Agricultural scene-based inspection robot and control method

Abstract

The invention discloses an inspection robot based on an agricultural scene and a control method. The inspection robot comprises a robot body, and a path planning and navigation control module, a data acquisition and processing control module, a task execution and cooperation control module and a remote monitoring and management control module which are configured on the robot body; the robot body is provided with a mechanical arm, the data acquisition and processing control module is connected with the path planning and navigation control module, the task execution and cooperation control module is connected with the path planning and navigation control module, and the remote monitoring and management control module is in communication connection with the remote monitoring center.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of agricultural technology, and relates to a robot for inspection based on an agricultural scene and a control method. BACKGROUND

[0002] With the intensification of global agricultural labor shortage and resource constraints, traditional manual inspection methods have been difficult to meet the needs of modern agriculture for efficiency and accuracy. Inspection robots, which can monitor pests and diseases, assess crop growth, and collect environmental parameters, have become the core equipment for the intelligent transformation of agriculture. However, due to the complexity and dynamics of agricultural scenes, uneven crop distribution, and other issues, traditional agricultural inspection has low efficiency, high labor costs, and poor environmental adaptability. SUMMARY

[0003] The present application is to overcome at least one deficiency of the prior art, and provides a robot for inspection based on an agricultural scene and a control method.

[0004] To achieve the above-mentioned purpose, the present application adopts the following technical solution: a robot for inspection based on an agricultural scene, comprising a robot body and a path planning and navigation control module, a data acquisition and processing control module, a task execution and cooperation control module, and a remote monitoring and management control module configured on the robot body; the robot body is configured with a mechanical arm, the data acquisition and processing control module is connected with the path planning and navigation control module, the task execution and cooperation control module is connected with the path planning and navigation control module, and the remote monitoring and management control module is communicatively connected with a remote monitoring center.

[0005] Further, the path planning and navigation control module comprises a global path planning module, a local path planning module, and a navigation control module, the global path planning module constructs an environment map and sets a driving route of the robot for inspection.

[0006] Further, the local path planning module adjusts and optimizes the local path according to real-time perceived environmental information.

[0007] Further, the navigation control module controls the motion direction and speed of the robot for inspection according to the planned path.

[0008] Further, the data acquisition and processing control module comprises a sensor data acquisition module and a data processing and analysis module; the sensor data acquisition module integrates multiple sensors to collect farmland environment and crop growth data.

[0009] Further, the data processing and analysis module performs real-time processing and analysis on the collected data to extract specific information.

[0010] Further, the task execution and cooperation control module comprises an inspection task execution module and a multi-robot cooperation module; the inspection task execution module controls the robot to complete corresponding actions and operations according to the preset inspection task, and monitors and feeds back the task execution in real time.

[0011] Further, the multi-robot cooperation module controls multiple inspection robots to work cooperatively, and information sharing and task allocation are performed through the establishment of a communication network among the robots.

[0012] The control method of the inspection robot based on the agricultural scene comprises the following steps: Step 1: The sensor data acquisition module acquires the farmland environment, constructs an environment map, and generates a global inspection path according to the set target point; Step 2: The sensor data acquisition module perceives the environmental information in real time, and adjusts and optimizes the local path; Step 3: The robot runs according to the global inspection path, and adjusts the running direction of the robot according to the local path; Step 4: The robot executes corresponding actions and operations at the target point.

[0013] Further, the method for constructing the environment map in step 1 is as follows: Step 11: The point cloud data and image data collected by the data acquisition and processing control module are delivered to the global path planning module; Step 12: The SLAM framework is used to construct the map in real time; Step 13: The collected point cloud data and image data are preprocessed; Step 14: The map is dynamically updated in combination with the new data collected by the inspection robot.

[0014] In summary, the present application has the following advantages: The present application realizes path planning and adaptive navigation in a complex agricultural environment based on the path planning and navigation control module, the data acquisition and processing control module, and the task execution and cooperation control module, greatly improves the environmental adaptability and agricultural inspection efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 It is a schematic diagram of the exoskeleton waist module of the present application. DETAILED DESCRIPTION

[0016] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, unless otherwise specified, the following embodiments and features described therein can be combined with each other. Example

[0017] like Figure 1 As shown, the inspection robot based on agricultural scenarios includes a robot body and a path planning and navigation control module, a data acquisition and processing control module, a task execution and collaboration control module, and a remote monitoring and management control module configured on the robot body. The robot body is equipped with a robotic arm. The data acquisition and processing control module is connected to the path planning and navigation control module, the task execution and collaboration control module is connected to the path planning and navigation control module, and the remote monitoring and management control module is connected to the remote monitoring center.

[0018] The path planning and navigation control module includes a global path planning module, a local path planning module, and a navigation control module. The global path planning module constructs an environmental map and sets the travel route of the inspection robot: before the inspection task begins, it uses the geographic information system (GIS) data of the farmland and combines it with the environmental data collected by the data acquisition and processing control module to construct an environmental map. The path planning algorithm is used to plan the optimal or near-optimal inspection path based on the constructed environmental map and the set target points, so that the robot can efficiently cover the farmland area while avoiding obstacles. The local path planning module adjusts and optimizes the local path based on real-time perceived environmental information: during the inspection process, the local path is adjusted and optimized based on real-time perceived environmental information to avoid obstacles, adapt to terrain changes, etc. For example, when encountering an obstacle, the robot can detect the position and size of the obstacle through sensors, and then use the local path planning algorithm to replan the local path around the obstacle, ensuring that the robot can continue to travel along the predetermined inspection area; The navigation control module controls the movement direction and speed of the inspection robot according to the planned path, enabling it to travel accurately along the path.

[0019] The data acquisition and processing control module includes a sensor data acquisition module and a data processing and analysis module. The sensor data acquisition module integrates multiple sensors to collect farmland environment and crop growth data. The sensor data acquisition module includes a camera, a laser radar, a weather sensor, a soil sensor, etc. By controlling the sampling frequency, collection time and other parameters of the sensor data acquisition module, sufficient accurate and real-time data can be obtained.

[0020] The data processing and analysis module processes and analyzes the collected data in real time, extracts specific information, including the growth state of crops, pest and disease conditions, soil moisture, etc. Real-time processing includes classification, identification and modeling, providing a basis for subsequent decision-making and control.

[0021] The task execution and cooperation control module includes a patrol task execution module and a multi-robot cooperation module. The patrol task execution module controls the robot to complete corresponding actions and operations such as taking pictures, recording videos, and collecting samples according to the preset patrol task. At the same time, the task execution is monitored and fed back in real time to ensure that the task can be completed smoothly.

[0022] The multi-robot cooperation module controls multiple patrol robots to work cooperatively. By establishing a communication network between the robots, information sharing and task allocation are realized, improving the efficiency and coverage of the patrol.

[0023] The remote monitoring and management control module uses wireless communication technology such as 4G, 5G, Wi-Fi, etc. to realize data transmission and communication between the patrol robot and the remote monitoring center. The staff of the monitoring center can remotely control the running state of the robot by sending instructions such as starting, stopping, adjusting parameters, etc. At the same time, they can also receive the data and image information sent back by the robot in real time, and remotely monitor and manage the patrol process.

[0024] The patrol robot control method based on agricultural scenarios includes the following steps: Step 1: The sensor data acquisition module collects the farmland environment, constructs an environment map, and generates a global patrol path according to the set target point; Step 2: The sensor data acquisition module senses environmental information in real time and adjusts and optimizes the local path; Step 3: The robot runs according to the global patrol path and adjusts the running direction of the robot according to the local path; Step 4: The robot performs corresponding actions and operations at the target point.

[0025] The method for constructing the environment map in step 1 is: Step 11: The point cloud data and image data collected by the data acquisition and processing control module are transmitted to the global path planning module; Step 12: Real-time construction of the map using the SLAM framework; Step 13: Preprocessing of the collected point cloud data and image data; Step 14: Dynamic updating of the map in combination with new data collected by the inspection robot.

[0026] The steps for adjusting and optimizing the local path are as follows: Step 21: Real-time collection of environmental point cloud data, conversion of the point cloud data into an occupancy grid map, and perception of the location and dynamic changes of obstacles; Step 22: Real-time adjustment of the path and local recovery using the A* algorithm; Step 23: Adjustment of the robot speed according to the distance and speed of the obstacle to ensure the path adjustment response when moving quickly.

[0027] The method for real-time adjustment of the path is as follows: Set the target point as a source of attraction, which generates an attractive force on the robot; regard the obstacle as a source of repulsion, which generates a repulsive force on the robot, and calculate the attractive force and the repulsive force: The attractive force is proportional to the distance from the robot to the target point, and the formula is ; wherein is the attractive force gain coefficient, is the location of the target point, is the location of the robot; The repulsive force is inversely proportional to the distance from the robot to the obstacle, and the formula is

[0028] wherein is the repulsive force gain coefficient, d is the distance from the robot to the obstacle, and d0 is the range of the repulsive force; The resultant force is the vector sum of the attractive force and the repulsive force, and the formula is ; According to the direction and size of the resultant force, the position of the robot is updated; during the movement of the robot, the environmental changes are perceived in real time, and the size and direction of the attractive force and the repulsive force are dynamically adjusted to adapt to the changes in the environment.

[0029] Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor should belong to the scope of protection of the present application.

Claims

1. An agricultural scene based inspection robot, characterized in that: The robot body is provided with a mechanical arm, the data acquisition and processing control module is connected with the path planning and navigation control module, the task execution and cooperation control module is connected with the path planning and navigation control module, and the remote monitoring and management control module is in communication connection with the remote monitoring center.

2. The agricultural scene based inspection robot of claim 1, wherein: The path planning and navigation control module includes a global path planning module, a local path planning module and a navigation control module.

3. The agricultural scene based inspection robot of claim 2, wherein: The local path planning module adjusts and optimizes the local path according to the real-time perceived environmental information.

4. The agricultural scene based inspection robot of claim 2, wherein: The navigation control module controls the movement direction and speed of the inspection robot according to the planned path.

5. The agricultural scene based inspection robot of claim 1, wherein: The data acquisition and processing control module includes a sensor data acquisition module and a data processing and analysis module.

6. The agricultural scene based inspection robot of claim 5, wherein: The data processing and analysis module processes and analyzes the collected data in real time and extracts specific information.

7. The agriculture-scene-based inspection robot according to claim 1, characterized in that: The task execution and cooperation control module includes an inspection task execution module and a multi-robot cooperation module. The inspection task execution module controls the robot to complete corresponding actions and operations according to the preset inspection task, and monitors and feeds back the task execution in real time.

8. The agricultural scene based inspection robot of claim 7, wherein: The multi-robot cooperation module controls multiple inspection robots to work cooperatively, and shares information and allocates tasks through the establishment of a communication network between the robots.

9. A method for controlling an agricultural scene-based inspection robot, the method comprising: The method comprises the following steps: Step 1: The sensor data acquisition module acquires the farmland environment, constructs an environmental map, and generates a global inspection path according to the set target point; Step 2: The sensor data acquisition module adjusts and optimizes the local path according to the real-time perceived environmental information; Step 3: The robot runs according to the global inspection path and adjusts the running direction of the robot according to the local path; Step 4: The robot executes corresponding actions and operations at the target point. 10.The control method of the agricultural scene-based inspection robot according to claim 9, characterized in that: The method for constructing the environmental map in step 1 is: Step 11: The point cloud data and image data collected by the data acquisition and processing control module are delivered to the global path planning module; Step 12: The SLAM framework is used to construct the map in real time; Step 13: The collected point cloud data and image data are preprocessed; Step 14: The map is dynamically updated in combination with the new data collected by the inspection robot.

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