Peripheral extension method and system for robot with body

Abstract

The invention belongs to the technical field of robot peripherals, and discloses a peripheral extension method and system for a robot with a body, and the method comprises the steps: optimizing the starting process of the robot with the body based on a modular design concept, and processing a circuit board through employing an electromagnetic shielding technology; and according to the optimized starting process and the hardware acceleration module, designing a hardware interface standard of the robot with the body and the external equipment, and optimizing a communication protocol between the external equipment based on the hardware interface standard. According to the method, by optimizing the starting process, unnecessary operation steps are reduced, the starting time is remarkably shortened, and the response speed and the working efficiency of the system are improved; in addition, the electromagnetic shielding technology is adopted, it is ensured that the robot system stably operates in the complex electromagnetic environment, and the influence of electromagnetic interference on the system performance is effectively prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of robot peripherals, and particularly to a peripheral expansion method and system for embodied robots. Background Art

[0002] With the rapid development of artificial intelligence, robotics, sensor technology, and automation technology, the robotics industry is experiencing an unprecedented period of opportunity. Starting from the automation of industrial production lines, it has now been widely applied in multiple fields such as healthcare, logistics, and agriculture. Robotics technology has continuously overcome traditional limitations and realized the transformation from a single mechanical device to an intelligent, flexible, and efficient system. In particular, in recent years, the rapid development of intelligent collaborative robots and service robots has greatly expanded the application scenarios of the robotics industry and promoted the continuous growth of market demand.

[0003] However, under the current technical framework, the peripheral expansion of embodied robots still faces several challenges. First, the startup time of complex robot systems is relatively long, which affects the system's response speed and real-time performance. Second, since robots usually need to operate in complex electromagnetic environments, the electromagnetic interference problems in existing technologies seriously affect the system's stability and performance. In addition, the existing underlying software architecture design lacks sufficient real-time support, especially when processing multi-sensor data acquisition and executing real-time control tasks, its response ability is significantly insufficient. Moreover, the adaptation work of peripheral interfaces is cumbersome, and there may be compatibility problems and low data fusion efficiency between the driver programs of different sensors. At the same time, the current underlying communication protocol has limited support for multi-robot collaboration and wireless communication scenarios, and cannot effectively guarantee the stability and real-time performance of network transmission. Finally, the testing and verification work of hardware may have problems due to omissions or inadequacies, especially in complex custom hardware environments, these problems are particularly prominent.

[0004] Therefore, how to provide a peripheral expansion method and system for embodied robots is an urgent problem to be solved at present. Summary of the Invention

[0005] Embodiments of the present invention provide a peripheral expansion method and system for embodied robots to solve the above-mentioned technical problems existing in the prior art.

[0006] To provide a basic understanding of some aspects of the disclosed embodiments, a simple summary is given below. This summary part is not a general review, nor is it intended to identify key / important constituent elements or delineate the protection scope of these embodiments. Its sole purpose is to present some concepts in a simple form as a preface to the subsequent detailed description.

[0007] According to the first aspect of the embodiments of the present invention, a peripheral expansion method for embodied robots is provided.

[0008] In one embodiment, a peripheral expansion method for an embodied robot, the method comprising:

[0009] Optimizing the startup process of the embodied robot based on the modular design concept, and processing the circuit board using electromagnetic shielding technology; designing the hardware interface standard between the embodied robot and external devices according to the optimized startup process and the hardware acceleration module, and optimizing the communication protocol between external devices based on the hardware interface standard.

[0010] In one embodiment, the optimizing the startup process of the embodied robot based on the modular design concept, and processing the circuit board using electromagnetic shielding technology includes:

[0011] Based on the modular design concept, planning the hardware and software architecture of the embodied robot; analyzing and optimizing the startup process of the embodied robot according to the planning results; selecting electromagnetic shielding materials according to the optimized hardware architecture, and processing the circuit board in combination with multi-stage filter technology.

[0012] In one embodiment, the analyzing and optimizing the startup process of the embodied robot according to the planning results includes:

[0013] According to the planning results of the hardware and software architecture, analyzing the startup process of the embodied robot using a performance analysis tool and a log recording tool, identifying the startup steps and determining the execution order of each step; based on the startup process analysis results, preferentially loading target services and target programs, delaying the loading of non-target services and non-target programs, and optimizing the order of the startup process; according to the optimized startup order, disabling non-target log recording operations to optimize the operation boot program; using the optimized operation boot program to modify and optimize the firmware interface source code to obtain the optimized startup process of the embodied robot.

[0014] In one embodiment, the using the optimized operation boot program to modify and optimize the firmware interface source code to obtain the optimized startup process of the embodied robot includes:

[0015] Using the optimized operation boot program to check the firmware driver loading list, identifying and deleting non-target driver programs, and rearranging the loading order of driver programs based on the importance of hardware components; according to the rearranged loading order, modifying the hardware initialization code to optimize the process of parallel initializing several hardware components; locating the time delay positions in the firmware interface source code according to the optimized operation boot program logic, adjusting the delay parameters to optimize the firmware interface source code; based on the optimized firmware interface source code, performing recompilation using compiler options, and obtaining the optimized startup process of the embodied robot through the recompiled firmware.

[0016] In one embodiment, designing the hardware interface standard between the embodied robot and external devices according to the optimized startup process and the hardware acceleration module, and optimizing the communication protocol between external devices based on the hardware interface standard includes:

[0017] According to the optimized startup process and the hardware acceleration module, utilize the processing module in the hardware architecture to optimize the computing task scheduling; according to the characteristics of different tasks, allocate the computing tasks to the corresponding processing units; according to the allocation results of the computing tasks and the corresponding hardware requirements, design the hardware interface standard between the embodied robot and external devices; based on the designed hardware interface standard, analyze and optimize the communication protocol between the embodied robot and external devices.

[0018] In one embodiment, utilizing the processing module in the hardware architecture to optimize the computing task scheduling according to the optimized startup process and the hardware acceleration module includes:

[0019] According to the optimized startup process, integrate the hardware acceleration module into the hardware architecture and identify the processing modules in the hardware architecture; based on the identified processing modules, initially optimize the computing task scheduling using the priority preemption scheduling algorithm, and distinguish real-time tasks and non-real-time tasks through a synchronization mechanism; according to the distinction results of real-time tasks and non-real-time tasks, optimize the task allocation using the memory management algorithm, and monitor the task running status in combination with a performance monitoring tool to optimize the computing task scheduling.

[0020] In one embodiment, designing the hardware interface standard between the embodied robot and external devices according to the allocation results of the computing tasks and the corresponding hardware requirements includes:

[0021] According to the allocation results of the computing tasks, analyze the performance requirements required for each task; obtain and analyze the external devices of the embodied robot to obtain the interface specifications of the external devices; combine the performance requirements and the interface specifications to design the hardware interface standard between the embodied robot and external devices, and the hardware interface standard includes hardware interface design, driver architecture planning, and data fusion algorithms.

[0022] In one embodiment, combining the performance requirements and the interface specifications to design the hardware interface standard between the embodied robot and external devices includes:

[0023] Combine the task performance requirements and the interface specifications of the external devices to construct a hardware adaptation module, and perform hardware interface design and driver architecture planning based on the hardware adaptation module; according to the performance requirements required for the tasks, collect task data from hardware sensors and preprocess the task data; use the Kalman filter algorithm to suppress noise and estimate the state of the preprocessed task data, and combine a preset deep learning model to associate and fuse the task data of different hardware sensors.

[0024] In one embodiment, the analysis and optimization of the communication protocol between the embodied robot and external devices based on the designed hardware interface standard includes:

[0025] Based on the designed hardware interface standard, analyze the communication protocol between the embodied robot and external devices, identify communication problems; according to the identified communication problems, design a communication adaptation module, and optimize the communication protocol by combining communication technologies and Ethernet adaptation strategies.

[0026] According to the second aspect of the embodiments of the present invention, a peripheral expansion system for an embodied robot is provided.

[0027] In one embodiment, the peripheral expansion system for an embodied robot includes:

[0028] A startup process optimization unit for optimizing the startup process of the embodied robot based on the modular design concept and processing the circuit board using electromagnetic shielding technology;

[0029] A hardware interface design unit for designing the hardware interface standard between the embodied robot and external devices according to the optimized startup process and hardware acceleration module, and optimizing the communication protocol between external devices based on the hardware interface standard.

[0030] According to the third aspect of the embodiments of the present invention, a computer device is provided.

[0031] In some embodiments, the computer device includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the above method are implemented.

[0032] According to the fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided.

[0033] In one embodiment, a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0034] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0035] 1. By optimizing the startup process, the present invention reduces unnecessary operation steps, significantly shortens the startup duration, and improves the response speed and working efficiency of the system; in addition, by using electromagnetic shielding technology, it ensures the stable operation of the robot system in a complex electromagnetic environment and effectively prevents the influence of electromagnetic interference on the system performance.

[0036] 2. By introducing a hardware acceleration module, the present invention enhances the processing capacity of the system under high load conditions, ensuring real-time response when the robot executes multiple tasks. In addition, through a unified hardware interface and driver program architecture, the adaptation process of various sensors is simplified, and a data fusion algorithm is adopted to improve the real-time performance and accuracy of data acquisition.

[0037] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The drawings herein are incorporated into the specification and constitute a part of this specification, showing embodiments consistent with the present invention, and are used together with the specification to explain the principles of the present invention.

[0039] Figure 1 is a flowchart of a peripheral expansion method for an embodied robot shown according to an exemplary embodiment;

[0040] Figure 2 is a schematic block diagram of a peripheral expansion system for an embodied robot shown according to an exemplary embodiment;

[0041] Figure 3 is a schematic structural diagram of a computer device shown according to an exemplary embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] The following description and the drawings fully illustrate the specific embodiments herein, enabling those skilled in the art to practice them. Parts and features of some embodiments may be included in or replaced by parts and features of other embodiments. The scope of the embodiments herein includes the entire scope of the claims and all available equivalents of the claims. Herein, terms such as "first", "second", etc. are only used to distinguish one element from another, and do not require or imply any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a structure, device or equipment including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such structure, device or equipment. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the structure, device or equipment including the said element. The embodiments herein are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts among the embodiments can be referred to each other.

[0043] As used herein, the terms "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings. These are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation on the present invention. In the description of the present application, unless otherwise specified and defined, the terms "mounted", "connected", and "coupled" should be understood in a broad sense. For example, they can be mechanical connections or electrical connections, or can be the communication inside two elements. They can be directly connected or indirectly connected through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0044] As used herein, unless otherwise specified, the term "plurality" means two or more.

[0045] As used herein, the character " / " indicates that the objects before and after are in an "or" relationship. For example, A / B means: A or B.

[0046] As used herein, the term "and / or" is a correlative relationship describing objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B.

[0047] It should be understood that although the steps in the flowchart are shown sequentially in the direction of the arrows, these steps are not necessarily executed sequentially in the direction of the arrows. Unless there is a clear indication in the present application, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the figure may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed alternately or in turn with at least a part of other steps or sub-steps or stages of other steps.

[0048] Each module in the device or system of the present application can be implemented in whole or in part by software, hardware, and their combination. The above-mentioned modules can be embedded in the processor in the computer device in hardware form or be independent of it, or can be stored in the memory in the computer device in software form, so that the processor can call and execute the operations corresponding to each of the above modules.

[0049] Without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0050] Figure 1An embodiment of a peripheral expansion method for an embodied robot according to the present invention is shown.

[0051] In this alternative embodiment, the peripheral expansion method for an embodied robot includes:

[0052] Step S101, optimizing the startup process of the embodied robot based on the modular design concept and processing the circuit board using electromagnetic shielding technology;

[0053] Step S102, designing the hardware interface standard between the embodied robot and external devices according to the optimized startup process and the hardware acceleration module, and optimizing the communication protocol between external devices based on the hardware interface standard.

[0054] In this alternative embodiment, the optimizing the startup process of the embodied robot based on the modular design concept and processing the circuit board using electromagnetic shielding technology includes:

[0055] Based on the modular design concept, planning the hardware and software architecture of the embodied robot; according to the planning results, analyzing and optimizing the startup process of the embodied robot; according to the optimized hardware architecture, selecting electromagnetic shielding materials, and processing the circuit board in combination with multi-stage filter technology.

[0056] In this alternative embodiment, the analyzing and optimizing the startup process of the embodied robot according to the planning results includes:

[0057] According to the planning results of the hardware and software architecture, using performance analysis tools and log recording tools to analyze the startup process of the embodied robot, identifying the startup steps and determining the execution order of each step; based on the startup process analysis results, preferentially loading target services and target programs, delaying the loading of non-target services and non-target programs, and optimizing the order of the startup process; according to the optimized startup order, disabling non-target log recording operations to optimize the operation boot program; using the optimized operation boot program to modify and optimize the firmware interface source code to obtain the optimized startup process of the embodied robot.

[0058] In this alternative embodiment, the using the optimized operation boot program to modify and optimize the firmware interface source code to obtain the optimized startup process of the embodied robot includes:

[0059] Using the optimized operation guidance program, check the firmware driver loading list, identify and delete non-target drivers, and rearrange the loading order of drivers based on the importance of hardware components; according to the rearranged loading order, modify the hardware initialization code to optimize the process of parallel initialization of several hardware components; based on the optimized operation guidance program logic, locate the time delay positions in the firmware interface source code and adjust the delay parameters to optimize the firmware interface source code; based on the optimized firmware interface source code, use compiler options for recompilation, and obtain the optimized startup process of the embodied robot through the recompiled firmware.

[0060] In this alternative embodiment, the design of the hardware interface standard between the embodied robot and external devices according to the optimized startup process and the hardware acceleration module, and the optimization of the communication protocol between external devices based on the hardware interface standard include:

[0061] According to the optimized startup process and the hardware acceleration module, use the processing module in the hardware architecture to optimize the computing task scheduling; according to the characteristics of different tasks, allocate the computing tasks to the corresponding processing units; according to the allocation results of the computing tasks and the corresponding hardware requirements, design the hardware interface standard between the embodied robot and external devices; based on the designed hardware interface standard, analyze and optimize the communication protocol between the embodied robot and external devices.

[0062] In this alternative embodiment, the use of the processing module in the hardware architecture to optimize the computing task scheduling according to the optimized startup process and the hardware acceleration module includes:

[0063] According to the optimized startup process, integrate the hardware acceleration module into the hardware architecture and identify the processing module in the hardware architecture; based on the identified processing module, initially optimize the computing task scheduling using the priority preemption scheduling algorithm, and distinguish real-time tasks and non-real-time tasks through a synchronization mechanism; according to the distinction results of real-time tasks and non-real-time tasks, optimize the task allocation using the memory management algorithm, and monitor the task running status in combination with a performance monitoring tool to optimize the computing task scheduling.

[0064] In this alternative embodiment, the design of the hardware interface standard between the embodied robot and external devices according to the allocation results of the computing tasks and the corresponding hardware requirements includes:

[0065] According to the allocation results of the computing tasks, analyze the performance requirements required for each task; obtain and analyze the external devices of the embodied robot to obtain the interface specifications of the external devices; combine the performance requirements and the interface specifications to design the hardware interface standard between the embodied robot and external devices, and the hardware interface standard includes hardware interface design, driver architecture planning, and data fusion algorithms.

[0066] In this alternative embodiment, the design of the hardware interface standard between the embodied robot and external devices by combining performance requirements and interface specifications includes:

[0067] Combining the task performance requirements and the interface specifications of external devices, constructing a hardware adaptation module, and based on the hardware adaptation module, conducting hardware interface design and driving architecture planning; according to the performance requirements needed for the task, collecting task data from hardware sensors and preprocessing the task data; using the Kalman filtering algorithm to suppress noise and estimate the state of the preprocessed task data, and combining a preset deep learning model to associate and fuse the task data of different hardware sensors.

[0068] In this alternative embodiment, the analysis and optimization of the communication protocol between the embodied robot and external devices based on the designed hardware interface standard includes:

[0069] Based on the designed hardware interface standard, analyzing the communication protocol between the embodied robot and external devices to identify communication problems; according to the identified communication problems, designing a communication adaptation module and optimizing the communication protocol by combining communication technologies and Ethernet adaptation strategies.

[0070] It should be noted that a method for peripheral expansion of an embodied robot specifically includes:

[0071] Step 1. Architecture and modular design

[0072] Adopting modular design to optimize the hardware and software architectures of the robot system, ensuring that each module collaborates efficiently, is easy to expand and maintain. Modular design divides the system into independent sub-modules, and each module performs a specific task, reducing development complexity and accelerating the development process. The following are the specific implementation steps:

[0073] Function division and requirement analysis, analyzing the system functions according to task requirements, dividing them into independent modules such as perception, decision-making, execution, and communication, ensuring low coupling and high independence between modules.

[0074] Hardware modular design, ensuring that each hardware sub-module (such as sensors, power supplies, actuators, etc.) works independently and conducts data transmission through standardized interfaces (such as CAN bus, Ethernet, USB, etc.).

[0075] Software modular design, adopting a layered architecture design, dividing the system into a hardware driver layer, a middleware layer, and an application layer. Each module interacts through standard interfaces, supporting a real-time operating system (RTOS) to ensure task scheduling and resource allocation.

[0076] Collaboration and communication between modules, using standardized communication protocols (such as TCP / IP, UDP, CAN) to ensure efficient data exchange between modules, and adopting an asynchronous communication mechanism to reduce latency.

[0077] Performance optimization and low-power design. Optimize load balancing through reasonable allocation of computing resources, and adopt low-power hardware and dynamic voltage and frequency scaling (DVFS) technology to reduce power consumption.

[0078] Modular testing and verification. Conduct unit testing, integration testing and simulation verification on each module to ensure the stability of the system and its collaborative work.

[0079] Expansion and maintenance. Design expandable interfaces to support the plugging and replacement of subsequent sensor and actuator modules, and simplify system maintenance.

[0080] Planning hardware resources and software functions is a key step in optimizing the robot system architecture. Through reasonable planning, it can be ensured that the system can operate efficiently, be easily expandable, have good performance, and can process multi-sensor data and support real-time requirements. The following are the specific implementation steps:

[0081] (1) Requirement analysis and function definition

[0082] Requirement analysis: Analyze the application scenarios and functional requirements of the robot, such as perception, control, navigation and communication, and clarify the resource requirements of hardware and software.

[0083] Function partitioning: Divide the system functions into independent modules (such as perception, control, communication modules) to ensure low coupling and high cohesion between modules.

[0084] (2) Hardware resource planning

[0085] Hardware modular design: Select appropriate sensors, processing units and communication modules according to requirements to ensure that the modules are independent and the interfaces are standardized.

[0086] Computing resource allocation: Select appropriate processors (such as CPU, GPU) to meet the requirements of data fusion and real-time computing.

[0087] Power consumption optimization and EMC design: Select low-power hardware, and reduce electromagnetic interference through electromagnetic shielding and filters to ensure the stable operation of the system.

[0088] (3) Software function planning

[0089] Modular software architecture: Divide the software into multiple layers (hardware drivers, communication protocols, algorithms, applications, etc.) to ensure efficient collaboration between modules.

[0090] Real-time design: Use a real-time operating system (RTOS) to ensure that high-priority tasks are completed in a timely manner.

[0091] Data Fusion and Communication Protocol: Design a unified data format to support multi-sensor fusion, and select a suitable communication protocol (such as CAN, Ethernet) to ensure stable and efficient data transmission.

[0092] (4) Coordination and Optimization of Hardware and Software Resources

[0093] Resource Docking and Performance Optimization: Allocate hardware and software resources according to module requirements, optimize the overall performance through hardware-software co-design, and reduce latency.

[0094] Load Balancing and Dynamic Scheduling: Dynamically adjust resource allocation according to module load to ensure that critical tasks can obtain computing resources first.

[0095] (5) Testing and Verification

[0096] Unit Testing and Integration Testing: Independently test hardware and software modules to ensure that their respective functions are normal, and conduct integration testing to verify the stability and performance of the system.

[0097] Performance Verification: Verify the performance of the system in scenarios of multi-robot collaboration and high-speed data transmission to ensure that it meets the performance requirements.

[0098] (6) Expansion and Maintenance

[0099] Modular Design Facilitates Expansion: Through modular design, new sensors can be easily added or algorithms can be updated to ensure flexible expansion of the system.

[0100] Flexible Software Update and Hardware Compatibility: Software and hardware are independent, enabling the system to be updated, optimized, and upgraded to ensure long-term operation and maintainability.

[0101] Step 2: Start the Optimization Plan

[0102] Streamline the Boot Process: By streamlining the boot process and optimizing the UEFI source code, improve the system boot speed, especially ensuring fast boot in high-load environments. The following are the basis and steps for modifying and optimizing the UEFI source code:

[0103] (1) Basis for Modifying and Optimizing the UEFI Source Code

[0104] Firmware Initialization Optimization: Reduce unnecessary operations (such as logging, hardware scanning), parallelize initialization tasks, and utilize multi-core processors to accelerate boot.

[0105] Driver and Protocol Optimization: Simplify and optimize device driver loading to reduce the initialization time of driver programs and protocol stacks during boot.

[0106] Hardware Resource Management Optimization: Reduce the interaction steps of the hardware abstraction layer (HAL) to improve the system response speed.

[0107] (2) Specific implementation steps for modifying and optimizing UEFI source code

[0108] Identify startup bottlenecks: Analyze the startup process to identify bottlenecks in firmware initialization, hardware scanning, driver loading, etc.

[0109] Streamline the startup process: Disable unnecessary logging, reduce file system operations, and improve startup speed.

[0110] Optimize driver loading and protocol stack: Only load necessary driver programs, adjust the loading order, and prioritize the startup of critical drivers.

[0111] Optimize firmware time delay: Reduce the waiting time for hardware readiness and set a reasonable timeout.

[0112] Optimize UEFI protocol: Improve the protocol implementation, enhance hardware communication efficiency, and reduce protocol exchange latency.

[0113] Step 3: Real-time optimization and hardware acceleration solutions

[0114] Hardware acceleration module: Use hardware acceleration modules such as GPU and FPGA to quickly process high-performance computing tasks. Optimize real-time operating systems: Optimize real-time operating systems such as RTLinux to improve task scheduling efficiency and ensure that tasks are executed on time. These optimizations significantly enhance the real-time performance and processing power of the system, especially suitable for tasks with high real-time requirements.

[0115] Step 4: Multi-sensor adaptation and data fusion optimization

[0116] Unify hardware interfaces and driver architectures: Design unified interfaces and driver programs for various sensors (such as lidar, IMU, cameras, etc.) to simplify the access process. Efficient data fusion algorithms: Design efficient data fusion algorithms to process sensor-collected data in real time, improving data accuracy and real-time performance. Enhance the environmental perception accuracy and real-time performance of the robot system.

[0117] Step 5: Communication protocol support and network adaptation

[0118] Enhance communication protocol support: Support multiple communication protocols (such as CAN, Ethernet, RS485, etc.) to ensure efficient communication with external devices or other robot systems. Optimize the wireless communication module: Optimize the wireless communication module to improve the stability and real-time performance of wireless communication, ensuring the efficient cooperation of the robot system. Through these optimizations, the collaborative combat ability in multi-robot cooperation and wireless communication environments is greatly enhanced.

[0119] Step 6: Interface debugging and adaptation

[0120] Interface debugging and adaptation are key steps to ensure efficient communication in the robot system. It mainly includes the debugging of CAN, I2C, SPI, and UART interfaces to ensure that the system can stably connect to various devices.

[0121] (1) CAN Interface Debugging

[0122] Hardware Verification: Check the wiring and terminal resistance to ensure normal physical connection.

[0123] Protocol Stack Configuration: Adjust the baud rate and clock to ensure correct data transmission.

[0124] Real-time Verification: Test the timeliness of data transmission under high load.

[0125] Error Handling: Monitor error frames and bit errors to ensure reliable data.

[0126] System Integration Test: Connect to other devices to verify the communication effect.

[0127] (2) I2C Interface Debugging

[0128] Hardware Inspection: Ensure normal SCL, SDA wiring and resistance.

[0129] Protocol Stack Configuration: Set the working mode and clock frequency.

[0130] Communication Verification: Ensure normal data transmission between multiple devices.

[0131] Performance Test: Verify stability under different loads and noise environments.

[0132] Troubleshooting: Solve common problems such as missing ACK.

[0133] (3) SPI Interface Debugging

[0134] Hardware Verification: Check the connection of signal lines such as MISO and MOSI to ensure normal timing.

[0135] Protocol Configuration: Set the clock polarity, transmission mode, etc.

[0136] Data Test: Ensure accurate data transmission.

[0137] Performance Optimization: Test the bandwidth and frequency to ensure stable data transmission.

[0138] Parallel Data Stream Test: Ensure that data from multiple devices does not interfere with each other.

[0139] (4) UART Interface Debugging

[0140] Hardware Verification: Ensure normal connection of signal lines such as TX and RX.

[0141] Baud Rate Setting: Debug the stability at different baud rates.

[0142] Data Verification: Use debugging tools to test whether the communication is normal.

[0143] Flow Control Debugging: Ensure that data is not lost under high load.

[0144] Multi-Device Testing: Ensure the system is stable when multiple devices communicate simultaneously.

[0145] (5) System Integration and Comprehensive Debugging

[0146] Joint Debugging: Ensure that multiple interface devices can work properly simultaneously.

[0147] Load Testing: Verify the system stability under long-term high load.

[0148] Log Monitoring: Analyze anomalies and optimize configurations.

[0149] System Integration: After completing the interface debugging, conduct overall integration testing to ensure that each interface works in coordination.

[0150] Step Seven, 5G Adaptation Solution

[0151] With the development of 5G technology, especially in real-time communication scenarios with high bandwidth and low latency, 5G adaptation will become one of the core technologies of the robot system. A 5G adaptation module is introduced to ensure that the system can achieve high-speed and large-capacity data transmission in vehicle-mounted or industrial environments. Its main optimizations include:

[0152] 5G Communication Module Integration: The system supports the access of 5G modules, including 5GNR (New Radio) technology, to ensure a stable network connection even in high-speed mobile scenarios. Low-Latency Data Transmission: Optimize the 5G communication protocol stack to improve the data transmission speed and latency control, especially suitable for application scenarios such as multi-robot collaboration and video stream transmission. High-Bandwidth Application Support: Provide stable and efficient 5G network access for large-bandwidth data streams, such as high-definition image and video transmission, to ensure that the data stream remains unobstructed even when the system is under high load.

[0153] Step Eight, I2S Audio Adaptation

[0154] In some robotic applications, the processing and transmission of audio data are also crucial. To this end, the adaptation of the I2S (Inter-IC Sound) audio interface is added to the robotic system: High-quality audio acquisition and playback: The I2S interface supports high-quality audio data transmission with audio processing modules (such as microphones, speakers, etc.). The system can collect environmental audio information in real time or conduct voice interactions with users. Optimize audio data processing: Introduce dedicated audio processing chips (such as DSPs) or hardware acceleration modules to ensure clear and low-latency transmission of audio data through efficient data stream transmission and processing. Multi-channel audio support: Support multi-channel audio output, which is suitable for applications such as voice prompts and sound source localization in robotic systems, improving the human-machine interaction ability of the robotic system.

[0155] Step Nine: In-Vehicle Ethernet Adaptation Solution

[0156] Combined with in-vehicle Ethernet technology, the communication ability of the robotic system in the in-vehicle environment is enhanced. The application of in-vehicle Ethernet is particularly important, especially in scenarios that require high-speed and high-bandwidth data transmission (such as sensor data, video streams, control command transmission):

[0157] In-vehicle Ethernet interface support: Design hardware interfaces and driver programs that support standards such as Ethernet AVB and Automotive Ethernet to ensure seamless connection with in-vehicle Ethernet switches and devices. In-vehicle Ethernet protocol stack optimization: Ensure low-latency, high-bandwidth, and highly reliable data transmission by optimizing the protocol stack (such as supporting IEEE 802.1Q, IEEE 802.1AS, etc.). Real-time data transmission: Optimize the data transmission mechanism of the in-vehicle network to ensure that sensor data is transmitted to the processing unit in real time, supporting rapid decision-making and control.

[0158] Step Ten: Hardware Testing and Verification

[0159] Hardware testing and verification are important steps to ensure that the hardware system meets the predetermined requirements in the design, production, integration, and other stages. Its process includes the following steps:

[0160] (1) Requirement analysis and test plan: Clearly define the hardware functions, performance, and reliability requirements, formulate a test plan, and select appropriate test methods and tools.

[0161] (2) Design phase verification: Review the hardware design, conduct simulations and prototype tests to ensure that the design meets the functional requirements.

[0162] (3) Sample production and functional testing: After producing samples, conduct basic function verification, interface testing, and signal integrity testing.

[0163] (4) Performance testing: Test the performance of the hardware at different frequencies, power consumptions, and temperatures to ensure compliance with performance standards.

[0164] (5) Environmental and reliability testing: Verify the stability of the hardware under extreme temperature and humidity, vibration, shock, and voltage fluctuations.

[0165] (6) Compatibility and interoperability testing: Ensure that the hardware is compatible with other devices and platforms and supports relevant communication protocols.

[0166] (7) Security testing: Detect the anti-tampering ability and data security of the hardware to ensure that the firmware has no security vulnerabilities.

[0167] (8) Final verification and compliance testing: Conduct certification tests to ensure that the hardware complies with relevant regulations and quality standards.

[0168] (9) Fault analysis and repair: Analyze the problems found during testing, repair them, and retest to ensure that the problems are solved.

[0169] (10) Documentation and reporting: Organize the test data, generate a detailed report, and record the test results and improvement suggestions.

[0170] (11) Mass production and continuous verification: After entering mass production, continuously conduct sampling tests to ensure that the mass-produced hardware is consistent with the test samples.

[0171] Step Eleven: Comprehensive Optimization and System Integration

[0172] Efficient system integration ensures that different hardware and software modules work together in automotive and industrial environments, especially communication modules, sensor modules, audio modules, 5G modules, etc. The key steps include:

[0173] (1) Requirements analysis and system architecture design: Design a system architecture that supports seamless collaboration of various interfaces, and clarify the interface functions and data flows.

[0174] (2) Hardware interface selection and specification: Select interfaces that are compatible and support high data transfer rates to ensure system scalability.

[0175] (3) Software interface management and coordination: Develop driver programs, optimize the operating system configuration, and design a unified API or middleware.

[0176] (4) Unified protocol and data format: Ensure that the data formats and protocols between interfaces are consistent to avoid data loss or confusion.

[0177] (5) Performance testing and verification: Conduct tests on the interfaces for bandwidth, latency, data integrity, etc. to ensure system stability.

[0178] (6) Error Detection and Fault Tolerance Mechanism: Design real-time monitoring, redundancy mechanism and error recovery mechanism to ensure the fault tolerance of the system.

[0179] (7) System Debugging and Optimization: Gradually debug the interface module, optimize the performance, and eliminate bottlenecks.

[0180] (8) Integration Testing and Verification: Verify the system performance through full-link, load, and long-running tests.

[0181] (9) Documentation and Training: Organize technical documents to ensure that team members master the use and maintenance of the system.

[0182] (10) Continuous Monitoring and Maintenance: Ensure the long-term stable operation of the system through real-time monitoring and regular optimization.

[0183] (11) Through these steps, the system can be efficiently integrated to ensure that different modules work together in a complex environment.

[0184] Optimize resource scheduling and data flow control, and improve the system response ability by dynamically adjusting bandwidth and priority. The specific implementation steps include:

[0185] (1) Requirement Analysis and Load Modeling: Establish a load model and analyze characteristics such as interface traffic and bandwidth requirements.

[0186] (2) System Resource Monitoring and Data Collection: Real-time monitor hardware resources and interface load to obtain performance data.

[0187] (3) Intelligent Scheduling Algorithm Design: Design bandwidth allocation and priority scheduling algorithms to dynamically adjust resources based on load.

[0188] (4) Dynamic Load Balancing and Resource Adjustment: According to the load situation, perform resource scheduling and bandwidth adjustment to ensure the optimal system performance.

[0189] (5) Real-time Monitoring and Feedback Mechanism: Continuously monitor the system performance and adjust the scheduling strategy.

[0190] (6) Fault Tolerance and High Availability Design: Design redundant resources and fault recovery mechanisms to ensure the system stability.

[0191] (7) Performance Testing and Optimization: Conduct load, throughput, and latency tests to optimize the scheduling algorithm.

[0192] (8) Documentation and Training: Record the optimization strategy and train technical personnel to understand and apply the scheduling algorithm.

[0193] Through intelligent scheduling and optimization, ensure the stable and efficient operation of the system under load changes and improve resource utilization.

[0194] The specific implementation of a peripheral expansion method for embodied robots mainly describes the hardware and software optimization solutions adopted in the vehicle-mounted system, including startup time optimization, electromagnetic interference protection, hardware acceleration processing, sensor data fusion, communication protocol optimization, etc. The purpose is to improve the stability, real-time performance, adaptability and intelligence of the system. The specific embodiments are as follows:

[0195] Step 1. Startup time optimization method

[0196] (1) Optimize the bootloader, preferentially load core services and necessary drivers, and delay the loading of non-core modules to reduce waiting time during startup.

[0197] (2) Streamline the startup process, adjust system parameters, disable unnecessary background processes and logging, reduce resource occupancy, and optimize data transmission.

[0198] (3) Delay service startup, delay the loading of non-core services, and ensure that core services start first.

[0199] (4) Optimize kernel parameters, adjust kernel configuration, optimize memory management and CPU scheduling, and improve startup efficiency.

[0200] (5) Compress data transmission, use compression algorithms to reduce data transmission volume and resource occupancy during startup.

[0201] Step 2. Anti-electromagnetic interference design

[0202] (1) Electromagnetic shielding design

[0203] Special electromagnetic shielding materials are used in the hardware design. To ensure that the system can work properly in the high electromagnetic noise environment of the vehicle, a metal shell with high electromagnetic shielding effect is designed, and the internal circuit is shielded and isolated from the external environment to reduce the impact of electromagnetic interference on signals.

[0204] (2) Power line filtering

[0205] In the power management module, a more refined power filtering circuit design is adopted. By adding multiple stages of filters, especially the effective isolation of high-frequency noise, the electromagnetic interference resistance of the system is significantly improved. The specific method is to design a filter combination of multiple capacitors and inductors at the power input end to effectively block high-frequency noise generated by the engine and other wireless devices. Technical effect: The anti-interference ability is improved by about 20%-30%.

[0206] Step 3. Hardware acceleration and processing performance improvement method

[0207] (1) Integration of GPU acceleration module

[0208] Hardware Integration: Select a suitable GPU (such as NVIDIA Jetson or ARM Mali GPU), combine it with an ARM processor, share memory through a high-speed interface, and optimize memory management.

[0209] Software Optimization: Assign highly parallel tasks (such as image processing and path planning) to the GPU and serial tasks to the CPU. Use CUDA or OpenCL for programming and optimize data transfer and computing task scheduling.

[0210] (2) Hardware-Accelerated Task Allocation

[0211] Task Analysis: The CPU is suitable for control logic and low-parallel tasks, while the GPU is suitable for high-parallel tasks (such as image processing and deep learning).

[0212] Task Allocation: Dynamically allocate tasks according to task parallelism and real-time requirements to ensure efficient utilization of CPU and GPU resources.

[0213] Scheduling and Load Balancing: Monitor the system load in real time, adjust task allocation, and ensure load balancing and real-time response.

[0214] Step 4: Sensor Data Fusion Optimization Method

[0215] (1) Unified Hardware Interface Design: Design an adapter module to enable devices such as lidar, cameras, and ultrasonic sensors to be connected through a unified interface, simplifying sensor adaptation.

[0216] (2) Efficient Data Fusion Algorithm: Combine Kalman filtering and deep learning to improve data processing accuracy and real-time performance, with an efficiency increase of 30%-50%. The steps are as follows:

[0217] Data Acquisition and Preprocessing: Collect and process sensor data, denoise, remove anomalies, and normalize.

[0218] Deep Learning Fusion: Use CNN, RNN, and LSTM for data fusion:

[0219] Early Fusion: Concatenate sensor data

[0220] Mid-Fusion: Merge after branch processing

[0221] Late Fusion: Weighted merge of prediction results

[0222] Training and Optimization: Optimize the deep learning model through data training, and use loss functions (such as MSE and cross-entropy) and transfer learning to improve efficiency.

[0223] Post-Processing and Decision Making: Smooth the fusion results for path planning, collision detection, etc.

[0224] Real-time optimization: Utilize GPU / TPU to accelerate inference and optimize algorithms to improve real-time performance and processing capabilities.

[0225] Step 5: Communication Protocol Optimization and Network Adaptation Method

[0226] (1) Optimize the underlying communication protocol, optimize in-vehicle Ethernet and 5G protocols, enhance compatibility and efficiency, reduce data transmission latency, and improve stability.

[0227] In-vehicle Ethernet optimization: Improve bandwidth utilization, optimize flow control (such as TSN protocol), priority scheduling, and low-latency transmission. Strengthen error detection and recovery, and introduce multi-path communication.

[0228] 5G protocol optimization: Use network slicing technology to allocate priorities and bandwidth, dynamic spectrum management, and millimeter-wave optimization to reduce latency and increase throughput. Introduce low-latency communication protocols and MEC technology to optimize the response speed of autonomous driving.

[0229] (2) Optimize multi-network collaboration and compatibility to ensure seamless switching between in-vehicle networks (such as in-vehicle Ethernet, 5G, Wi-Fi, etc.), optimize network switching protocols, QoS strategies, and use gateway technology to enhance compatibility. Develop an adaptive protocol stack to dynamically select the most suitable communication protocol according to the network environment.

[0230] Implementation steps for protocol optimization:

[0231] Requirement analysis: Set optimization goals (such as latency, bandwidth, etc.) according to in-vehicle application requirements.

[0232] Protocol design and modification: Optimize the protocol layer, focusing on aspects such as flow control and priority scheduling.

[0233] Simulation and verification: Use simulation tools to verify the optimization effect and ensure stability.

[0234] Hardware and software implementation: Implement the optimized protocol on the in-vehicle platform to ensure compatibility.

[0235] System integration and testing: Integrate the optimized protocol and conduct real-scenario testing.

[0236] (3) Enhance the wireless communication adaptation ability, design an adaptation module to support seamless switching between networks such as Wi-Fi, 5G, and in-vehicle Ethernet, and improve communication stability and real-time performance by about 40%-60%.

[0237] By optimizing in-vehicle Ethernet and 5G protocols, network efficiency and stability have been improved, and the adaptability and performance of the system in complex in-vehicle environments have been enhanced.

[0238] By optimizing the bootloader and simplifying the startup process, unnecessary operations (such as logging) are reduced, and the startup time is shortened by about 30% - 50%, significantly improving the system response speed and work efficiency. Especially in the in-vehicle environment, the quick startup reduces the idle time and enhances the driving experience. Anti-interference technologies (such as electromagnetic shielding and power supply filtering design) are adopted in the circuit design, improving the system stability in a high electromagnetic noise environment, and the anti-interference ability is enhanced by 20% - 30%. The introduction of the GPU acceleration module significantly improves the processing ability under high load conditions, ensuring real-time response during multitasking. The processing ability is enhanced by 40% - 60%, meeting the requirements of in-vehicle systems for high real-time performance and multitasking.

[0239] By unifying the hardware interface and driver program architecture, the adaptation process of different sensors (such as lidar, cameras, ultrasonic sensors) is simplified, and the real-time performance and accuracy of data acquisition are improved through an efficient data fusion algorithm. The fusion efficiency is increased by 30% - 50%, enhancing road perception and driving safety. The optimization of the underlying communication protocol and the improvement of the wireless communication module driver and adaptation ensure efficient and stable communication of the robot in a dynamic network environment. Especially in the in-vehicle environment, it supports wireless communication methods such as in-vehicle Ethernet, 5G, and Wi-Fi, and the communication stability and real-time performance are improved by 40% - 60%.

[0240] In the hardware design, a strict testing and verification process is introduced to ensure the stable operation of the module in harsh environments such as high temperature and vibration. The hardware failure rate is reduced by 20% - 30%, improving the system reliability and guaranteeing the long-term stability of the vehicle system. The in-vehicle audio system enhances speech recognition, noise suppression, and audio output quality through advanced signal processing technology. Especially in a noisy environment, the recognition accuracy of the voice assistant and navigation system is significantly improved, enhancing the driver's usage experience.

[0241] Figure 2 An embodiment of a peripheral expansion system for an embodied robot according to the present invention is shown.

[0242] In this alternative embodiment, the peripheral expansion system for an embodied robot includes:

[0243] A startup process optimization unit 201 for optimizing the startup process of the embodied robot based on the modular design concept and processing the circuit board using electromagnetic shielding technology;

[0244] A hardware interface design unit 202 for designing the hardware interface standard between the embodied robot and external devices according to the optimized startup process and hardware acceleration module, and optimizing the communication protocol between external devices based on the hardware interface standard.

[0245] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structural diagram may be as shown in Figure 3 . The computer device includes a processor, a memory, and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in the above method embodiment are implemented.

[0246] Those skilled in the art can understand that Figure 3 the structure shown in is only a block diagram of some structures related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0247] In addition, the present invention also provides a computer device, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the steps in the above method embodiment are implemented.

[0248] Furthermore, the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by the processor, the steps in the above method embodiment are implemented.

[0249] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0250] The present invention is not limited to the structures already described and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is only limited by the appended claims.

Claims

1. A peripheral expansion method for an embodied robot, characterized in that: The method includes: The startup process of the embodied robot is optimized based on the modular design concept, and the circuit board is processed using electromagnetic shielding technology; According to the optimized startup process and hardware acceleration module, the hardware interface standard between the embodied robot and external devices is designed, and the communication protocol between external devices is optimized based on the hardware interface standard.

2. The peripheral expansion method for an embodied robot according to claim 1, characterized in that: The method of optimizing the startup process of the embodied robot based on the modular design concept and using the electromagnetic shielding technology to process the circuit board includes: Based on the modular design concept, plan the hardware and software architecture of the embodied robot; Analyze and optimize the startup process of the embodied robot based on the planning results; According to the optimized hardware architecture, electromagnetic shielding materials are selected, and the circuit board is processed in combination with multi-stage filter technology.

3. The peripheral expansion method for an embodied robot according to claim 2, characterized in that: The process of analyzing and optimizing the startup process of the embodied robot based on the planning results includes: Based on the planning results of the hardware and software architecture, use performance analysis tools and logging tools to analyze the startup process of the embodied robot, identify the startup steps and determine the execution order of each step; Based on the analysis results of the startup process, target services and target programs are loaded first, and non-target services and non-target programs are loaded later, so as to optimize the order of the startup process; Disable non-target logging operations according to the optimized boot sequence to optimize the operation boot process; By using the optimized operation boot program, the firmware interface source code is modified and optimized to obtain the optimized startup process of the embodied robot.

4. The peripheral expansion method for an embodied robot according to claim 3, characterized in that: The startup process of the optimized embodied robot obtained by modifying and optimizing the firmware interface source code using the optimized operation boot program includes: Using the optimized bootloader, check the firmware driver loading list, identify and remove non-target drivers, and rearrange the driver loading order based on the importance of hardware components; Modify the hardware initialization code according to the rearranged loading order to optimize the process of initializing several hardware in parallel; According to the optimized operation boot program logic, locate the time delay position in the firmware interface source code, adjust the delay parameters, and optimize the firmware interface source code; Based on the optimized firmware interface source code, recompilation is performed using compiler options, and the optimized startup process of the embodied robot is obtained through the recompiled firmware.

5. The peripheral expansion method for an embodied robot according to claim 1, characterized in that: The design of the hardware interface standard between the embodied robot and the external device according to the optimized startup process and the hardware acceleration module, and the optimization of the communication protocol between the external devices based on the hardware interface standard include: According to the optimized startup process and hardware acceleration module, the computing task scheduling is optimized by utilizing the processing module in the hardware architecture; According to the characteristics of different tasks, the computing tasks are assigned to the corresponding processing units; Design the hardware interface standard between the embodied robot and external devices based on the distribution results of computing tasks and the corresponding hardware requirements; Based on the designed hardware interface standards, the communication protocol between the embodied robot and external devices is analyzed and optimized.

6. The peripheral expansion method for an embodied robot according to claim 5, characterized in that: The optimizing of computing task scheduling by using the processing module in the hardware architecture according to the optimized startup process and the hardware acceleration module includes: According to the optimized startup process, the hardware acceleration module is integrated into the hardware architecture, and the processing modules in the hardware architecture are identified; Based on the identified processing modules, the priority preemptive scheduling algorithm is used to preliminarily optimize the scheduling of computing tasks, and the synchronization mechanism is used to distinguish between real-time tasks and non-real-time tasks; Based on the distinction between real-time tasks and non-real-time tasks, the memory management algorithm is used to optimize task allocation, and the performance monitoring tool is used to monitor the task running status and optimize computing task scheduling.

7. The peripheral expansion method for an embodied robot according to claim 6, characterized in that: The hardware interface standard between the embodied robot and the external device is designed according to the distribution result of the computing task and the corresponding hardware requirements, including: According to the distribution results of computing tasks, analyze the performance requirements of each task; Acquire and analyze the external devices of the embodied robot to obtain the interface specifications of the external devices; In combination with performance requirements and interface specifications, the hardware interface standard between the embodied robot and external devices is designed. The hardware interface standard includes hardware interface design, drive architecture planning and data fusion algorithm.

8. The peripheral expansion method for an embodied robot according to claim 7, characterized in that: The hardware interface standards between the embodied robot and the external device are designed in combination with the performance requirements and interface specifications, including: Combine the task performance requirements and the interface specifications of external devices to build a hardware adaptation module, and then design the hardware interface and plan the driver architecture based on the hardware adaptation module; Collect task data from hardware sensors and pre-process the task data according to the performance requirements of the task; The Kalman filtering algorithm is used to perform noise suppression and state estimation on the preprocessed task data, and the preset deep learning model is combined to associate and fuse the task data of different hardware sensors.

9. The peripheral expansion method for an embodied robot according to claim 8, characterized in that: The hardware interface standard based on the design, analyzing and optimizing the communication protocol between the embodied robot and the external device includes: Based on the designed hardware interface standards, analyze the communication protocol between the embodied robot and external devices to identify communication problems; Based on the identified communication problems, a communication adaptation module is designed, and the communication protocol is optimized by combining communication technology and Ethernet adaptation strategy.

10. A peripheral expansion system for an embodied robot, characterized in that: The system includes: The startup process optimization unit is used to optimize the startup process of the embodied robot based on the modular design concept and use electromagnetic shielding technology to process the circuit board; The hardware interface design unit is used to design the hardware interface standard between the embodied robot and external devices according to the optimized startup process and hardware acceleration module, and optimize the communication protocol between external devices based on the hardware interface standard.

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