Management and control method and equipment based on RISC-V architecture and computer readable medium
By using RISC-V architecture to associate functional modules and sensors in AGV cars, sensing the environment and triggering reaction logic, the problem of insufficient overall control capabilities under the traditional processor architecture is solved, and more efficient dynamic regulation and environmental adaptation are achieved.
Patent Information
- Application Number
- CN202311728123.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-12-14
- Publication Date
- 2025-07-08
AI Technical Summary
In the prior art, automotive domain controllers based on traditional processor architectures have low overall control capabilities for AGV cars, making it difficult to effectively adapt to complex surrounding environments.
The RISC-V architecture is used to correlate multiple functional modules of the AGV car, sense the surrounding environment through the sensor module, determine the current state of the object, and based on this trigger reaction logic, dynamic regulation is achieved.
It improves the overall control capability of AGV trolleys, can better adapt to various environmental changes, improves performance, energy efficiency and data security, and meets the real-time needs of ADAS and autonomous driving.
Smart Images
Figure CN120270267A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of control of the RISC-V architecture, and particularly to a control method, device, and computer-readable medium based on the RISC-V architecture. Background Art
[0002] With the development of technology, AGV vehicles have gradually become intelligent, and AGV vehicles have become highly intelligent complex systems, especially in the field of ADAS (Advanced Driver Assistance System) control. This system is an important part of AGV vehicles and includes various functions such as automatic emergency braking and lane keeping assistance, aiming to improve driving safety and comfort. To achieve this, automobile manufacturers and technology providers have been constantly working hard to improve electronic control technology in the automotive field.
[0003] In the prior art, automotive domain controllers based on traditional processor architectures: These traditional controllers use general-purpose processors (such as ARM or x86 architectures) to perform various tasks, including data acquisition, sensor fusion, decision-making, and execution control. These functions can include automatic emergency braking, adaptive cruise control, lane keeping assistance, blind spot monitoring, traffic sign recognition, automatic parking, etc. Although these systems have been widely used in many automobiles, the overall control ability of AGV vehicles is low. Summary of the Invention
[0004] An object of this application is to provide a control method, device, and computer-readable medium based on the RISC-V architecture, which associates multiple functional modules based on the RISC-V architecture and correlates multiple functional modules, improving the overall control ability of AGV vehicles. At the same time, the current state of an object is determined according to the surrounding environment of the AGV vehicle, so as to trigger the reaction logic of the AGV vehicle based on the current state of the object, realizing the dynamic regulation of the AGV vehicle under the RISC-V architecture, so as to dynamically regulate the surrounding environment of the AGV vehicle, and then adapt to various surrounding environments of the AGV vehicle.
[0005] To achieve the above object, some embodiments of this application provide a control method based on the RISC-V architecture, which is applied to an AGV vehicle, and the control method based on the RISC-V architecture includes:
[0006] Obtain multiple functional modules in the AGV vehicle;
[0007] Associate multiple functional modules based on the RISC-V architecture and correlate multiple functional modules;
[0008] Perceive the surrounding environment of the AGV vehicle based on the sensor module to obtain the surrounding environment of the AGV vehicle;
[0009] Determine the current state of an object based on the surrounding environment of the AGV vehicle;
[0010] Trigger the reaction logic of the AGV vehicle based on the current state of the object.
[0011] Optionally, obtaining multiple functional modules in the AGV vehicle includes:
[0012] Traverse the AGV vehicle and output detection signals;
[0013] Determine the corresponding module based on the passive response of the detection signal;
[0014] If there are multiple modules, determine the corresponding functional module based on the information of the module and clarify the functions of the functional module.
[0015] Optionally, associating multiple functional modules based on the RISC-V architecture and associating multiple functional modules includes:
[0016] Obtain the RISC-V architecture and embed the RISC-V architecture into the AGV vehicle;
[0017] Use the RISC-V architecture as a control module and associate the RISC-V architecture with multiple functional modules;
[0018] Trigger the multitask management of the RISC-V architecture and match multiple functional modules to corresponding tasks;
[0019] Control multiple functional modules for ADAS domain control.
[0020] Optionally, the control of multiple functional modules for ADAS domain control further includes:
[0021] Monitor the working status of multiple functional modules;
[0022] Associate the working status of multiple functional modules and be controlled by the RISC-V architecture;
[0023] The RISC-V architecture constructs a control learning model based on multiple functional modules and controls multiple functional modules for ADAS domain control based on the learning model.
[0024] Optionally, perceiving the surrounding environment of the AGV vehicle based on the sensor module to obtain the surrounding environment of the AGV vehicle includes:
[0025] When the AGV vehicle is in a moving state, trigger the sensor module. At this time, the sensor module is distributed at multiple positions of the AGV vehicle;
[0026] The sensor module dynamically monitors as the AGV vehicle moves and perceives the surrounding environment of the AGV vehicle;
[0027] Multiple regions are formed based on the division of the surrounding environment of the AGV vehicle;
[0028] Synchronously identify multiple regions to determine corresponding objects.
[0029] Optionally, determining the current state of an object according to the surrounding environment of the AGV vehicle includes:
[0030] Obtain multiple objects within the surrounding environment of the AGV vehicle;
[0031] Mark the current state of the object based on the changes of the object within a preset time.
[0032] Optionally, determining the current state of an object according to the surrounding environment of the AGV vehicle includes:
[0033] The changes of the object include position change, speed change, direction change or signal change.
[0034] Optionally, triggering the reaction logic of the AGV vehicle based on the current state of the object includes:
[0035] Obtain the current state of the object;
[0036] Match the current state of the object with a matching table and output a corresponding dynamic event;
[0037] Trigger the reaction logic of the AGV vehicle according to this dynamic event. At this time, regulate the reaction logic of the moving AGV vehicle based on the RISC-V architecture and perform associated control on multiple functional modules.
[0038] Some embodiments of the present application further provide a control device based on the RISC-V architecture, including:
[0039] An acquisition module, configured to acquire multiple functional modules within the AGV vehicle;
[0040] A control module, configured to associate multiple functional modules based on the RISC-V architecture and associate multiple functional modules;
[0041] A surrounding environment module, configured to sense the surrounding environment of the AGV vehicle based on a sensor module to obtain the surrounding environment of the AGV vehicle;
[0042] A state module, configured to determine the current state of an object according to the surrounding environment of the AGV vehicle;
[0043] A reaction logic module, configured to trigger the reaction logic of the AGV vehicle based on the current state of the object.
[0044] Some embodiments of the present application also provide a control device based on the RISC-V architecture, the device includes:
[0045] One or more processors; and a memory storing computer program instructions, which when executed cause the processors to execute the above-mentioned control method based on the RISC-V architecture.
[0046] Some embodiments of the present application also provide a computer-readable medium, on which computer program instructions are stored, and the computer program instructions can be executed by a processor to implement the above-mentioned control method based on the RISC-V architecture.
[0047] Compared with the prior art, in the solution provided by the embodiments of the present application, multiple functional modules in the AGV trolley are obtained; multiple functional modules are associated based on the RISC-V architecture and the multiple functional modules are correlated; the surrounding environment of the AGV trolley is sensed based on the sensor module to obtain the surrounding environment of the AGV trolley; the current state of the object is determined according to the surrounding environment of the AGV trolley; the reaction logic of the AGV trolley is triggered based on the current state of the object. At this time, multiple functional modules are associated based on the RISC-V architecture and the multiple functional modules are correlated, improving the overall control ability of the AGV trolley. At the same time, the current state of the object is determined according to the surrounding environment of the AGV trolley, so as to trigger the reaction logic of the AGV trolley based on the current state of the object, realizing the dynamic regulation of the AGV trolley under the RISC-V architecture, so as to facilitate the AGV trolley to dynamically regulate the surrounding environment of the AGV trolley, and further adapt to various surrounding environments of the AGV trolley. Description of the Drawings
[0048] Figure 1 It is a schematic flow chart of a control method based on the RISC-V architecture provided by an embodiment of the present application;
[0049] Figure 2 Shows Figure 1 The flow chart of S110 in
[0050] Figure 3 Shows Figure 1 The flow chart of S120 in
[0051] Figure 4 Shows Figure 1 The flow chart of S130 in
[0052] Figure 5 Shows Figure 1 The flow chart of S140 in
[0053] Figure 6 Shows Figure 1 The flow chart of S150 in
[0054] Figure 7 Schematic diagram of a sensor module for a control method based on the RISC-V architecture provided by an embodiment of the present application;
[0055] Figure 8 Control schematic diagram of a control method based on the RISC-V architecture provided by an embodiment of the present application;
[0056] Figure 9 Schematic diagram of the connection of multiple sensor modules for a control method based on the RISC-V architecture provided by an embodiment of the present application;
[0057] Figure 10 Shows a block diagram of a control device based on the RISC-V architecture according to an embodiment of the present application;
[0058] Figure 11 Schematic diagram of the structure of a control device based on the RISC-V architecture provided by an embodiment of the present application. Detailed implementation manners
[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present application belong to the scope of protection of the present application.
[0060] Referring to Figures 1 to 11 , an embodiment of the present application also provides a control method based on the RISC-V architecture, which is applied to an AGV vehicle. The control method based on the RISC-V architecture includes:
[0061] Step S110, obtaining multiple functional modules in the AGV vehicle;
[0062] Step S120, associating multiple functional modules based on the RISC-V architecture and associating the multiple functional modules;
[0063] Step S130, sensing the surrounding environment of the AGV vehicle based on a sensor module to obtain the surrounding environment of the AGV vehicle;
[0064] Step S140, determining the current state of an object according to the surrounding environment of the AGV vehicle;
[0065] Step S150, triggering the reaction logic of the AGV vehicle based on the current state of the object.
[0066] In the solution provided by the embodiment of the present application, multiple functional modules in the AGV vehicle are obtained; multiple functional modules are associated based on the RISC-V architecture and the multiple functional modules are associated; the surrounding environment of the AGV vehicle is sensed based on the sensor module to obtain the surrounding environment of the AGV vehicle; the current state of the object is determined according to the surrounding environment of the AGV vehicle; the reaction logic of the AGV vehicle is triggered based on the current state of the object. At this time, multiple functional modules are associated based on the RISC-V architecture and the multiple functional modules are associated, which improves the overall control ability of the AGV vehicle. At the same time, the current state of the object is determined according to the surrounding environment of the AGV vehicle, so as to trigger the reaction logic of the AGV vehicle based on the current state of the object, realizing the dynamic regulation of the AGV vehicle under the RISC-V architecture, so as to dynamically regulate the surrounding environment of the AGV vehicle, and then adapt to various surrounding environments of the AGV vehicle.
[0067] In step S110, multiple functional modules in the AGV vehicle are obtained.
[0068] The specific steps are as follows:
[0069] Step S111, traverse the AGV vehicle and output a detection signal;
[0070] Step S112, determine the corresponding module based on the passive response of the detection signal;
[0071] Step S113, if there are multiple modules, determine the corresponding functional module based on the information of the module and clarify the function of the functional module.
[0072] In the embodiment of the present application, the AGV vehicle is detected. By traversing the AGV vehicle and outputting a detection signal, it is convenient to test each module along the feedback of the detection signal, so as to determine the corresponding module based on the passive response of the detection signal, thereby testing each module of the AGV vehicle. At this time, the detection signal makes a passive response and triggers multiple modules, so as to make a judgment on each module. Multiple modules are concentrated in the ADAS domain control.
[0073] In step S120, multiple functional modules are associated based on the RISC-V architecture and the multiple functional modules are associated.
[0074] In an embodiment of the present application, the RISC-V architecture corresponds to a RISC-V processing unit, which includes a processor core, a cache, a memory management unit (MMU), and a bus interface. The processor unit adopts the RISC-V instruction set and supports multi-core operation. This solution uses the StarFive VisionFive 2 SBC as the main control platform, equipped with 8GB RAM, HDMI 2.0 and MIPI DSI display interfaces, dual gigabit Ethernet, four USB 3.0 / 2.0 ports, a QSPI flash for the bootloader, and supports eMMC flash modules, M.2 NVMe SSDs, and microSD card storage.
[0075] The specific steps are as follows:
[0076] Step S121: Obtain the RISC-V architecture and embed the RISC-V architecture into the AGV cart;
[0077] Step S122: Use the RISC-V architecture as a control module and associate the RISC-V architecture with multiple functional modules;
[0078] Step S123: Trigger the multi-task management of the RISC-V architecture and match the multiple functional modules with corresponding tasks;
[0079] Step S124: Control the multiple functional modules for ADAS domain control;
[0080] In an embodiment of the present application, the RISC-V architecture is an open and customizable computer processor architecture, which is widely used in embedded systems, chip design, and automotive control systems. It is based on the reduced instruction set (Reduced Instruction Set Computing, RISC) and has high customizability and openness; by associating the RISC-V architecture with multiple functional modules, it is convenient to control the multiple functional modules for ADAS domain control to manage the AGV cart. Therefore, associating the RISC-V architecture with multiple functional modules and performing ADAS domain control on the multiple functional modules improves the overall control ability of the AGV cart.
[0081] At this time, obtain the RISC-V architecture and embed the RISC-V architecture into the AGV cart. According to the RISC-V architecture as a control module and associate the RISC-V architecture with multiple functional modules, so as to perform overall control on the multiple functional modules in the RISC-V architecture. Among them, trigger the multi-task management of the RISC-V architecture and match the multiple functional modules with corresponding tasks, and control the multiple functional modules for ADAS domain control to manage the AGV cart, so as to facilitate the cooperation of the corresponding functional modules in the form of their respective tasks.
[0082] In addition, the control of ADAS domain control of multiple functional modules also includes: monitoring the working status of multiple functional modules; associating the working status of multiple functional modules and controlling them by the RISC-V architecture; the RISC-V architecture constructs a control learning model according to the multiple functional modules, and controls the ADAS domain control of the multiple functional modules based on the learning model.
[0083] At this time, the introduction of RISC-V architecture provides higher performance, greater flexibility and better security, thereby solving problems such as performance, energy efficiency, data security and customizability. Specifically, it includes:
[0084] Performance improvement: The RISC-V architecture provides high-performance computing capabilities to meet real-time data processing and low latency requirements, especially for ADAS and autonomous driving applications.
[0085] Improved energy efficiency: The RISC-V architecture can support more efficient energy management, extend battery life, and reduce energy consumption.
[0086] Enhanced data security: The customizability of RISC-V allows the implementation of hardware-level data encryption and security mechanisms, improving data security and reducing potential risks.
[0087] Improved customizability: RISC-V’s customizability provides greater flexibility to meet the customization needs of different vehicle models and applications, promoting innovation.
[0088] In step S130, the surrounding environment of the AGV is sensed based on the sensor module to obtain the surrounding environment of the AGV.
[0089] In an embodiment of the present application, the sensor module senses the surrounding environment and transmits the data to the RISC-V processor unit for real-time analysis, including object detection, speed measurement, etc. At this time, the surrounding environment of the AGV car is sensed based on the sensor module to obtain the surrounding environment of the AGV car, so as to facilitate further judgment based on the surrounding environment of the AGV car.
[0090] The specific steps are as follows:
[0091] Step S131, when the AGV is in a moving state, trigger the sensor module, at which point the sensor modules are distributed at multiple locations of the AGV;
[0092] In an embodiment of the present application, when the AGV is in a moving state, the sensor module is triggered so that the sensor module can detect the surrounding environment of the AGV in a dynamic state. At this time, the sensor modules are distributed at multiple positions of the AGV and explore the surrounding environment of the AGV.
[0093] The sensor module includes a lidar, a high-definition camera, and other sensors. They are used to sense the environment around the AGV vehicle and provide real-time data streams.
[0094] Step S132: The sensor module dynamically monitors as the AGV vehicle moves and senses the environment around the AGV vehicle;
[0095] Step S133: Multiple regions are formed based on the division of the environment around the AGV vehicle;
[0096] Step S134: Synchronously identify multiple regions to determine the corresponding objects;
[0097] In an embodiment of the present application, the sensor module dynamically monitors as the AGV vehicle moves and senses the environment around the AGV vehicle, so as to know the external environment of the AGV vehicle through the environment around the AGV vehicle. Further, identify the environment around the AGV vehicle, form multiple regions based on the division of the environment around the AGV vehicle, synchronously identify multiple regions, and input multiple regions into the region recognition module, so as to determine the corresponding objects through the recognition of the regions; at this time, synchronously identify multiple regions to determine the corresponding objects.
[0098] In step S140, determine the current state of the object according to the environment around the AGV vehicle.
[0099] In an embodiment of the present application, obtain the environment around the AGV vehicle, so as to determine the current state of the object according to the environment around the AGV vehicle, and further evaluate the reaction actions of the AGV vehicle according to the current state of the object.
[0100] The specific steps are as follows:
[0101] Step S141: Obtain multiple objects within the environment around the AGV vehicle;
[0102] Step S142: Mark the current state of the object based on the changes of the object within a preset time; the changes of the object include position changes, speed changes, direction changes, or signal changes.
[0103] In an embodiment of the present application, perform environment recognition on the surrounding environment, so as to obtain multiple objects within the environment around the AGV vehicle, thereby controlling multiple objects. At this time, mark the current state of the object based on the changes of the object within a preset time; the changes of the object include position changes, speed changes, direction changes, or signal changes. The reaction logic of the AGV vehicle will also change with the changes of the surrounding environment and gradually adapt to the control of driverless driving to improve the autonomous control of the AGV vehicle.
[0104] In step S150, the reaction logic of the AGV cart is triggered based on the current state of the object.
[0105] In the embodiments of the present application, the reaction logic of the AGV cart is triggered based on the current state of the object, so as to trigger the reaction logic of the AGV cart through the current state of the object, thereby triggering the change of the AGV cart according to the change of the current state of the object.
[0106] The specific steps are as follows:
[0107] Step S151: Obtain the current state of the object;
[0108] Step S152: Match the current state of the object with the matching table and output the corresponding dynamic event;
[0109] Step S153: Trigger the reaction logic of the AGV cart according to the dynamic event. At this time, the reaction logic of the AGV cart in the moving state is regulated based on the RISC-V architecture, and the correlation control is performed on multiple functional modules.
[0110] In the embodiments of the present application, the current state of the object is obtained, the current state of the object is matched with the matching table, and the corresponding dynamic event is output, so as to trigger the reaction logic of the AGV cart according to the dynamic event. At this time, the reaction logic of the AGV cart in the moving state is regulated based on the RISC-V architecture, and the correlation control is performed on multiple functional modules. At this time, the system supports multi-domain control, including safety module, power module, chassis module, cockpit module, autonomous driving module and body module, to provide comprehensive control of the AGV cart.
[0111] ADAS domain controller perception system solution:
[0112] AGV cart self-state perception sensor): Self-perception uses the body induction sensor to measure the current state of the AGV cart, including: the speed, acceleration, yaw and steering angle of the AGV cart, etc. Body induction usually uses pre-installed measurement units to obtain information, such as: odometer, inertial measurement unit (IMU), gyroscopes and information from the controller area network (CAN) bus.
[0113] Localization Sensor: The localization sensor uses external sensors such as GPS (Exteroceptive Sensor) or dead reckoning based on inertial measurement unit readings for localization, and can determine the global and local positions of the AGV vehicle. High-precision localization of the AGV vehicle usually combines information from multiple sensors, such as GPS, IMU, odometer, and camera, etc. Data fusion of multiple sensors can minimize the limitations and drawbacks of individual sensors and improve the accuracy and reliability of localization.
[0114] Surrounding-sensing Sensors: The surrounding-sensing sensors mainly include cameras, ultrasonic radars, etc.
[0115] In the solution provided by the embodiment of the present application, multiple functional modules in the AGV vehicle are obtained; multiple functional modules are associated based on the RISC-V architecture and the multiple functional modules are correlated; the surrounding environment of the AGV vehicle is sensed based on the sensor module to obtain the surrounding environment of the AGV vehicle; the current state of the object is determined according to the surrounding environment of the AGV vehicle; the reaction logic of the AGV vehicle is triggered based on the current state of the object. At this time, multiple functional modules are associated based on the RISC-V architecture and the multiple functional modules are correlated, which improves the overall control ability of the AGV vehicle. At the same time, the current state of the object is determined according to the surrounding environment of the AGV vehicle, so as to trigger the reaction logic of the AGV vehicle based on the current state of the object, realizing the dynamic regulation of the AGV vehicle under the RISC-V architecture, so as to facilitate the AGV vehicle to dynamically regulate the surrounding environment of the AGV vehicle, and further adapt to various surrounding environments of the AGV vehicle.
[0116] In addition, the present invention applies the RISC-V architecture to provide higher-performance computing capabilities, so as to be able to process real-time data and meet the real-time performance requirements in advanced driver assistance systems (ADAS) and autonomous driving applications.
[0117] The high-performance computing capabilities of the RISC-V architecture help improve the performance and reliability of the autonomous driving system and promote the development of autonomous driving technology. The RISC-V architecture supports more efficient energy management, which helps extend the battery life, reduce fuel consumption, and improve the energy efficiency of the vehicle.
[0118] The customizability of the RISC-V architecture allows the implementation of hardware-level data encryption and security mechanisms, improving data security and helping to prevent malicious attacks and data leakage. The RISC-V architecture provides greater flexibility, allowing custom instruction sets to meet the customization requirements of different vehicle models and applications. This increases the flexibility and innovation capabilities of vehicle manufacturers.
[0119] RISC-V is an open architecture that promotes standardization and interoperability, contributing to driving innovation and cooperation across the automotive industry. Enhancing the driving experience: By improving automotive performance, safety, and the driving experience, the present invention is expected to provide a better driving experience and meet consumers' demands for intelligent vehicles.
[0120] The core of the present invention is the application of the RISC-V architecture to the automotive domain control system. This is a key technical point aimed at improving performance, energy efficiency, data security, and customizability. At this time, not only the hardware level is concerned, but also the integration with software is emphasized. This collaborative work between hardware and software is crucial for implementing an integrated automotive domain control system. Additionally, the present invention adopts a distributed software architecture to achieve parallel operation and an efficient system. The points to be protected include the design and implementation of this distributed architecture.
[0121] Reference Figure 10 , some embodiments of the present application also provide a control device 200 based on the RISC-V architecture, characterized by including:
[0122] An acquisition module 210 for acquiring multiple functional modules within the AGV cart;
[0123] A control module 220 for associating multiple functional modules based on the RISC-V architecture and associating multiple functional modules;
[0124] A surrounding environment module 230 for perceiving the surrounding environment of the AGV cart based on a sensor module to obtain the surrounding environment of the AGV cart;
[0125] A status module 240 for determining the current status of an object according to the surrounding environment of the AGV cart;
[0126] A reaction logic module 250 for triggering the reaction logic of the AGV cart based on the current status of the object.
[0127] In addition, embodiments of the present application also provide a control device based on the RISC-V architecture. The structure of the device is as Figure 11 shown. The device includes a memory 31 for storing computer-readable instructions and a processor 32 for executing the computer-readable instructions. Wherein, when the computer-readable instructions are executed by the processor, the processor is triggered to execute the control method based on the RISC-V architecture.
[0128] The method and / or embodiment in the embodiments of the present application can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program codes for executing the method shown in the flowchart. When the computer program is executed by a processing unit, the above functions defined in the method of the present application are executed.
[0129] It should be noted that the computer-readable medium described in the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, apparatus, or device.
[0130] In the present application, the computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination of the above.
[0131] Computer program code for performing the operations of this application can be written in one or more programming languages or combinations thereof, including object-oriented programming languages and also conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., through the Internet using an Internet service provider).
[0132] The flowcharts or block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of devices, methods, and computer program products according to various embodiments of this application. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks can occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.
[0133] As another aspect, embodiments of this application also provide a computer-readable medium, which can be included in the devices described in the above embodiments; or it can exist separately without being assembled into the device. The above computer-readable medium carries one or more computer-readable instructions, and the computer-readable instructions can be executed by a processor to implement the steps of the methods and / or technical solutions of the foregoing embodiments of this application.
[0134] In a typical configuration of this application, devices of a terminal and a service network both include one or more processors (CPUs), an input / output interface, a network interface, and a memory.
[0135] The memory may include non-permanent memory in the computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.
[0136] A computer-readable medium includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, 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 technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassette tapes, magnetic disk storage, or other magnetic storage devices, or any other non-transitory medium that can be used to store information that can be accessed by a computing device.
[0137] In addition, an embodiment of the present application also provides a computer program, and the computer program is stored in a computer device, so that the computer device executes the method executed by the control code.
[0138] It should be noted that the present application can be implemented in software and / or a combination of software and hardware. For example, it can be implemented using an application-specific integrated circuit (ASIC), a general-purpose computer, or any other similar hardware device. In some embodiments, the software program of the present application can be executed by a processor to implement the above steps or functions. Similarly, the software program (including related data structures) of the present application can be stored in a computer-readable recording medium, such as a RAM memory, a magnetic or optical drive, or a floppy disk and similar devices. In addition, some steps or functions of the present application can be implemented using hardware, for example, as a circuit that cooperates with a processor to execute each step or function.
[0139] For those skilled in the art, it is obvious that the present application is not limited to the details of the above exemplary embodiments, and the present application can be implemented in other specific forms without departing from the spirit or basic characteristics of the present application. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present application is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present application. Any reference signs in the claims should not be construed as limiting the claimed rights. In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. The multiple units or devices stated in the apparatus claims can also be implemented by one unit or device through software or hardware. First, second, etc. are used to denote names and do not denote any particular order.
Claims
1. A control method based on the RISC-V architecture, characterized in that, Applied to an AGV vehicle, the management and control method based on the RISC-V architecture includes: Obtain multiple functional modules within the AGV vehicle; Associate multiple functional modules based on the RISC-V architecture and associate multiple functional modules; Perceive the surrounding environment of the AGV vehicle based on the sensor module to obtain the surrounding environment of the AGV vehicle; Determine the current state of an object according to the surrounding environment of the AGV vehicle; Trigger the reaction logic of the AGV vehicle based on the current state of the object.
2. The control method based on the RISC-V architecture according to claim 1, wherein The obtaining of multiple functional modules within the AGV vehicle includes: Traverse the AGV vehicle and output a detection signal; Determine the corresponding module based on the passive response of the detection signal; If there are multiple modules, determine the corresponding functional module based on the information of the module and clarify the function of the functional module.
3. The control method based on the RISC-V architecture according to claim 2, wherein The associating multiple functional modules based on the RISC-V architecture and associating multiple functional modules includes: Obtain the RISC-V architecture and embed the RISC-V architecture into the AGV vehicle; Use the RISC-V architecture as a control module and associate the RISC-V architecture with multiple functional modules; Trigger the multitasking management of the RISC-V architecture and match multiple functional modules with corresponding tasks; Control multiple functional modules for ADAS domain control.
4. The control method based on the RISC-V architecture according to claim 3, wherein The control of multiple functional modules for ADAS domain control further includes: Monitor the working states of multiple functional modules; Associate the working states of multiple functional modules and be controlled by the RISC-V architecture; The RISC-V architecture constructs a control learning model based on multiple functional modules and controls multiple functional modules for ADAS domain control based on the learning model.
5. The control method based on the RISC-V architecture according to claim 1, wherein The perceiving the surrounding environment of the AGV vehicle based on the sensor module to obtain the surrounding environment of the AGV vehicle includes: When the AGV vehicle is in a moving state, trigger the sensor module. At this time, the sensor module is distributed at multiple positions of the AGV vehicle; The sensor module dynamically monitors as the AGV vehicle moves and perceives the surrounding environment of the AGV vehicle; Form multiple regions based on the division of the surrounding environment of the AGV vehicle; Perform synchronous recognition on multiple regions to determine the corresponding objects.
6. The control method based on the RISC-V architecture according to claim 5, characterized in that The determining the current state of an object according to the surrounding environment of the AGV vehicle includes: Obtain multiple objects within the surrounding environment of the AGV vehicle; Mark the current state of the object based on the changes of the object within a preset time.
7. The control method based on the RISC-V architecture according to claim 6, characterized in that The determining the current state of an object according to the surrounding environment of the AGV vehicle includes: The changes of the object include position change, speed change, direction change or signal change.
8. The control method based on the RISC-V architecture according to claim 7, wherein The triggering the reaction logic of the AGV vehicle based on the current state of the object includes: Obtain the current state of the object; Match the current state of the object with a matching table and output the corresponding dynamic event; Trigger the reaction logic of the AGV vehicle according to this dynamic event. At this time, regulate the reaction logic of the AGV vehicle in a moving state based on the RISC-V architecture and perform associative control on multiple functional modules.
9. A control device based on the RISC-V architecture, characterized in that, The device includes: One or more processors; and A memory storing computer program instructions that, when executed, cause the processor to execute the control method based on the RISC-V architecture according to any one of claims 1 to 8.
10. A computer-readable medium, characterized in that, A computer program instruction is stored thereon, and the computer program instruction can be executed by a processor to implement the control method based on the RISC-V architecture according to any one of claims 1 to 8.