An automatic breaking operation method and system for an excavator and an excavator

Abstract

The application discloses an automatic crushing operation method and system for an excavator and the excavator, and belongs to the technical field of excavator control, and comprises the following steps: a target identification step, in which a camera module is used to identify a crushing target and acquire position information of the crushing target; a path planning step, in which a domain controller is used to combine the position information of the crushing target, a global map of an environment and environment data of the environment around the excavator, plan a path and generate a walking instruction; and an action control step, in which a whole-machine controller is used to control the excavator to walk and crush according to the walking instruction, so that the crushing operation is realized. The automatic crushing operation method and system for the excavator and the excavator can realize automatic identification, accurate positioning and path planning of the crushing target, and thus improve the automation level, operation accuracy and safety of the crushing operation.

Description

Technical Field

[0001] This invention relates to the field of excavator control technology, specifically to an automatic crushing operation method, system, and excavator for excavators. Background Technology

[0002] In engineering fields such as building demolition and mining, excavators are key equipment for performing crushing operations. However, traditional crushing operations rely heavily on manual operation, which has inherent drawbacks such as high operational difficulty, low efficiency, and high safety risks. Furthermore, existing automated excavator solutions still have significant shortcomings in practical applications.

[0003] First, in terms of target recognition and positioning, the reliance on a single sensor can easily lead to inaccurate recognition and positioning loss under complex or harsh working conditions (such as poor lighting or dust). There is a lack of effective multi-source information fusion and redundancy verification mechanisms. Second, in terms of path planning and movement control, the planning algorithm fails to fully consider the dynamic characteristics of heavy equipment such as excavators in unstructured terrain, such as slippage and bumps, resulting in a large deviation between the planned path and the actual trajectory. Furthermore, the lack of real-time, closed-loop trajectory tracking and correction capabilities makes it impossible for the equipment to accurately reach the target location. Finally, manual close-range operation of the breaker still faces dangers such as flying rocks and collapses, and operator fatigue can also lead to a decrease in work accuracy and efficiency. Summary of the Invention In view of the problems existing in the prior art, the present invention provides an automatic crushing operation method, system and excavator for excavators, which can realize automatic identification, precise positioning and path planning of crushing targets, thereby improving the automation level, operation accuracy and safety of crushing operations.

[0004] The technical solution of the present invention is as follows: In a first aspect of the invention, an automated crushing operation method for an excavator is provided, comprising: The target recognition step involves using a camera module to identify the broken target and obtain its location information. The path planning step involves using a domain controller to combine the location information of the crushing target, the global map of the surrounding environment, and the environmental data around the excavator to plan the path and generate travel instructions. The motion control steps involve the machine controller controlling the excavator to perform walking and crushing operations according to the walking instructions, thereby achieving the crushing operation. In some embodiments of the present invention, the target recognition step specifically involves training a target detection algorithm model on a broken target, deploying the trained target detection algorithm model to a camera module, and after the camera module recognizes the broken target, sending the position signal of the target object to the domain controller. In some embodiments of the present invention, the path planning step specifically involves detecting environmental data around the excavator using a lidar module, constructing a two-dimensional grid map based on the environmental data, wherein the grid map includes occupied areas, unknown areas, and non-occupied areas, and the domain controller using a path planning algorithm to perform path planning based on the global map and the two-dimensional grid map and generate walking instructions. In some embodiments of the present invention, the motion control steps specifically involve the following steps: during the process of the machine controller controlling the excavator to move according to the walking command, the machine controller acquires the excavator's acceleration and angular velocity in real time through the attitude sensor, integrates the data to obtain trajectory data, performs feature association and fusion with the binocular camera, uses a PID-based motion control algorithm to track the trajectory and achieve motion correction, and controls the excavator to move. When the camera module and the lidar unit locate the position of the crushing target, the machine controller controls the excavator to perform crushing operations. In some embodiments of the present invention, the T-BOX module enables remote monitoring and control of the excavator. In a second aspect of the invention, an automatic crushing operation system for an excavator is provided, comprising: The camera module is used to identify broken targets and obtain their location information; The lidar unit is used to detect environmental data around the excavator. The domain controller is used to combine the location information of the crushing target, the global map of the environment, and the environmental data of the surrounding environment of the excavator to perform path planning and generate walking instructions. Attitude sensors are used to acquire the excavator's acceleration and angular velocity in real time; The machine controller receives travel commands from the domain controller and controls the excavator to perform travel and crushing operations to achieve crushing work. The execution module, including the main valve, main pump, and engine controller, is used to perform the crushing operation. In some embodiments of the present invention, the domain controller is configured to detect environmental data around the excavator using a lidar unit, construct a two-dimensional grid map based on the environmental data, and perform path planning based on the global map and the two-dimensional grid map using a path planning algorithm to generate travel instructions. The grid map includes occupied areas, unknown areas, and non-occupied areas. In some embodiments of the present invention, the machine controller is configured to control the excavator to move according to the walking command. The machine controller acquires the excavator's acceleration and angular velocity in real time through the attitude sensor, integrates them to obtain trajectory data, and performs feature association and fusion with the camera module. A PID-based motion control algorithm is used for trajectory tracking and motion correction. When the camera module and the lidar unit locate the position of the crushing target, the machine controller controls the excavator to perform crushing operations. In some embodiments of the present invention, a TBOX module is also included for remote monitoring and control. In a third aspect of the invention, an excavator is provided, the excavator including a memory and a processor; the memory is used to store a computer program; the processor is used to implement the above-described automatic crushing operation method for the excavator when the computer program is executed.

[0005] One or more technical solutions of the present invention have the following beneficial effects: The present invention provides an automatic crushing operation method, system, and excavator for excavators. Through the fusion of multi-source information from a camera module, a lidar module, and an attitude sensor, it achieves stable identification and precise positioning of the crushing target under complex working conditions. The domain controller performs intelligent planning based on a two-dimensional grid map and the A* algorithm, and the whole machine controller uses a PID motion control algorithm with compensation term for real-time closed-loop trajectory tracking and correction, ensuring that the excavator can accurately reach the target in unstructured terrain. Remote monitoring and control are realized through the TBOX module, freeing operators from dangerous and heavy on-site operations, significantly improving operational safety and automation level, and achieving precise, efficient, and safe crushing operations. Attached Figure Description

[0006] Figure 1 This is a flowchart illustrating the working framework of an automatic crushing operation method for an excavator provided in Embodiment 1 of the present invention. Figure 2 This is a working framework diagram of an automatic crushing operation system for an excavator provided in Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of a two-dimensional grid map provided in Embodiment 1 of the present invention. Detailed Implementation

[0007] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0008] Example 1 In a typical embodiment of the present invention, an automatic crushing operation method for an excavator is provided, comprising: The target recognition step involves using a camera module to identify the broken target and obtain its location information. The path planning step involves using a domain controller to combine the location information of the crushing target, the global map of the surrounding environment, and the environmental data around the excavator to plan the path and generate travel instructions. The motion control steps involve the machine controller controlling the excavator to perform walking and crushing operations according to the walking instructions, thereby achieving the crushing operation. It has changed the traditional operation mode that relies on manual operation. Through automated sequence control, it has significantly reduced the labor intensity and skill requirements of operators, and effectively avoided inefficiency and safety accidents caused by human fatigue or operation errors. It enables excavators to autonomously complete all actions from target discovery to crushing, greatly improving the overall efficiency and continuity of operation.

[0009] In this embodiment, the camera module is set as a binocular camera, and the target to be broken is the stone that needs to be broken.

[0010] The target recognition step specifically involves training a target detection algorithm model on the broken target, deploying the trained target detection algorithm model to the camera module, and sending the target's position signal to the domain controller after the camera module identifies the broken target.

[0011] In this embodiment, the target detection algorithm model adopts the YOLO series model. By using the target detection algorithm model, it can adapt to broken targets of different shapes and sizes, avoiding the problems of ambient light and shadow interference that are easily affected by traditional single threshold detection methods. The trained target detection algorithm model is deployed to the camera module, realizing edge computing, reducing data transmission latency, ensuring the real-time response of broken target recognition, and providing accurate and timely input signals for subsequent path planning and motion control.

[0012] The path planning step specifically involves detecting environmental data around the excavator using a lidar module, constructing a two-dimensional grid map based on the environmental data, the grid map including occupied areas, unknown areas, and non-occupied areas, and then using a path planning algorithm to plan the path and generate travel instructions based on the global map and the two-dimensional grid map. LiDAR can actively and accurately detect three-dimensional information of the surrounding environment, unaffected by lighting conditions, and can still work reliably, especially in harsh working conditions filled with dust. By constructing a two-dimensional grid map containing occupied, unknown, and unoccupied areas, the domain controller can transform the complex physical environment into a computer-processable digital model, clearly identifying walkable and obstacle areas. Based on this, path planning can be performed to automatically avoid obstacles and generate safe and efficient travel routes, thereby significantly improving the intelligence and safety of excavators' autonomous movement in complex and unstructured construction sites.

[0013] Specifically: Step 1: Obtain a global map of the region where the vehicle is located in advance; Step 2: Based on the binocular camera function, the target's (x, y, z) can be determined, where x and y are the relative coordinates of the target position from the vehicle's position, and z is the relative distance; Step 3: The lidar detects the environment around the vehicle to identify whether there are obstacles in the area; Step 4: The domain controller divides the environment into a two-dimensional grid map based on the LiDAR results. This two-dimensional grid map includes three scenarios: occupied, unknown, and unoccupied. Figure 3 As shown; Step 5: The domain controller performs path planning based on the global map and the areas defined in Step 4. Based on the working conditions of the excavator, the A* algorithm is used for path planning, with the formula: f(x) = g(x) + h(x); Where h(x) is the estimated cost; Step 6: The domain controller sends the travel command to the vehicle controller.

[0014] The specific motion control steps are as follows: during the process of the whole machine controller controlling the excavator to move according to the walking command, the whole machine controller obtains the acceleration and angular velocity of the excavator in real time through the attitude sensor, integrates them to obtain trajectory data, and performs feature association and fusion with the binocular camera. The PID-based motion control algorithm is used to track the trajectory and realize motion correction to control the excavator to move. When the camera module and the lidar unit locate the position of the crushing target, the whole machine controller controls the excavator to perform crushing operation.

[0015] By measuring the excavator's acceleration and angular velocity in real time using attitude sensors and obtaining trajectory data through integration, the system provides internal motion perception capabilities independent of visual signals. This data is then fused with feature-related data from the external environment perception data obtained from the binocular cameras, forming a complementary redundancy verification mechanism. Even when the data quality from the binocular cameras deteriorates due to road bumps, slippage, or reduced visibility, the system can still maintain reliable positioning and trajectory tracking using attitude sensor data. A closed-loop control algorithm with added compensation terms is employed to dynamically eliminate trajectory deviations during travel, ensuring the excavator can accurately and smoothly travel along the planned path to the target point. This overcomes the problems of deviation and slippage that easily occur when heavy equipment travels on rough terrain, ultimately achieving high-precision point arrival and laying the foundation for subsequent precision crushing.

[0016] Specifically: Step 1: The vehicle controller receives the travel command from the domain controller. The vehicle controller controls the excavator to open the left and right travel main valves and simultaneously controls the output of the main pump solenoid valve to achieve travel. Step 2: After the excavator moves, the tilt angle sensor will transmit the acceleration a and angular velocity w. After integration, the trajectory of the whole vehicle is obtained. Then, feature association and fusion are performed with the binocular camera to supplement the amount of data collected by the binocular camera when encountering road bumps, slippage, etc. Step 3: PID-based motion control is used for trajectory tracking and correction. Since PID control is based on the difference between speed and angle, there may be a problem of slow movement when the vehicle approaches the target. Therefore, a compensation term v is added to the original formula. ref and w ref Although PID control has a time lag, its application is suitable for the low operating speed of the excavator. The formula is: ; ; ; ; V(t) represents the velocity at the current moment; K p K i 、 K d These are the coefficients for PID control; X represents the current position along the x-axis; x ref Represents the target position along the x-axis; y represents the current position along the y-axis; ref Represents the target position along the y-axis; V refIt is a speed correction; W(t) represents the angular velocity at the current moment; w ref It corrects the angular velocity; Represents the current perspective - the target perspective; The T-BOX module enables remote monitoring and control of excavators. With the T-BOX module, operators can monitor the excavator's operating status, location, and surrounding environment in real time from a remote monitoring center, without being physically present at hazardous work sites such as those prone to collapse or with the risk of falling rocks. It also allows for remote intervention in emergencies, greatly ensuring personnel safety and making it particularly suitable for high-risk work environments. In a second aspect of the invention, an automatic crushing operation system for an excavator is provided, comprising: The camera module is used to identify broken targets and obtain their location information; The lidar unit is used to detect environmental data around the excavator. The domain controller is used to combine the location information of the crushing target, the global map of the environment, and the environmental data of the surrounding environment of the excavator to perform path planning and generate walking instructions. Attitude sensors are used to acquire the excavator's acceleration and angular velocity in real time; The machine controller receives travel commands from the domain controller and controls the excavator to perform travel and crushing operations to achieve crushing work. The execution module, including the main valve, main pump, and engine controller, is used to perform the crushing operation. The domain controller is configured to detect environmental data around the excavator using a lidar unit. The domain controller constructs a two-dimensional grid map based on the environmental data and uses a path planning algorithm to plan a path and generate travel instructions based on the global map and the two-dimensional grid map. The grid map includes occupied areas, unknown areas, and non-occupied areas. The machine controller is configured to control the excavator to move according to the walking command. The machine controller acquires the excavator's acceleration and angular velocity in real time through the attitude sensor, integrates them to obtain trajectory data, and performs feature association and fusion with the camera module. A PID-based motion control algorithm is used for trajectory tracking and motion correction. When the camera module and the lidar unit locate the position of the crushing target, the machine controller controls the excavator to perform crushing operations. It also includes a TBOX module for remote monitoring and control. In a third aspect of the invention, an excavator is provided, the excavator including a memory and a processor; the memory is used to store a computer program; the processor is used to implement the above-described automatic crushing operation method for the excavator when the computer program is executed.

[0017] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. An automatic crushing operation method for excavators, characterized in that, include: The target recognition step involves using a camera module to identify the broken target and obtain its location information. The path planning step involves using a domain controller to combine the location information of the crushing target, the global map of the surrounding environment, and the environmental data around the excavator to plan the path and generate travel instructions. The motion control steps involve controlling the excavator to perform walking and crushing operations through the overall machine controller based on the walking instructions, thereby achieving the crushing operation. The target recognition step specifically involves training a target detection algorithm model on the broken target, deploying the trained target detection algorithm model to the camera module, and sending the position signal of the target to the domain controller after the camera module recognizes the broken target. The path planning step is specifically as follows: the LiDAR module detects the environmental data around the excavator's surroundings; the domain controller constructs a two-dimensional grid map based on the environmental data; the grid map includes occupied areas, unknown areas, and non-occupied areas; and the domain controller uses a path planning algorithm to perform path planning based on the global map and the two-dimensional grid map and generates walking instructions. The specific motion control steps are as follows: during the process of the whole machine controller controlling the excavator to move according to the walking command, the whole machine controller obtains the acceleration and angular velocity of the excavator in real time through the attitude sensor, integrates them to obtain trajectory data, and performs feature association and fusion with the camera module. The PID-based motion control algorithm is used to track the trajectory and realize motion correction to control the excavator to move. When the camera module and the lidar module locate the position of the crushing target, the whole machine controller controls the excavator to perform crushing operation. Remote monitoring and control of excavators can be achieved through the T-BOX module; The automated crushing operation method is specifically as follows: Step 1: Obtain a global map of the region where the vehicle is located in advance; Step 2: Based on the camera module's function, the target's (x, y, z) coordinates can be determined, where x, y, and z are the relative coordinates of the target's position from the vehicle's position. Step 3: The lidar detects the environment around the vehicle to identify whether there are obstacles in the area; Step 4: The domain controller divides the environment into a two-dimensional grid map based on the LiDAR results. The two-dimensional grid map includes three cases: occupied, unknown, and unoccupied. Step 5: The domain controller performs path planning based on the global map and the areas defined in Step 4. Based on the working conditions of the excavator, the A* algorithm is used for path planning, with the formula: f(x) = g(x) + h(x); Where h(x) is the estimated cost; Step 6: The domain controller sends the walking command to the whole machine controller.

2. A system for implementing the automatic crushing operation method for an excavator as described in claim 1, characterized in that, include: The camera module is used to identify broken targets and obtain their location information; Specifically, a target detection algorithm model is trained on the broken target, and the trained target detection algorithm model is deployed to the camera module. After the camera module identifies the broken target, it sends the position signal of the target to the domain controller. The lidar module is used to detect environmental data around the excavator. The domain controller is used to combine the location information of the broken target, the global map of the surrounding environment, and the environmental data of the excavator's surrounding environment to perform path planning and generate walking instructions. Specifically, the domain controller uses a lidar module to detect the environmental data of the excavator's surrounding environment, constructs a two-dimensional grid map based on the environmental data, and the grid map includes occupied areas, unknown areas and non-occupied areas. The domain controller uses a path planning algorithm to perform path planning based on the global map and the two-dimensional grid map and generate walking instructions. Attitude sensors are used to acquire the excavator's acceleration and angular velocity in real time; The machine controller receives travel commands from the domain controller and controls the excavator to perform travel and crushing operations to achieve crushing work. Specifically, during the process of the machine controller controlling the excavator to travel according to the travel commands, the machine controller acquires the excavator's acceleration and angular velocity in real time through attitude sensors, integrates them to obtain trajectory data, and performs feature association and fusion with the camera module. A PID-based motion control algorithm is used to track the trajectory and correct the motion to control the excavator to travel. When the camera module and the lidar module locate the position of the crushing target, the machine controller controls the excavator to perform crushing operations. The execution module, including the main valve, main pump, and engine controller, is used to perform the crushing operation; The T-BOX module enables remote monitoring and control of excavators.

3. An excavator, characterized in that, The excavator includes a memory and a processor; the memory is used to store a computer program; the processor is used to implement the automatic crushing operation method for the excavator as described in claim 1 when the computer program is executed.

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