external environment of the target vehicle, including road information, information of other target vehicles and the like; the system comprises a target vehicle, a camera, a data processing unit and a data processing unit, wherein one target vehicle can correspond to one or more cameras, and can be specifically selected according to needs, and the cameras are connected with a hardware interface of the target vehicle and perform data interaction with an AP (access point) of the target vehicle in real time; the camera is used for monitoring the running condition of an external target vehicle in a certain road section or monitoring the running data of all target vehicles in one area; the first AP node acquires data acquired by a first camera based on GMSL and processes the data based on a lane line perception AI algorithm, wherein the data comprises an original picture, lane line information based on the original picture and lane line data before fitting; the first AP node or the second AP node processes the received data, acquires a processing result and sends the processing result to the MDC based on the ETH; the external data of the target vehicle is collected based on the camera, so that the method is efficient, convenient and low in cost; the data collected by camera shooting are processed based on the AP, the safety is high, the method can be used for electronic controller units with relatively low resources, and the application range is wide.
In a possible implementation manner, because the data collected by the first camera or the second camera are various, a large amount of unnecessary data information may be collected, a screening module may be arranged on the first camera or the second camera, data related to lane line information in the data collected by the first camera or the second camera is screened out based on the screening module, then the effective data obtained by screening is transmitted to the AP by the first camera or the second camera, so that the data processing pressure of the AP is reduced, the accuracy of a control instruction is improved, the data obtained by the camera is screened, the calculation pressure of a calculation platform for intelligent driving can be reduced, the running speed of the calculation platform for intelligent driving is improved, and the user experience is improved.
In a possible implementation manner, the first AP node performs YUV data configuration based on received data, and issues the acquired character device data to the Mini; and the second AP node acquires the data acquired by the second camera based on the CAN and issues the acquired data to the AP.
In one possible implementation manner, the obtaining a first control instruction of a target vehicle includes: acquiring chassis information of the target vehicle sent by the vehicle control unit; and processing the chassis information to obtain the first control instruction, and generating the first control instruction based on the chassis information provided by the vehicle controller, so that the effective information of the target vehicle is fully utilized, and the effectiveness and the safety of data are ensured.
In a second aspect, an embodiment of the present application provides a control method based on an adaptive platform and an ROS2, including:
the ROS2 framework is provided with a plurality of nodes, each node has a specific function, and the MDC receives data sent by the AP node based on the ROS2 and processes the received data based on the algorithm of the ROS2 node; the method comprises the steps that a first ROS2 node receives lane line information sent by a first AP node; the second ROS2 node receives lane line data sent by the second AP node; and the third ROS2 node receives the first control instruction sent by the third AP node. Each ROS2 node has a specific algorithm for processing data, and after the ROS2 node processes the data based on the algorithm, the processing result is converted into topic, so that other ROS2 nodes receive and release the data based on subscription; for example, the first ROS2 node forwards the received lane line information: the second ROS2 node processes the received lane line data to acquire subject information; the third ROS2 node generates a second control order based on the first control order. Each ROS2 node processes the data received by the node based on the algorithm, converts the processing result into topic, and sends the information corresponding to the topic to the subscribed ROS2 node if other ROS2 nodes subscribe to the topic, so that the information corresponding to the topic is published. The fourth ROS2 node subscribes topic information, lane line data sent by the second ROS2 node are obtained, and a lane line fitting result is obtained based on the lane line data; the fifth ROS2 node subscribes topic information, lane line data sent by the second ROS2 node are obtained, and a decision optimization result is obtained based on the lane line data; and the sixth ROS2 node subscribes the topic information, acquires lane line data sent by the second ROS2 node, and acquires the optimization result of the control algorithm based on the lane line data.
For example, after receiving the control instruction, the MCU performs data processing according to the control instruction, including but not limited to generating a lane line fitting, decision planning or control algorithm optimization instruction, the MCU sends the lane line fitting instruction to the fourth ROS2 node, the fourth ROS2 node subscribes to subject information, obtains lane line data sent by the second ROS2 node, and obtains a lane line fitting result based on the lane line data. Based on the subscription data, the fourth ROS2 node sends the lane line fitting result to the MCU; the fifth ROS2 node sends the decision optimization result to the MCU; the sixth ROS2 node sends the optimization result of the control algorithm to the MCU; the MCU generates a driving route of the target vehicle based on the lane line fitting result, the decision optimization result and the control algorithm optimization result, and sends the driving route to a seventh ROS2 node.
The ROS2 framework and the AP framework are fused, and an information interaction mode and a memory management mode which are mutually complementary effectively accelerate the development of software, so that the method is suitable for intelligent driving vehicles at the early stage and the low stage of software development.
In a third aspect, an embodiment of the present application provides a control apparatus based on an adaptive platform and an ROS2, including:
the acquisition unit is used for acquiring data; the data includes the external environment and other target vehicles, such as: the distance to another target vehicle, the speed difference to another target vehicle, the number of other target vehicles, etc., and the condition of the road within a certain distance from the target vehicle.
The first processing unit is used for processing the acquired data by the self-adaptive platform to obtain a processing result; and the AP acquires an original photo in the acquired data based on an internal algorithm, such as a lane line perception (AI) algorithm, according to the received acquired data, identifies lane line information according to the original photo, and issues the lane line information.
The transmission unit is used for the self-adaptive platform to transmit the processing result to the intelligent driving computing platform; the sending unit may include a plurality of AP nodes, and the AP nodes are configured to receive data sent by the camera, process the received data, and then send the data to the intelligent driving computing platform.
In a fourth aspect, an embodiment of the present application provides a control apparatus based on an adaptive platform and an ROS2, including:
the receiving unit is used for receiving lane line information sent by the self-adaptive platform based on the ROS2 node; for example, the first ROS2 node receives lane line information sent by the first AP node and forwards the lane line information to the Host subsystem for processing; the second ROS2 node receives the lane line data sent by the second AP node and publishes the lane line data as other ROS2 nodes, such as topic, so that the other ROS2 nodes receive the topic based on the subscription.
The second processing unit is used for processing the lane line information by the ROS2 node to obtain a processing result; the ROS2 node processes the received data based on an internal algorithm and converts the data into corresponding topics, so that other ROS2 nodes receive the topics based on subscriptions and publish the topics.
The publishing unit is used for publishing the processing result according to the subscription data to obtain a publishing result; for example, the fourth ROS2 node obtains lane line fitting results and publishes based on subscriptions; the fifth ROS2 node obtains a decision planning result and issues the decision planning result based on subscription; and the sixth ROS2 node acquires the optimization result of the control algorithm, and publishes the control algorithm based on subscription and the like.
The generating unit is used for generating a running route of the target vehicle according to the release result; the generating unit is connected with the vehicle control unit and performs information interaction with the vehicle control unit based on the third AP node.
In a fifth aspect, an embodiment of the present application provides an intelligent vehicle, including a processor, a memory and a communication interface, wherein the memory is used for storing information transmission program codes, and the processor is used for calling the vehicle running control program codes to execute the method of the first aspect.
In a sixth aspect, an embodiment of the present application provides a service device, where the service device includes a processor, and the processor is configured to support the service device to implement corresponding functions in the adaptive platform and ROS 2-based control method provided in the second aspect. The service device may also include a memory, coupled to the processor, that stores program instructions and data necessary for the service device. The service device may also include a communication interface for the service device to communicate with other devices or a communication network.
In a seventh aspect, the present application provides a chip system, which includes a processor for enabling a service device to implement the functions referred to in the above first aspect, for example, generating or processing information referred to in the above first aspect control method based on an adaptive platform and an ROS 2. In one possible design, the system-on-chip further includes a memory for storing program instructions and data necessary for the data transmission device. The chip system may be constituted by a chip, or may include a chip and other discrete devices.
In an eighth aspect, the present application provides a chip system, which includes a processor for enabling a service device to implement the functions referred to in the second aspect, for example, generating or processing information referred to in the adaptive platform and ROS 2-based control method of the second aspect. In one possible design, the system-on-chip further includes a memory for storing program instructions and data necessary for the data transmission device. The chip system may be constituted by a chip, or may include a chip and other discrete devices.
In a ninth aspect, the present application provides a computer readable storage medium for storing computer software instructions for an adaptive platform and ROS 2-based control apparatus provided in the above first aspect, which contains a program designed to execute the above first aspect.
In a tenth aspect, an embodiment of the present application provides a computer-readable storage medium for storing computer software instructions for use in a service device provided in the second aspect, which includes a program designed to execute the second aspect.
In an eleventh aspect, the present application provides a computer program, where the computer program includes instructions, and when the computer program is executed by a computer, the computer can execute the procedures executed by the adaptive platform and ROS 2-based control apparatus in the first aspect.
In a twelfth aspect, the present application provides a computer program, where the computer program includes instructions, and when the computer program is executed by a computer, the computer can execute the process executed by the service device in the second aspect.
Drawings
FIG. 1 is a schematic structural diagram of a control device based on an adaptive platform and an ROS2, provided by an embodiment of the present application;
FIG. 2 is a block diagram of an SOA provided by an embodiment of the present application;
FIG. 3 is a block diagram of a ROS2 provided in an embodiment of the present application;
FIG. 4 is a first flowchart of a control method based on an adaptive platform and an ROS2 according to an embodiment of the present application;
fig. 5 is a second flowchart of a control method based on an adaptive platform and an ROS2 provided in an embodiment of the present application.
Detailed Description
The embodiments of the present application will be described below with reference to the drawings.
The terms "first" and "second," and the like in the description and claims of this application and in the drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
As used in this specification, the terms "component," "module," "system," and the like are intended to refer to a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, a component may be, but is not limited to being, a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of illustration, both an application running on a computing device and the computing device can be a component. One or more components can reside within a process and/or thread of execution and a component can be localized on one computer and/or distributed between 2 or more computers. In addition, these components can execute from various computer readable media having various data structures stored thereon. The components may communicate by way of local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from two components interacting with another component in a local system, distributed system, and/or across a network such as the internet with other systems by way of the signal).
First, some terms in the present application are explained so as to be easily understood by those skilled in the art.
(1) SOA: service oriented architecture.
(2) AP (automatic Adaptive platform), Adaptive platform.
(3) ROS 2: and the middleware is used for anonymously publishing, subscribing and transferring information among different processes.
(4) Node: a node, is an entity that communicates with other nodes using the ROS framework.
(5) Message: message, the data structure used in subscribing and publishing topics in the ROS 2.
(6) topics, a node may publish information to a topic and may also subscribe to a topic to receive messages.
(7) MDC: mobile Data Center, intelligent driving computing platform.
(8) MCU: microcontroller Unit, a micro control Unit.
(9) Socket: is an intermediate software abstraction layer for the application layer to communicate with the TCP/IP protocol suite, which is a set of interfaces.
(10) YUV, a color coding method, is generally used for data processing.
(11) Mini: MDC can be used for secondary developed chips for image processing.
(12) Host: MDC can be used for secondary developed chips for architectural services.
(13) Docker: the application container engine is an open-source application container engine, so that developers can package their applications and dependency packages into a portable image and then distribute the portable image to any popular Linux or Windows machine, and virtualization can be realized.
(14) GMSL: gigabit Multimedia Serial Links, a high speed Serial interface, suitable for the transmission of video, audio and control signals, can reach distances of 15m or more using 50 Ω coaxial cables or 100 Ω Shielded Twisted Pair (STP) cables.
(15) CAN: controller Area Network, Controller Area Network.
(16) ETH: an Ethernet network.
(17) HMI: human Machine Interface, Human Machine Interface.
In order to facilitate understanding of the embodiments of the present application, a description will be given below of one of the control systems based on the adaptive platform and the ROS 2.
Referring to fig. 1, the adaptive platform and ROS2 based control system in the present application includes an AP framework and a smart driving computing platform, wherein the smart driving computing platform (MDC) processes and transmits data based on the ROS2 framework; the AP framework and the ROS2 framework realize communication based on socket; the AP acquires external data of a target vehicle acquired by a sensor based on a communication module, processes the acquired data and then sends the processed data to the MDC; and the MDC receives data sent by the AP or sends data to the AP based on the communication module.
The MDC may include a processor that processes the received data based on a processor, which may be any conventional processor; those skilled in the art will appreciate that the processor, computer, or memory may actually comprise multiple processors, computers, or memories that may or may not be stored within the same physical housing. For example, the memory may be a hard drive or other storage medium located differently than a computer. Thus, references to a processor or computer are to be understood as including references to a collection of processors or computers or memories which may or may not operate in parallel. Rather than using a single processor to perform the steps described herein, some components, such as the steering component and the retarding component, may each have their own processor that performs only computations related to the component-specific functions. In some embodiments, the processor may be an MCU, which may enable data to be acquired and processed based on the ROS2 node.
The MDC also can comprise a user interface, and based on the user interface, information is provided for a user or information sent by the user is acquired, so that intelligent driving is realized; the user interface may be an HMI; for example, the user may see the route of the target vehicle through the HMI and interact information based on the HMI and the MDC, such as sending the interaction information to the MDC based on the HMI through a touch screen or voice.
The MDC performs data subscription and publication based on an ROS2 framework inside to realize data processing and transmission, wherein the ROS2 realizes communication with the AP through a socket; the ROS2 realizes data processing and transmission based on nodes, topics (subscriptions) and services, each node receives published topic information (topic) in a subscription mode, and responds to the application and response of each node service according to the topic; specifically, the ROS2 node acts as a publisher, for data publishing, supports publishing of multiple data types, and may be associated with multiple data writers to publish one or more topics; the ROS2 node is used as a subscriber for subscribing data, supports the subscription of multiple data types, can be connected with multiple data readers and subscribes to one or more topics; data writers for updating objects of data to publishers, each data writer corresponding to a particular topic; and the data readers are used for reading data from the subscribers, and each data reader corresponds to a specific topic. Referring to fig. 3, in some embodiments, node1 receives topic1 published by node2 based on a subscription, node4 and node2 receive topic2 published by node1 based on a subscription, node5 receives topic3 published by node1 and node3 based on a subscription, the data storage module stores topic1, topic2 and topic3, and node1 and node3 subscribe to and publish topic with each other.
The AP follows a Service Oriented Architecture (SOA) to perform data processing and data transmission; the SOA consists of a group of services which can be mutually called and application programs of the services; referring to fig. 2, the clients (client 1, client2, and client 3) perform data interaction with the data bus based on the IP/port information; the service terminals (service 1, service2 and service 3) perform data interaction with the data bus based on user services, and the client and the service terminals realize communication with the service terminals based on the data bus. In some embodiments, the AP acquires data through the data bus and interacts with the MDC based on the basic framework of the SOA, so as to implement a user service function, ensure security of intelligent driving, and improve user experience.
The communication module may be communicatively coupled to one or more devices via a network. In some embodiments, the communication module may implement communication connection with other devices through GMSL, CAN, or ETH; for example, the camera transmits data to the AP node through the GMS or the CAN, the AP node transmits data to the ROS2 node of the MDC through the ETH, and transmits and receives data based on the communication module, thereby ensuring the security of data transmission and further ensuring the security of intelligent driving.
The camera comprises a first camera (the model is Leopard AR 0231) and a second camera (the model is MINIEYE), the cameras are used for capturing a plurality of images of the surrounding environment of the target vehicle, the cameras can select a static working mode and a video recording working mode, the installation position of the cameras can be installed on the target vehicle or outside the target vehicle according to the requirement, and the interaction of real-time information with the target vehicle through a hardware interface can be realized. In some embodiments, the first camera sends the collected data to the first AP node through GMSL, and the first AP node performs YUV data configuration on the received collected data and issues the character device data to the Mini; specifically, the first AP node acquires an original photo based on a lane line perception AI algorithm, identifies a lane line, and sends lane line information to the Mini. The second camera issues the received lane line information to a second AP node through the CAN, and the second AP node issues the lane line information to a second ROS2 node through the ETH; the lane line information may include each lane and a lane line between the lanes; specifically, the lane line is a dotted line, a solid line or a double yellow line, the color of the line, the isolation zone of the road, the material of the isolation zone, and even the content of an arrow and characters on the road.
Referring to fig. 1, the control system based on the adaptive platform and the ROS2 in the present application may further include a vehicle controller, where the vehicle controller sends the target vehicle chassis information to a third AP node through the CAN, and sends the first control instruction to a third ROS2 node; the third ROS2 node receives the target vehicle state information from the MCU based on the subscription and issues a second control instruction to the MCU;
the vehicle control unit comprises a plurality of sensors, wherein the sensors are used for acquiring chassis information of a target vehicle, including acquiring an accelerator pedal signal, a brake pedal signal and other part signals, and controlling the action of each part controller on the lower layer after making corresponding judgment so as to drive the vehicle to normally run; the main functions of the vehicle control unit comprise: the system comprises a driving torque control device, a brake energy optimization control device, a whole vehicle energy management device, a CAN network maintenance and management device, a fault diagnosis and treatment device, a vehicle state monitoring device and the like, wherein the driving torque control device, the brake energy optimization control device, the whole vehicle energy management device, the CAN network maintenance and management device, the fault diagnosis and treatment device, the vehicle state monitoring device and the like are used for controlling the operation of the vehicle. The vehicle control unit sends the received chassis information of the target vehicle to a third AP node, and the third AP node generates a first control instruction based on the chassis information of the target vehicle; the first control instruction is generated based on the chassis information provided by the vehicle control unit, the effective information of the target vehicle is fully utilized, and the effectiveness and the safety of data are guaranteed.
The target vehicle may be a car, a train, or the like, and the embodiment of the present application is not particularly limited.
It is understood that fig. 1 to 3 are only an exemplary implementation manner of the present embodiment, and the control system based on the adaptive platform and the ROS2 in the present embodiment includes, but is not limited to, the above control system based on the adaptive platform and the ROS 2.
Referring to fig. 4, fig. 4 is a control method based on an adaptive platform and an ROS2 according to an embodiment of the present application, where the method may be applied to the system shown in fig. 1, and the system shown in fig. 1 may be used to support and execute steps S11-S13 of the method flow shown in fig. 4.
Step S11: collecting data;
specifically, the camera may collect data information of an external environment of the target vehicle, including road information and information of other target vehicles; the system comprises a target vehicle, a camera, a data processing unit and a data processing unit, wherein one target vehicle can correspond to one or more cameras, and can be specifically selected according to needs, and the cameras are connected with a hardware interface of the target vehicle and perform data interaction with an AP (access point) of the target vehicle in real time; the camera is used for monitoring the driving condition of an external target vehicle in a certain road section or monitoring the driving data of all target vehicles in one area, so that the safe driving of the target vehicles is ensured, and the user experience is improved.
Optionally, because the data variety that first camera or second camera gathered is various, a large amount of unnecessary data information may be gathered, can set up the screening module to first camera or second camera, select the data relevant with lane line information in the data that first camera or second camera gathered based on the screening module, then effective data transmission to AP that first camera or second camera obtained with the screening, so that reduce AP's data processing pressure, and improve control command's accuracy.
Step S12: the self-adaptive platform processes the acquired data to obtain a processing result;
specifically, the AP receives data collected by the camera and processes the received data.
The first AP node acquires data acquired by the first camera based on GMSL and processes the data based on a lane line perception AI algorithm, wherein the data includes acquiring an original photo, acquiring lane line information based on the original photo and distributing lane line data before fitting.
Optionally, the first AP node performs YUV data configuration based on the received data, and issues the acquired character device data to the Mini for picture processing; and the second AP node acquires the data acquired by the second camera based on the CAN and issues the acquired data to the AP.
Optionally, the second AP node performs caching processing on the received data and issues the data.
Step S13: and the self-adaptive platform sends the processing result to the intelligent driving computing platform.
Specifically, the first AP node or the second AP node processes the received data, obtains a processing result, and sends the processing result to the MDC based on the ETH.
According to the embodiment of the application, the external data of the target vehicle is collected based on the camera, so that the method is efficient, convenient and fast and is low in cost; the data collected by camera shooting are processed based on the AP, the safety is high, the method can be used for electronic controller units with relatively low resources, and the application range is wide.
Referring to fig. 5, fig. 5 is a control method based on an adaptive platform and an ROS2 according to an embodiment of the present application, where the method may be applied to the system shown in fig. 1, and the system shown in fig. 1 may be used to support and execute steps S21-S24 of the method flow shown in fig. 5.
Step S21: receiving lane line information sent by a self-adaptive platform based on an ROS2 node;
specifically, the ROS2 framework has a plurality of nodes, each node has a specific function, and the MDC receives data sent by the AP node based on the ROS2 and processes the received data based on an algorithm of the ROS2 node; the method comprises the steps that a first ROS2 node receives lane line information sent by a first AP node; the second ROS2 node receives lane line data sent by the second AP node; and the third ROS2 node receives the first control instruction sent by the third AP node.
Step S22: the ROS2 node processes the lane line information to obtain a processing result;
specifically, each ROS2 node has a specific algorithm for processing data, and after the ROS2 node processes the data based on the algorithm, the processing result is converted into topic, so that other ROS2 nodes receive and release the data based on subscription; for example, the first ROS2 node forwards the received lane line information: the second ROS2 node processes the received lane line data to acquire subject information; the third ROS2 node generates a second control order based on the first control order.
Step S23: according to the subscription data, publishing the processing result to obtain a publishing result;
specifically, each ROS2 node processes the data received by the node based on an algorithm, converts the processing result into topic, and sends the information corresponding to the topic to the subscribed ROS2 node if it receives that another ROS2 node subscribes to the topic, so as to publish the information corresponding to the topic. The fourth ROS2 node subscribes topic information, lane line data sent by the second ROS2 node are obtained, and a lane line fitting result is obtained based on the lane line data; the fifth ROS2 node subscribes topic information, lane line data sent by the second ROS2 node are obtained, and a decision optimization result is obtained based on the lane line data; and the sixth ROS2 node subscribes the topic information, acquires lane line data sent by the second ROS2 node, and acquires the optimization result of the control algorithm based on the lane line data.
For example, after receiving the control instruction, the MCU performs data processing according to the control instruction, including but not limited to generating a lane line fitting, decision planning or control algorithm optimization instruction, the MCU sends the lane line fitting instruction to the fourth ROS2 node, the fourth ROS2 node subscribes to subject information, obtains lane line data sent by the second ROS2 node, and obtains a lane line fitting result based on the lane line data.
Step S24: and generating a running route of the target vehicle according to the release result.
Specifically, based on the subscription data, the fourth ROS2 node sends the lane line fitting result to the MCU; the fifth ROS2 node sends the decision optimization result to the MCU; the sixth ROS2 node sends the optimization result of the control algorithm to the MCU; the MCU generates a driving route of the target vehicle based on the lane line fitting result, the decision optimization result and the control algorithm optimization result, and sends the driving route to a seventh ROS2 node.
According to the embodiment of the application, the ROS2 framework and the AP framework are fused, and the information interaction mode and the memory management mode are mutually complementary, so that the software development is effectively accelerated, and the method is suitable for intelligent driving vehicles at the initial stage and the low stage of software development.
The method of the embodiments of the present application is explained in detail above, and the related apparatus of the embodiments of the present application is provided below.
Embodiments of the present application also provide a control apparatus based on an adaptive platform and an ROS2, which may include an acquisition unit, a processing unit, and a transmitting unit. The details of each unit are as follows.
The acquisition unit is used for acquiring data; the data includes the external environment and other target vehicles, such as: the distance to another target vehicle, the speed difference to another target vehicle, the number of other target vehicles, etc., and the condition of the road within a certain distance from the target vehicle.
The first processing unit is used for processing the acquired data by the self-adaptive platform to obtain a processing result; and the AP acquires an original photo in the acquired data based on an internal algorithm, such as a lane line perception (AI) algorithm, according to the received acquired data, identifies lane line information according to the original photo, and issues the lane line information.
The transmission unit is used for the self-adaptive platform to transmit the processing result to the intelligent driving computing platform; the sending unit may include a plurality of AP nodes, and the AP nodes are configured to receive data sent by the camera, process the received data, and then send the data to the intelligent driving computing platform.
For example, the first AP node receives data sent by the first camera based on GMSL, processes the data, and then sends the data to the intelligent driving computing platform based on ETH; and the second AP node receives the data sent by the second camera based on the CAN, processes the data and then sends the data to the intelligent driving computing platform based on the ETH.
In a possible implementation manner, the apparatus further includes a vehicle controller, and the vehicle controller is configured to collect chassis information of the target vehicle and send the chassis information to the first AP node.
Embodiments of the present application also provide a control apparatus based on an adaptive platform and an ROS2, the control apparatus may include a receiving unit, a converting unit, a issuing unit, and a generating unit, and detailed descriptions of the respective units are as follows:
the receiving unit is used for receiving lane line information sent by the self-adaptive platform based on the ROS2 node; for example, the first ROS2 node receives lane line information sent by the first AP node and forwards the lane line information to the Host subsystem for processing; and the second ROS2 node receives the lane line data sent by the second AP node and converts the lane line data into topic, so that other ROS2 nodes can receive the lane line data corresponding to the topic based on subscription.
The second processing unit is used for processing the lane line information by the ROS2 node to obtain a processing result; the ROS2 node processes the received data based on an internal algorithm and converts the data into corresponding topics, so that other ROS2 nodes receive the topics based on subscriptions and publish the topics.
And the publishing unit is used for publishing the processing result according to the subscription data to acquire a publishing result.
The generating unit is used for generating a running route of the target vehicle according to the release result; the generating unit is connected with the vehicle control unit and performs information interaction with the vehicle control unit based on the third AP node.
The generating unit comprises a third ROS2 node, receives the state information of the target vehicle sent by the MCU, and sends a second control instruction to the MCU. The MCU acquires the state information of the target vehicle in real time based on the state information of the target vehicle fed back by each sensor in the target vehicle, and sends the state information of the target vehicle to a third ROS2 node, so that the third ROS2 node can more accurately generate a second control instruction by combining with a received first control instruction sent by a third AP node, and convert the second control instruction into topic, and the MCU generates lane line fitting topic, decision planning topic and control algorithm optimization topic based on the topic.
The embodiment of the application also provides a control device based on the adaptive platform and the ROS2, and the device comprises at least one processor, at least one memory and at least one communication interface. In addition, the device may also include common components such as an antenna, which will not be described in detail herein.
The processor may be a general purpose Central Processing Unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to control the execution of programs according to the above schemes.
A communication interface, which is used to communicate with other devices or communication Networks, such as ethernet, Radio Access Network (RAN), core network, Wireless Local Area Network (WLAN), etc.
The Memory may be, but is not limited to, a Read-Only Memory (ROM) or other type of static storage device that can store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory may be self-contained and coupled to the processor via a bus. The memory may also be integral to the processor.
Wherein, the memory is used for storing the application program codes for executing the above scheme and is controlled by the processor to execute. The processor is configured to execute application program code stored in the memory.
The memory stores code that may implement the subject vehicle control methods provided above, such as acquiring data collected by a camera.
It should be noted that, for the functions of the functional units in the control device target vehicle based on the adaptive platform and the ROS2 described in the embodiment of the present application, reference may be made to the description of steps S11 to S13 and steps S21 to S24 in the above method embodiment, and details are not repeated here.
The embodiment of the application also provides a control device based on the adaptive platform and the ROS2, and the device comprises at least one processor, at least one memory and at least one communication interface. In addition, the device may also include common components such as an antenna, which will not be described in detail herein.
The processor may be a general purpose Central Processing Unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to control the execution of programs according to the above schemes.
A communication interface, which is used to communicate with other devices or communication Networks, such as ethernet, Radio Access Network (RAN), core network, Wireless Local Area Network (WLAN), etc.
The Memory may be, but is not limited to, a Read-Only Memory (ROM) or other type of static storage device that can store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. The memory may be self-contained and coupled to the processor via a bus. The memory may also be integral to the processor.
Wherein, the memory is used for storing the application program codes for executing the above scheme and is controlled by the processor to execute. The processor is configured to execute application program code stored in the memory.
The memory stores code that may implement the target vehicle control methods described above, such as sending an optimal travel route to the target vehicle.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit may be stored in a computer-readable storage medium if it is implemented in the form of a software functional unit and sold or used as a separate product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a storage medium, and including several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, and may specifically be a processor in the computer device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. The storage medium may include: a U-disk, a removable hard disk, a magnetic disk, an optical disk, a Read-Only Memory (ROM) or a Random Access Memory (RAM), and the like.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (6)
1. A control method based on an adaptive platform and an ROS2 is characterized by comprising the following steps:
receiving lane line information sent by a self-adaptive platform based on an ROS2 node; the method for receiving lane line information sent by the self-adaptive platform based on the ROS2 node comprises the following steps: the first ROS2 node receives the lane line information sent by the first AP node; the second ROS2 node receives lane line data sent by the second AP node; the third ROS2 node receives a first control instruction sent by the third AP node;
the ROS2 node processes the lane line information to obtain a processing result;
according to the subscription data, publishing the processing result to obtain a publishing result; the publishing the processing result according to the subscription data to obtain a publishing result comprises: a fourth ROS2 node subscribes topic information, acquires the lane line data sent by the second ROS2 node, and acquires a lane line fitting result based on the lane line data; a fifth ROS2 node subscribes the topic information, acquires the lane line data sent by the second ROS2 node, and acquires a decision optimization result based on the lane line data; the sixth ROS2 node subscribes the topic information, acquires the lane line data sent by the second ROS2 node, and acquires a control algorithm optimization result based on the lane line data;
and generating a running route of the target vehicle according to the release result.
2. The method of claim 1, wherein the ROS2 node processes the lane marking information to obtain a processing result, comprising:
the first ROS2 node forwards the received lane line information:
the second ROS2 node processes the received lane line data to acquire subject information;
the third ROS2 node generates a second control instruction based on the first control instruction.
3. The method of claim 2, wherein generating a travel route for a target vehicle based on the published results comprises:
based on subscription data, the fourth ROS2 node sends the lane line fitting result to an MCU; the fifth ROS2 node sends the decision optimization result to an MCU; the sixth ROS2 node sends the control algorithm optimization result to the MCU;
the MCU generates a driving route of the target vehicle based on the lane line fitting result, the decision optimization result and the control algorithm optimization result, and sends the driving route to a seventh ROS2 node.
4. The method of claim 1, wherein the obtaining a first control command of the target vehicle comprises:
the self-adaptive platform acquires chassis information of the target vehicle sent by the vehicle control unit;
and the self-adaptive platform processes the chassis information to acquire the first control instruction.
5. A control device based on an adaptive platform and a ROS2, comprising:
the receiving unit is used for receiving lane line information sent by the self-adaptive platform based on the ROS2 node; the method for receiving lane line information sent by the self-adaptive platform based on the ROS2 node comprises the following steps: the first ROS2 node receives the lane line information sent by the first AP node; the second ROS2 node receives lane line data sent by the second AP node; the third ROS2 node receives a first control instruction sent by the third AP node;
the second processing unit is used for processing the lane line information by the ROS2 node to obtain a processing result;
the publishing unit is used for publishing the processing result according to the subscription data to obtain a publishing result; the publishing the processing result according to the subscription data to obtain a publishing result comprises: a fourth ROS2 node subscribes topic information, acquires the lane line data sent by the second ROS2 node, and acquires a lane line fitting result based on the lane line data; a fifth ROS2 node subscribes the topic information, acquires the lane line data sent by the second ROS2 node, and acquires a decision optimization result based on the lane line data; the sixth ROS2 node subscribes the topic information, acquires the lane line data sent by the second ROS2 node, and acquires a control algorithm optimization result based on the lane line data;
and the generating unit is used for generating a running route of the target vehicle according to the release result.
6. A computer storage medium, characterized in that it stores a computer program which, when executed by a processor, implements the method of any of the preceding claims 1-4.
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