Modularized unmanned distribution vehicle control device and installation method thereof

Abstract

The invention relates to a modularized unmanned distribution vehicle control device and an installation method thereof, and belongs to the technical field of unmanned vehicle intelligent control, the modularized unmanned distribution vehicle control device comprises an unmanned vehicle, the unmanned vehicle is internally provided with a control device hardware structure and an intelligent extension module, and the control device hardware structure is connected with the intelligent extension module. The hardware structure of the control device comprises a main control module, a sensing module group, a communication module group, a power supply module, a driving module group and an installation structure module. The intelligent expansion module comprises an AI acceleration module, an energy consumption management module, a self-diagnosis and identification module and a cooperative communication module which are arranged in the main control module, and a heat dissipation adjusting structure for dissipating heat of each part, and each module has a self-detection function by setting a module state self-diagnosis mechanism; after the module is inserted, the master controller automatically identifies the ID and the type of the module, uploads state information such as voltage, current and temperature, evaluates the health state, and timely maintains and replaces the module.

Description

Technical Field

[0001] This invention belongs to the field of unmanned vehicle intelligent control technology, specifically relating to a modular unmanned delivery vehicle control device and its installation method. Background Technology

[0002] With the continuous development of express delivery services on university campuses, traditional manual pickup faces challenges such as the "last mile" delivery difficulty and uncertain pickup times. Some companies have attempted to introduce unmanned delivery vehicles, but most are costly, bulky, and complex, making them unsuitable for the campus environment. Existing unmanned vehicle control systems are mostly highly integrated, with inconvenient module replacement and difficult debugging, making them ill-suited to the requirements of easy equipment maintenance and flexible functional expansion in a campus setting. Therefore, developing an unmanned vehicle control device with a clear structure, replaceable control modules, and strong adaptability is of great significance. Summary of the Invention

[0003] The purpose of this invention is to provide a modular unmanned delivery vehicle control device and its installation method that are simple in structure and reasonably designed in order to solve the above problems.

[0004] The present invention achieves the above objectives through the following technical solutions:

[0005] A modular unmanned delivery vehicle control device includes an unmanned vehicle, wherein the unmanned vehicle is equipped with a control device hardware structure and an intelligent expansion module.

[0006] The hardware structure of the control device includes a main control module, a sensing module group, a communication module group, a power supply module, a drive module group, and an installation structure module. The main control module is used to perform functions such as path planning, task allocation, and module management, and the main control module is provided with a standard interface to connect to each sub-module.

[0007] The intelligent expansion module includes an AI acceleration module, an energy management module, a self-diagnosis and identification module, a collaborative communication module, and a heat dissipation adjustment structure for each part, all located inside the main control module.

[0008] As a further optimization of the present invention, the drive module group includes control servo motors, motors and other actuators for driving the unmanned vehicle to move, and the mechanisms are arranged independently to reduce thermal interference.

[0009] The installation structure module is used to install each module, and the module is fixed by a track-type slide structure, which facilitates quick installation and replacement.

[0010] The perception module group includes multiple sub-modules such as lidar, camera, ultrasonic, and infrared, which are used to identify the surrounding environment during the movement of the unmanned vehicle. At the same time, the sub-modules support plug-in and cascading.

[0011] The power module adopts an isolated power supply design, with power consumption monitoring and overload protection, and is used to supply power to the entire device, providing power support for the entire device.

[0012] As a further optimization of the present invention, the AI ​​acceleration module is connected to an edge computing unit such as Jetson Nano via a standard slot between the main control module and the AI ​​acceleration module for processing image recognition and complex decision-making tasks.

[0013] The energy management module is equipped with a current detection chip and a voltage detection chip, which work with the algorithm to determine the current task status and optimize energy consumption.

[0014] The self-diagnosis and identification module is used to assist the main control module in loading the corresponding driver according to the identification ID after each module is powered on;

[0015] The collaborative communication module interconnects with other vehicles through UWB or LoRa low-latency networks to exchange task information and achieve dynamic obstacle avoidance and task redistribution.

[0016] As a further optimization of the present invention, the communication module group is set inside the unmanned vehicle, supports the combination and switching of 4G / 5G, LoRa, Wi-Fi and UWB communication methods, and works with the collaborative communication module to schedule and allocate vehicles, while dividing the operating area for vehicle delivery.

[0017] As a further optimization of the present invention, each module in the hardware structure of the control device has an embedded MCU, which contains the corresponding module's ID information to assist in self-diagnosis and identification of the module.

[0018] As a further optimization of the present invention, the main control module is based on the STM32 main control board and is installed in an independently extractable manner.

[0019] As a further optimization of the present invention, the perception module group also includes sensors such as GPS and IMU, and the sensors are distributed hierarchically and are respectively set on different mounting surfaces of the unmanned vehicle.

[0020] As a further optimization of the present invention, during the operation of each module in the hardware structure of the control device, it is also necessary to cool down through a heat dissipation adjustment structure. The heat dissipation adjustment structure includes metal heat sink fins, a fan and a heat sensing control circuit, which automatically starts and stops according to the temperature.

[0021] As a further optimization of the present invention, a method for installing a modular unmanned delivery vehicle control device includes the following steps:

[0022] S1. Install the main control module on the central bracket of the unmanned vehicle, and use the standard interface on the main control module to insert the perception module group, communication module group, power module and AI collaborative processing module into it;

[0023] S2. After each module is inserted, power on the module for initialization and start the self-diagnostic program. During the self-diagnostic program, obtain the status parameters and ID identification code of each module, and mainly detect the voltage, temperature and operating status of each module.

[0024] S3. If all the statuses of each module are normal, the module identification code and status data are sent to the main control module. After receiving the data, the main control module verifies the type and status of each module and loads the corresponding driver or updates the module mapping table required by the module. At this time, each module in the device is ready.

[0025] S4. If the inserted module is in an abnormal state, an alarm device such as an alarm light or buzzer will be used to indicate the abnormal status of the module and report the problematic module. At this time, the module will be tested, replaced, and reconnected for re-self-diagnosis testing.

[0026] The beneficial effects of this invention are as follows:

[0027] 1. The main control unit of this invention is independently removable and installed, with the STM32 main control board as the core, which facilitates system maintenance and upgrades. At the same time, the signal connection adopts a pluggable interface design, and each functional module can be quickly replaced. Furthermore, the sensor modules are distributed hierarchically, including GPS, IMU, ultrasonic, and infrared sensors, which are fixed on different mounting surfaces to reduce signal interference.

[0028] 2. This invention enables each module to have self-detection function by setting a module status self-diagnosis mechanism. After the module is inserted, the main control automatically identifies its ID and type, matches the driver and completes initialization, and uploads status information such as voltage, current and temperature. The main control performs health status assessment and performs timely maintenance and replacement of the module. At the same time, the main control unit monitors the module energy consumption in real time and dynamically schedules the module operation status according to power consumption and task priority. Attached Figure Description

[0029] Figure 1 This is a top view of the modular structure of the control device of the present invention;

[0030] Figure 2 This is a functional structure block diagram of the present invention;

[0031] Figure 3 This is a flowchart of the self-diagnosis and identification process for the storage module status of the present invention;

[0032] Figure 4 This is a structural diagram of the multi-vehicle collaborative communication interface of the present invention;

[0033] Figure 5 This is a logical flowchart of the internal energy consumption management of the system of this invention. Detailed Implementation

[0034] The present application will now be described in further detail with reference to the accompanying drawings. It should be noted that the following specific embodiments are only used to further illustrate the present application and should not be construed as limiting the scope of protection of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application based on the above application content.

[0035] Example 1

[0036] like Figures 1-5 As shown, a modular unmanned delivery vehicle control device includes an unmanned vehicle, and the unmanned vehicle is equipped with a control device hardware structure and an intelligent expansion module.

[0037] Each module in the hardware structure of the control device has an embedded MCU, which records the corresponding module's ID information to assist in self-diagnosis and module identification. This enables each module to have self-testing capabilities and upload status information such as voltage, current, and temperature. The main controller performs health status assessment and monitors module energy consumption based on the actual transmitted data, dynamically scheduling module operation status according to power consumption and task priority.

[0038] The hardware structure of the control device includes a main control module, a sensing module group, a communication module group, a power supply module, a drive module group, and an installation structure module. The main control module is used to perform functions such as path planning, task allocation, and module management. The main control module is equipped with standard interfaces to connect each sub-module. The signal connection adopts a pluggable interface design, which allows each functional module to be quickly replaced.

[0039] The drive module group includes control servos, motors and other actuators to drive the unmanned vehicle to move, and the mechanisms are arranged independently to reduce thermal interference.

[0040] The mounting structure module is used to install each module. It adopts a track-type slide structure to fix the module, which facilitates quick installation and replacement.

[0041] The perception module group includes multiple sub-modules such as lidar, camera, ultrasonic, and infrared, which are used to identify the surrounding environment during the movement of the unmanned vehicle. The sub-modules support plug-and-play and cascading. The perception module group also includes sensors such as GPS and IMU, and the sensors are hierarchically distributed and set on different mounting surfaces of the unmanned vehicle to reduce signal interference and effectively improve the overall response efficiency of the device.

[0042] The power module adopts an isolated power supply design, with power consumption monitoring and overload protection, and is used to supply power to the entire device, providing power support for the entire device.

[0043] The intelligent expansion module includes an AI acceleration module, an energy management module, a self-diagnosis and identification module, a collaborative communication module, and a heat dissipation adjustment structure for each part, all located inside the main control module.

[0044] The AI ​​acceleration module connects to edge computing units such as Jetson Nano via a standard slot with the main control module. It is used to process image recognition and complex decision-making tasks, and improves intelligent perception capabilities through image recognition, crowd detection and other tasks.

[0045] The energy management module is equipped with current detection chips and voltage detection chips, which work with algorithms to determine the current task status and optimize energy consumption.

[0046] The self-diagnosis and identification module is used to assist the main control module in loading the corresponding driver according to the identification ID after each module is powered on. After the module is inserted, the main control module can automatically identify its ID and type, match the driver program and complete the initialization.

[0047] The collaborative communication module connects with other vehicles via UWB or LoRa low-latency networks to exchange task information and achieve dynamic obstacle avoidance and task redistribution.

[0048] The communication module group is located inside the autonomous vehicle and supports the combination and switching of 4G / 5G, LoRa, Wi-Fi and UWB communication methods. It works with the collaborative communication module to schedule and allocate vehicles, and divide the operating area when the vehicle is delivering goods. The multiple communication modes can be switched to a low-power communication mode when the autonomous vehicle's battery is low.

[0049] The main control module is based on the STM32 main control board and is installed independently, which facilitates system maintenance and upgrades.

[0050] During operation, each module in the hardware structure of the control device also needs to be cooled by a heat dissipation and regulation structure. The heat dissipation and regulation structure includes metal heat sinks, fans and thermal sensing control circuits, which automatically start and stop according to the temperature. By collecting temperature data during the operation of each module, the module is cooled down to improve its service life.

[0051] It should be noted that this modular unmanned delivery vehicle control device utilizes a drive module group to propel the unmanned vehicle and a perception module group to detect the environment and avoid obstacles. During operation, the control center allocates the unmanned vehicle's operating area and tasks via a collaborative communication module. During operation, parameters such as voltage, current, and temperature of each module are collected to calculate power consumption and estimate remaining battery capacity. The system then determines whether energy-saving adjustments are needed. If not, the above steps are repeated after a period of time. If energy saving is required, the module operation status is scheduled according to the following priority: 1. Reduce sampling frequency; 2. Shut down unnecessary modules; 3. Switch to low-power communication mode. Simultaneously, the power consumption model is updated and fed back to the main control system.

[0052] Example 2

[0053] like Figures 1-5 As shown, a method for installing a modular unmanned delivery vehicle control device includes the following steps:

[0054] S1. Install the main control module on the central bracket of the unmanned vehicle, and use the standard interface on the main control module to insert the perception module group, communication module group, power module and AI collaborative processing module into it;

[0055] S2. After each module is inserted, power on the module for initialization and start the self-diagnostic program. During the self-diagnostic program, obtain the status parameters and ID identification code of each module, and mainly detect the voltage, temperature and operating status of each module.

[0056] S3. If all the statuses of each module are normal, the module identification code and status data are sent to the main control module. After receiving the data, the main control module verifies the type and status of each module and loads the corresponding driver or updates the module mapping table required by the module. At this time, each module in the device is ready.

[0057] S4. If the inserted module is in an abnormal state, an alarm device such as an alarm light or buzzer will be used to indicate the abnormal status of the module and report the problematic module. At this time, the module will be tested, replaced, and reconnected for re-self-diagnosis testing.

[0058] The embodiments described above are merely examples of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.

Claims

1. A modular unmanned delivery vehicle control device, comprising an unmanned vehicle, characterized in that: The unmanned vehicle is equipped with a control device hardware structure and an intelligent expansion module. The hardware structure of the control device includes a main control module, a sensing module group, a communication module group, a power supply module, a drive module group, and an installation structure module. The main control module is used to perform functions such as path planning, task allocation, and module management, and the main control module is provided with a standard interface to connect to each sub-module. The intelligent expansion module includes an AI acceleration module, an energy management module, a self-diagnosis and identification module, a collaborative communication module, and a heat dissipation adjustment structure for each part, all located inside the main control module.

2. The modular unmanned delivery vehicle control device according to claim 1, characterized in that: The drive module group includes control servos, motors and other actuators to drive the unmanned vehicle to move, and the mechanisms are arranged independently to reduce thermal interference. The installation structure module is used to install each module, and the module is fixed by a track-type slide structure, which facilitates quick installation and replacement. The perception module group includes multiple sub-modules such as lidar, camera, ultrasonic, and infrared, which are used to identify the surrounding environment during the movement of the unmanned vehicle. At the same time, the sub-modules support plug-in and cascading. The power module adopts an isolated power supply design, with power consumption monitoring and overload protection, and is used to supply power to the entire device, providing power support for the entire device.

3. The modular unmanned delivery vehicle control device according to claim 1, characterized in that: The AI ​​acceleration module is connected to edge computing units such as Jetson Nano via a standard slot to the main control module for processing image recognition and complex decision-making tasks. The energy management module is equipped with a current detection chip and a voltage detection chip, which work with the algorithm to determine the current task status and optimize energy consumption. The self-diagnosis and identification module is used to assist the main control module in loading the corresponding driver according to the identification ID after each module is powered on; The collaborative communication module interconnects with other vehicles through UWB or LoRa low-latency networks to exchange task information and achieve dynamic obstacle avoidance and task redistribution.

4. The modular unmanned delivery vehicle control device according to claim 1, characterized in that: The communication module group is located inside the unmanned vehicle and supports the combination and switching of 4G / 5G, LoRa, Wi-Fi and UWB communication methods. It works with the collaborative communication module to schedule and allocate vehicles, and to divide the operating area for vehicle delivery.

5. A modular unmanned delivery vehicle control device according to claim 1, characterized in that: Each module in the hardware structure of the control device has an embedded MCU, which contains the corresponding module's ID information to assist in self-diagnosis and identification of the module.

6. The modular unmanned delivery vehicle control device according to claim 1, characterized in that: The main control module is based on the STM32 main control board and is installed independently by extraction.

7. A modular unmanned delivery vehicle control device according to claim 1, characterized in that: The perception module group also includes sensors such as GPS and IMU, and the sensors are distributed hierarchically and set on different mounting surfaces of the unmanned vehicle.

8. A modular unmanned delivery vehicle control device according to claim 1, characterized in that: During operation, each module in the hardware structure of the control device also needs to be cooled by a heat dissipation adjustment structure, which includes metal heat sink fins, a fan and a thermal sensing control circuit, and automatically starts and stops according to the temperature.

9. A method for installing a modular unmanned delivery vehicle control device according to any one of claims 1 to 7, characterized in that: Includes the following steps: S1. Install the main control module on the central bracket of the unmanned vehicle, and use the standard interface on the main control module to insert the perception module group, communication module group, power module and AI collaborative processing module into it; S2. After each module is inserted, power on the module for initialization and start the self-diagnostic program. During the self-diagnostic program, obtain the status parameters and ID identification code of each module, and mainly detect the voltage, temperature and operating status of each module. S3. If all the statuses of each module are normal, the module identification code and status data are sent to the main control module. After receiving the data, the main control module verifies the type and status of each module and loads the corresponding driver or updates the module mapping table required by the module. At this time, each module in the device is ready. S4. If the inserted module is in an abnormal state, an alarm device such as an alarm light or buzzer will be used to indicate the abnormal status of the module and report the problematic module. At this time, the module will be tested, replaced, and reconnected for re-self-diagnosis testing.

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