Intelligent excavator bucket trajectory automatic control method and system
By deploying multi-sensor modules on the excavator, utilizing virtual construction scenario planning and real-time data analysis, trajectory compensation is generated to correct the bucket control trajectory, thus solving the problem of limited trajectory control performance of the excavator in complex environments and achieving higher control precision.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ZHENJIANG VOCATIONAL TECHN COLLEGE
- Filing Date
- 2024-03-28
- Publication Date
- 2026-07-21
AI Technical Summary
Existing excavator bucket trajectory control methods have poor environmental adaptability when facing complex and dynamic environments, resulting in limited trajectory control performance.
The system uses a multi-sensor module to acquire data in real time, plans the initial bucket control trajectory through a virtual construction scenario, and performs trajectory deviation analysis and compensation to correct the bucket control trajectory.
It improves the precision of excavator bucket trajectory control, enabling it to better adapt to complex and dynamic excavation environments.
Smart Images
Figure CN118065464B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of automation control, and in particular to an automatic control method and system for the bucket trajectory of an intelligent excavator. Background Technology
[0002] As the complexity of modern engineering construction continues to increase, the application requirements of excavators in various scenarios are also becoming increasingly diversified. Automatic control of the excavator bucket can significantly improve the excavator's operating efficiency, accuracy, and safety, reduce operational difficulty, and adapt to various complex and dynamic working environments, making related research particularly important. In existing technologies, excavator bucket trajectory control mainly adopts rule-based control methods. Since rule-based control methods control the bucket trajectory based on pre-set rules, adjusting and updating these rules is cumbersome when the environment changes, making it difficult to meet dynamically changing excavation needs.
[0003] Currently, the excavator bucket trajectory control suffers from poor environmental adaptability, which in turn limits the performance of the trajectory control. Summary of the Invention
[0004] This application provides an intelligent excavator bucket trajectory automatic control method and system. It employs multi-sensor modules, utilizes virtual construction scenarios to plan the initial bucket control trajectory, acquires multi-sensor data in real time, performs trajectory deviation analysis, generates trajectory compensation, and corrects the bucket control trajectory. These techniques achieve the technical effect of better adapting to various complex and dynamic excavation environments, thereby improving the accuracy of excavator bucket trajectory control.
[0005] This application provides an automatic control method for the bucket trajectory of an intelligent excavator, including:
[0006] Based on the structural and functional information of the target excavator, a multi-sensor module is deployed.
[0007] Read the target task and, based on the target task, obtain basic data of the work area to construct a virtual construction scenario;
[0008] Based on the target operation task and the virtual construction scenario, plan the initial bucket control trajectory;
[0009] The target operation task is executed with reference to the initial bucket control trajectory, and multi-dimensional real-time sensor data is acquired through the multi-sensor module.
[0010] Based on the aforementioned multi-source real-time sensor data, trajectory deviation analysis is performed, and trajectory compensation is generated according to the trajectory deviation results.
[0011] The trajectory compensation is used to correct and compensate the initial bucket control trajectory, thereby generating a corrected bucket control trajectory.
[0012] The bucket trajectory of the intelligent excavator is controlled by correcting the bucket control trajectory.
[0013] In one possible implementation, based on the structural and functional information of the target excavator, a multi-sensor module is deployed to perform the following processing:
[0014] Obtain structural and performance information of the target excavator;
[0015] Based on the structural and functional information, a sensing requirement analysis is performed to obtain the sensing requirements of the target bucket.
[0016] Based on the target bucket sensing requirements and the structural information, sensing nodes are extracted to obtain multiple key sensing nodes;
[0017] For the multiple key sensing nodes, a multi-sensor module is deployed in accordance with the sensing requirements of the target bucket.
[0018] In one possible implementation, the target task is read, and based on the target task, basic data of the work area is obtained, a virtual construction scene is constructed, and the following processing is performed:
[0019] Interactively obtain the target task, which includes task type, task size, and task requirements data;
[0020] Based on the target task, basic data of the work area is obtained, including terrain data, geological data, environmental data, and obstacle data.
[0021] Using the basic data of the work area, the virtual construction scene is constructed through three-dimensional simulation technology.
[0022] In a possible implementation, based on the target task and the virtual construction scenario, an initial bucket control trajectory is planned, and the following processing is performed:
[0023] Based on the target task, the target task type is obtained, which includes excavation, loading, and leveling operations;
[0024] Based on the target task type, determine the target task requirements;
[0025] Using the virtual construction scenario and referring to the target operation requirements, a construction operation simulation plan is performed to obtain the initial bucket control trajectory, which includes multiple segments of trajectory.
[0026] In possible implementations, the following processing is performed:
[0027] Based on the initial bucket control trajectory, multiple sets of bucket control parameters of the multi-segment sub-trajectory are obtained, including bucket movement speed, acceleration, digging force and bucket attitude angle.
[0028] Based on the multiple sets of bucket control parameters, the operation efficiency, operation accuracy, and mechanical safety are evaluated to obtain the control evaluation results;
[0029] Based on the control evaluation results, the initial bucket control trajectory is optimized and adjusted.
[0030] In possible implementations, the following processing is performed:
[0031] Based on the control evaluation results, multiple sub-trajectory parameters to be adjusted are identified and obtained.
[0032] Based on the multiple sub-trajectory parameters to be adjusted, and by referring to the parameter adjustment step size, multiple sub-trajectory parameter adjustment schemes are obtained.
[0033] For the multiple sub-trajectory parameter adjustment schemes, the efficiency, accuracy and safety of the schemes are evaluated, and the optimal adjustment scheme is obtained based on the evaluation results to optimize the initial bucket control trajectory.
[0034] In one possible implementation, based on the aforementioned multi-source real-time sensor data, trajectory deviation analysis is performed, and trajectory compensation is generated according to the trajectory deviation results, followed by the following processing:
[0035] Based on the aforementioned multi-source real-time sensor data, combined with the initial bucket control trajectory, standard sub-trajectory operation information is obtained;
[0036] Based on the standard sub-trajectory operation information, a trajectory deviation analysis is performed with the multi-dimensional real-time sensor data to obtain trajectory deviation results, including position deviation, attitude deviation and time deviation.
[0037] Based on the trajectory deviation result, the trajectory compensation is generated.
[0038] This application also provides an automatic control system for the trajectory of an intelligent excavator bucket, including:
[0039] A multi-sensor module deployment module is used to deploy multi-sensor modules based on the structural and functional information of the target excavator.
[0040] A virtual construction scene construction module is used to read the target work task and, based on the target work task, obtain basic data of the work area to construct a virtual construction scene.
[0041] An initial bucket control trajectory planning module is used to plan the initial bucket control trajectory based on the target operation task and the virtual construction scenario.
[0042] The target operation task execution module is used to execute the target operation task with reference to the initial bucket control trajectory, and to acquire multi-dimensional real-time sensor data through the multi-sensor module.
[0043] The trajectory deviation analysis module is used to perform trajectory deviation analysis based on the multi-source real-time sensor data, and generate trajectory compensation based on the trajectory deviation results.
[0044] The correction compensation module is used to correct and compensate the initial bucket control trajectory using the trajectory compensation, and generate a corrected bucket control trajectory.
[0045] A bucket trajectory control module is used to perform intelligent excavator bucket trajectory control by correcting the bucket control trajectory.
[0046] The proposed method and system for automatic control of excavator bucket trajectory in this application first deploys a multi-sensor module based on the structural and functional information of the target excavator. Then, it reads the target operation task and acquires basic data of the operation area to construct a virtual construction scene, plans an initial bucket control trajectory, and executes the target operation task with reference to the initial bucket control trajectory. During task execution, it acquires multi-sensor real-time data through the multi-sensor module, performs trajectory deviation analysis and compensation on the multi-sensor real-time data, generates a corrected bucket control trajectory, and performs bucket trajectory control. This achieves the technical effect of better adapting to various complex and dynamic excavation environments, thereby improving the accuracy of excavator bucket trajectory control. Attached Figure Description
[0047] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments of this disclosure will be briefly described below. Flowcharts are used in this application to illustrate the operations performed by the system according to the embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed precisely in sequence. Instead, various steps can be processed in reverse order or simultaneously as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from these processes.
[0048] Figure 1 A flowchart illustrating an automatic control method for the bucket trajectory of an intelligent excavator provided in this application embodiment;
[0049] Figure 2This is a schematic diagram of the structure of an automatic control system for the bucket trajectory of an intelligent excavator provided in an embodiment of this application. Detailed Implementation
[0050] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application.
[0051] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description of this application will be provided in conjunction with the accompanying drawings. The described embodiments should not be considered as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0052] In the following description, references to "some embodiments" describe a subset of all possible embodiments; however, it is understood that "some embodiments" may be the same or different subsets of all possible embodiments and may be combined with each other without conflict. The terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules not explicitly listed or inherent to such processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.
[0053] This application provides an embodiment of an automatic control method for the bucket trajectory of an intelligent excavator, such as... Figure 1 As shown, the method includes:
[0054] Step S100: Based on the structural and functional information of the target excavator, deploy a multi-sensor module. The target excavator is the one undergoing automatic bucket trajectory control; it is the object of study. After identifying the target excavator, its structural and functional information is collected by consulting the instruction manual or contacting the manufacturer. Structural information includes the specific dimensions, positions, and connection methods of each part of the excavator, reflecting its physical characteristics. Functional information includes the excavator's operating characteristics, performance parameters, and working modes, reflecting its behavior under different working conditions. Based on the analysis of structural and functional information, a multi-sensor module that meets the monitoring requirements is determined, including displacement sensors, angle sensors, pressure sensors, and temperature sensors, used to monitor the bucket's position, speed, and angle, as well as the excavator's operating status. Combining the excavator's structural and functional characteristics, the sensor's monitoring range, the excavator's workflow, and the operator's habits, the optimal installation location for the sensor module is determined and deployed. Through debugging, it is ensured that the multi-sensor module can accurately and in real-time collect data.
[0055] In one possible implementation, step S100 further includes step S110, acquiring the structural and performance information of the target excavator; and step S120, performing a sensing requirement analysis based on the structural and functional information to obtain the sensing requirements of the target bucket. Specifically, detailed structural information of the target excavator is collected by consulting technical documents, conducting on-site surveys, or using professional measuring tools. This includes the specific dimensions, positions, and connection methods of each part, such as the bucket, robotic arm, and engine. Based on the excavator's performance parameters, working modes, and operational characteristics, its behavior patterns and performance limitations under different working conditions are analyzed. The collected structural and performance information is integrated to form a complete database of excavator structural and performance information. Based on this database, the parameters and key states that need to be monitored during excavator operation are analyzed, such as the bucket's position, speed, and angle, and the robotic arm's motion state. Based on the analysis results, the key sensing requirements of the target bucket are determined, such as position, angle, and torque. Then, step S130 is executed, extracting sensing nodes based on the target bucket's sensing requirements and the structural information to obtain multiple key sensing nodes. The sensing nodes are key nodes extracted from the bucket and related parts, capable of accurately monitoring the bucket's working status and environmental changes. After screening and optimization, several key sensing nodes are identified for step S140. For these key sensing nodes, and referring to the target bucket's sensing requirements, multi-sensor modules are deployed. Specifically, based on the monitoring requirements of the key sensing nodes, suitable multi-sensor modules are selected, such as displacement sensors, angle sensors, and pressure sensors. These modules are installed at the key sensing nodes on the target excavator according to the determined installation locations, and necessary adjustments are made to ensure accurate and real-time data acquisition. Steps S110 to S140 analyze sensing requirements based on the target excavator's structural and performance information, extract key sensing nodes, and deploy multi-sensor modules accordingly. This enables these modules to accurately monitor the target excavator's working status and environmental changes, achieving the technical effect of precise sensor module deployment.
[0056] Next, step S200 is executed to read the target work task and, based on the target work task, acquire basic data of the work area to construct a virtual construction scenario. Specifically, relevant information about the target work task is obtained from the task scheduling system, including the work type (such as excavation, loading, etc.), work area, and work requirements. Based on the target work task, basic data such as geographical information, environmental features, and obstacle distribution of the work area are acquired through GPS positioning, map data, or on-site surveys. Using the acquired basic data of the work area, combined with the structural and functional information of the excavator, a virtual construction scenario is constructed. This scenario can be a three-dimensional model used to simulate the real work environment.
[0057] In one possible implementation, step S200 further includes step S210, interactively acquiring a target work task, which includes task type, task scale, and task requirement data. The task type includes excavation, loading, etc.; the task scale includes excavation volume, work area, etc.; and the task requirements include accuracy, safety level, etc. After acquiring relevant information about the target work task from the task scheduling system, step S220 is executed, acquiring basic data of the work area based on the target work task. This basic data includes terrain data, geological data, environmental data, and obstacle data. Basic data of the work area is collected through on-site surveys, map data, or external materials. The collected data is integrated and processed to extract key information, such as terrain height, slope, texture, etc.; geological soil type, hardness, etc.; environmental weather conditions, wind speed, etc.; and the location, shape, and size of obstacles, etc. Then, step S230 is executed, using the basic data of the work area to construct the virtual construction scene through 3D simulation technology. In other words, using 3D simulation technology, a virtual construction scene is constructed based on the processed basic data of the work area. This includes 3D modeling of the terrain's undulations, the distribution of soil and rock in the geology, environmental weather conditions, and the shape and location of obstacles. During the construction process, the virtual construction scene is detailed and adjusted according to actual needs and working conditions, including adding lighting effects, shadow effects, and texture mapping to ensure a high degree of similarity to the actual working environment. This allows for better simulation and optimization of the intelligent excavator bucket trajectory control. Steps S210 to S230 acquire data on task type, task scale, task requirements, and basic data such as terrain, geology, environment, and obstacles, and use 3D simulation technology to create a highly realistic virtual construction scene. This makes the constructed scene closer to the actual working environment, thus achieving the technical effect of providing a more accurate and reliable foundation for trajectory control simulation.
[0058] After the virtual construction scenario is constructed, step S300 is executed: based on the target task and the virtual construction scenario, an initial bucket control trajectory is planned. That is, the specific requirements of the target task are analyzed, the task type, the characteristics of the work area, and the excavator's performance limitations are determined. Then, based on the virtual construction scenario and the target task, key parameters of the bucket control trajectory are determined, such as the starting point, ending point, path, and digging angle. Based on these key parameters, a preset control algorithm or optimization algorithm is used to generate the initial bucket control trajectory, which can be a mathematical model or a set of instructions.
[0059] In one possible implementation, step S300 further includes step S310, obtaining the target task type based on the target task, wherein the target task type includes excavation, loading, and leveling operations; and step S320, determining the target task requirements based on the target task type. 。 Specifically, based on the target task, the task type is identified by analyzing the task requirement data. The identified task types are then categorized and integrated, clarifying the requirements and characteristics of each type. Based on the analysis results, key parameters for each task type are determined. For example, for excavation, the depth, width, shape (e.g., trapezoid, rectangle), and volume of excavated earthwork must be determined; for loading, the location, type, and quantity of the loaded material must be determined; for leveling, the area, elevation, and flatness requirements of the leveling area must be determined. After the target task requirements are determined, step S330 is executed. Using the virtual construction scenario and referring to the target task requirements, a construction operation simulation plan is performed to obtain the initial bucket control trajectory, which includes multiple sub-trajectories. That is, the constructed virtual construction scenario is used for construction operation simulation planning. In the virtual construction scenario, based on the requirements of the target task, such as excavation volume, operating range, and accuracy requirements, a detailed construction plan is developed, including the specific actions of the excavator, the movement trajectory of the bucket during excavation, the operating steps of the excavator, and its interaction with the surrounding environment. Based on the simulation plan, an initial bucket control trajectory is generated. Since excavation operations involve multiple stages or sub-tasks, this initial bucket control trajectory includes multiple sub-trajectories, each corresponding to a specific excavation or operation stage. Steps S310 to S330 perform simulations according to the specific task type and requirements, ensuring that the obtained bucket control trajectory better matches the actual operation requirements. Furthermore, dividing the initial bucket control trajectory into multiple sub-trajectories improves the trajectory's flexibility and adaptability, thereby achieving the technical effects of improving the accuracy of the obtained initial bucket control trajectory and enhancing its flexibility and adaptability.
[0060] In another possible implementation, after obtaining the initial bucket control trajectory, step S300 further includes step S340, which, based on the initial bucket control trajectory, obtains multiple sets of bucket control parameters for the multi-segment sub-trajectories, including bucket speed, acceleration, digging force, and bucket attitude angle. Multiple sets of bucket control parameters for the multi-segment sub-trajectories are extracted from the initial bucket control trajectory data; these parameters reflect the bucket's motion state and operational requirements at different stages. The extracted bucket control parameters are organized and analyzed to determine the changing trends and interrelationships of each parameter, thereby analyzing the dynamic characteristics and behavior patterns of the bucket during operation. Then, step S350 is executed to evaluate the operating efficiency, operating accuracy, and mechanical safety based on the multiple sets of bucket control parameters, obtaining the control evaluation results. Specifically, the impact of parameters such as bucket movement speed and acceleration on work efficiency is analyzed. Work efficiency is evaluated by comparing actual work time with the theoretical optimal time. Work accuracy is evaluated by comparing the actual digging trajectory with the preset trajectory, based on parameters such as bucket attitude angle. The accuracy and consistency of the trajectory are assessed. The stress on the bucket at different stages is evaluated based on parameters such as digging force, ensuring mechanical safety and avoiding overload or potential mechanical damage within safe limits. A comprehensive control evaluation result is obtained by comprehensively considering the evaluation results of work efficiency, work accuracy, and mechanical safety. Step S360 is executed based on the obtained control evaluation result to optimize and adjust the initial bucket control trajectory. Analysis of the control evaluation result identifies aspects requiring optimization, including improving work efficiency, enhancing work accuracy, or improving mechanical safety. Based on the identified optimization needs, the bucket control parameters of the multi-segment sub-trajectory are adjusted, including bucket movement speed, acceleration, digging force, and bucket attitude angle, to achieve better work results. After obtaining the initial bucket control trajectory, steps S340 to S360 optimize and adjust the initial bucket control trajectory by evaluating work efficiency, work accuracy, and mechanical safety, thereby achieving the technical effect of improving work efficiency, accuracy, and safety.
[0061] In another possible implementation, step S360 further includes step S361, which identifies and obtains multiple sub-trajectory parameters to be adjusted based on the control evaluation results. That is, based on the control evaluation results, sub-trajectory parameters that need adjustment are identified. These parameters include the bucket's movement speed, acceleration, digging force, and bucket attitude angle, etc., which directly affect operational efficiency, accuracy, and safety. The impact of each sub-trajectory parameter to be adjusted on the operational effect is analyzed, and step S362 is executed. Based on the multiple sub-trajectory parameters to be adjusted, a reference parameter adjustment step size is used to obtain multiple sub-trajectory parameter adjustment schemes. Each scheme includes different parameter combinations and adjustment ranges. After obtaining the adjustment schemes, step S363 is executed to evaluate the efficiency, accuracy, and safety of the multiple sub-trajectory parameter adjustment schemes, and the optimal adjustment scheme is obtained based on the evaluation results to optimize the initial bucket control trajectory. Through comprehensive consideration of simulation analysis and actual data, a detailed evaluation of each sub-trajectory parameter adjustment scheme is conducted, including aspects such as operational efficiency, operational accuracy, and mechanical safety. Based on the evaluation results, an optimal sub-trajectory parameter adjustment scheme is selected. This scheme balances the requirements of operational efficiency, accuracy, and safety, achieving the best operational results. The initial bucket control trajectory is then optimized based on the optimal adjustment scheme. Steps S361 to S363, by obtaining multiple sub-trajectory parameter adjustment schemes and selecting the optimal one, reduce the potential risks of random optimization, enhance flexibility, and achieve the technical effect of improving the optimization effect of the initial bucket control trajectory.
[0062] Based on the generated initial bucket control trajectory, step S400 is executed, referring to the initial bucket control trajectory, to perform the target operation task, and multi-dimensional real-time sensor data is acquired through the multi-dimensional sensor module. At this time, according to the initial bucket control trajectory, the excavator is started to perform the target operation task. The control system automatically controls the excavator to perform the operation, or the operator operates it according to a preset trajectory. During the task execution, the real-time data acquisition function of the deployed multi-dimensional sensor module is used to monitor various status parameters of the target excavator during the operation process, such as bucket position, angle, speed, and the movement status of the robotic arm. The multi-dimensional sensor module transmits the real-time monitored data to the control system to obtain multi-dimensional real-time sensor data.
[0063] Step S500 is executed based on the obtained multi-source real-time sensor data. Trajectory deviation analysis is performed based on the multi-source real-time sensor data, and trajectory compensation is generated based on the trajectory deviation results. Specifically, the real-time data collected by the multi-source sensor module is processed and analyzed to extract parameters related to the bucket trajectory, such as bucket position, speed, and angle. By setting thresholds or using algorithms, the actual collected trajectory data is compared with the initial bucket control trajectory to perform deviation analysis and determine whether there is a deviation. If a deviation is found, corresponding trajectory compensation instructions are generated based on the degree and direction of the deviation using a preset algorithm or an optimized algorithm. These instructions include adjusting parameters such as bucket position, speed, and digging angle.
[0064] In one possible implementation, step S500 further includes step S510, which involves obtaining standard sub-trajectory operation information based on the multi-source real-time sensor data and the initial bucket control trajectory. The standard sub-trajectory operation information refers to information extracted from the multi-source real-time sensor data regarding the standard position, attitude, speed, and other parameters of the bucket at each sub-trajectory stage, based on the initial bucket control trajectory. This information reflects the standard trajectory that the bucket should follow during operation and is used to assess the degree of deviation from the actual operation trajectory. Therefore, after obtaining the standard sub-trajectory operation information, step S520 is executed, whereby trajectory deviation analysis is performed based on the standard sub-trajectory operation information and the multi-source real-time sensor data to obtain trajectory deviation results, including position deviation, attitude deviation, and time deviation. By comparing the standard sub-trajectory operation information with multi-source real-time sensor data, the deviation between the actual operation trajectory and the standard trajectory is evaluated. Based on the comparison results, trajectory deviation analysis is performed, analyzing the deviation in different aspects such as position, attitude, and time to determine the nature and degree of the deviation. Based on the trajectory deviation analysis, specific trajectory deviation results are obtained, including position deviation, attitude deviation, and time deviation. These results reflect the differences between the actual operation trajectory and the standard trajectory. Then, step S530 is executed to generate trajectory compensation based on the trajectory deviation results. Specifically, the causes of trajectory deviation are analyzed, including excavator operation problems, sensor errors, environmental interference, etc. Based on the trajectory deviation results and cause analysis, corresponding trajectory compensation strategies are generated, including adjusting bucket motion parameters and correcting operation steps, to reduce the deviation between the actual trajectory and the standard trajectory. According to the generated trajectory compensation strategy, the bucket control trajectory is adjusted to reduce deviation and improve operation accuracy. Steps S510 to S530 provide a reference standard for trajectory deviation analysis by acquiring standard sub-trajectory operation information. By comparing with the standard, subtle deviations can be detected, and compensation can be made for these deviations, achieving the technical effect of improving the accuracy of trajectory deviation analysis.
[0065] Based on the generated trajectory compensation command, step S600 is executed, using the trajectory compensation to correct the initial bucket control trajectory and generate a corrected bucket control trajectory; step S700, the intelligent excavator bucket trajectory control is performed using the corrected bucket control trajectory. That is, the trajectory compensation command generated in step S500 is used to correct the initial bucket control trajectory, including adjusting parameters such as the bucket's position, speed, and digging angle to eliminate trajectory deviations. Based on the initial trajectory after trajectory compensation, the bucket's movement path is recalculated or adjusted to generate a corrected bucket control trajectory, which more accurately reflects the actual operational requirements. Then, based on the corrected bucket control trajectory, the control system begins to execute intelligent excavator bucket trajectory control, including real-time adjustment of the excavator's operating status to ensure it operates according to the corrected trajectory. This embodiment employs a multi-sensor module deployment, utilizes a virtual construction scene to plan the initial bucket control trajectory, acquires multi-sensor data in real-time, performs trajectory deviation analysis, generates trajectory compensation, and corrects the bucket control trajectory, achieving a better adaptation to various complex and dynamic digging environments, thereby improving the accuracy of excavator bucket trajectory control.
[0066] In the above text, refer to Figure 1 A method for automatic control of the bucket trajectory of an intelligent excavator according to an embodiment of the present invention is described in detail. Next, reference will be made to... Figure 2 An intelligent excavator bucket trajectory automatic control system according to an embodiment of the present invention is described.
[0067] An intelligent excavator bucket trajectory automatic control system according to an embodiment of the present invention addresses the technical problem of poor environmental adaptability in existing excavator bucket trajectory control, which leads to limited performance of trajectory control. This system aims to better adapt to various complex and dynamic excavation environments, thereby improving the accuracy of excavator bucket trajectory control. The intelligent excavator bucket trajectory automatic control system includes: a multi-sensor module deployment module 10, a virtual construction scene construction module 20, an initial bucket control trajectory planning module 30, a target operation task execution module 40, a trajectory deviation analysis module 50, a correction and compensation module 60, and a bucket trajectory control module 70.
[0068] The multi-sensor module deployment module 10 is used to deploy multi-sensor modules based on the structural and functional information of the target excavator.
[0069] The virtual construction scene construction module 20 is used to read the target work task and, based on the target work task, obtain basic data of the work area to construct a virtual construction scene;
[0070] The initial bucket control trajectory planning module 30 is used to plan the initial bucket control trajectory based on the target operation task and the virtual construction scenario;
[0071] The target operation task execution module 40 is used to execute the target operation task with reference to the initial bucket control trajectory, and to acquire multi-dimensional real-time sensor data through the multi-dimensional sensor module;
[0072] The trajectory deviation analysis module 50 is used to perform trajectory deviation analysis based on the multi-source real-time sensor data, and generate trajectory compensation based on the trajectory deviation results;
[0073] The correction compensation module 60 is used to perform correction compensation on the initial bucket control trajectory using the trajectory compensation, and generate a corrected bucket control trajectory;
[0074] The bucket trajectory control module 70 is used to perform intelligent excavator bucket trajectory control by correcting the bucket control trajectory.
[0075] The specific configuration of the multi-sensor module deployment module 10 will be described in detail below. As mentioned above, based on the structural and functional information of the target excavator, a multi-sensor module is deployed. The multi-sensor module deployment module 10 may further include: a sensor requirement analysis unit for acquiring the structural and performance information of the target excavator, and performing sensor requirement analysis based on the structural and functional information to obtain the target bucket sensor requirements; and a sensor module deployment unit for extracting sensor nodes according to the target bucket sensor requirements and the structural information to obtain multiple key sensor nodes, and deploying the multi-sensor module for the multiple key sensor nodes, referring to the target bucket sensor requirements.
[0076] The specific configuration of the virtual construction scene construction module 20 will be described in detail below. As mentioned above, the virtual construction scene construction module 20 reads the target work task and, based on the target work task, obtains basic data of the work area to construct a virtual construction scene. The virtual construction scene construction module 20 may further include: a target work task acquisition unit for interactively acquiring the target work task, which includes task type, task scale, and task requirement data; a work area basic data acquisition unit for acquiring basic data of the work area based on the target work task, wherein the basic data of the work area includes terrain data, geological data, environmental data, and obstacle data; and a construction scene construction unit for using the basic data of the work area to construct the virtual construction scene through three-dimensional simulation technology.
[0077] The specific configuration of the initial bucket control trajectory planning module 30 will be described in detail below. As mentioned above, the initial bucket control trajectory is planned based on the target operation task and the virtual construction scenario. The initial bucket control trajectory planning module 30 may further include: a target operation task type acquisition unit for acquiring the target operation task type based on the target operation task, wherein the target operation task type includes excavation operation, loading operation, and leveling operation; a target operation task requirement determination unit for determining the target operation task requirement based on the target operation task type; and a simulation planning unit for performing construction operation simulation planning through the virtual construction scenario and referring to the target operation task requirement to obtain the initial bucket control trajectory, wherein the initial bucket control trajectory includes multiple sub-trajectories.
[0078] After obtaining the initial bucket control trajectory, the initial bucket control trajectory planning module 30 may further include: a multi-set bucket control parameter acquisition unit for acquiring multiple sets of bucket control parameters of the multi-segment sub-trajectory based on the initial bucket control trajectory, including acquiring bucket movement speed, acceleration, digging force, and bucket attitude angle; an evaluation unit for evaluating work efficiency, work accuracy, and mechanical safety based on the multiple sets of bucket control parameters, and obtaining control evaluation results; and an optimization and adjustment unit for optimizing and adjusting the initial bucket control trajectory based on the control evaluation results.
[0079] The initial bucket control trajectory is optimized and adjusted based on the control evaluation results. The optimization and adjustment unit may further include: a sub-trajectory parameter acquisition sub-unit for identifying and acquiring multiple sub-trajectory parameters to be adjusted based on the control evaluation results; a sub-trajectory parameter adjustment scheme acquisition sub-unit for obtaining multiple sub-trajectory parameter adjustment schemes by referring to parameter adjustment step sizes based on the multiple sub-trajectory parameters to be adjusted; and an evaluation and optimization sub-unit for evaluating the efficiency, accuracy, and safety of the multiple sub-trajectory parameter adjustment schemes, and obtaining the optimal adjustment scheme based on the evaluation results to optimize the initial bucket control trajectory.
[0080] The specific configuration of the trajectory deviation analysis module 50 will be described in detail below. As mentioned above, based on the multivariate real-time sensor data, trajectory deviation analysis is performed, and trajectory compensation is generated according to the trajectory deviation results. The trajectory deviation analysis module 50 may further include: a standard sub-trajectory operation information acquisition unit for acquiring standard sub-trajectory operation information based on the multivariate real-time sensor data and combined with the initial bucket control trajectory; and a trajectory deviation compensation unit for performing trajectory deviation analysis based on the standard sub-trajectory operation information and the multivariate real-time sensor data to obtain trajectory deviation results, including position deviation, attitude deviation, and time deviation, and generating the trajectory compensation based on the trajectory deviation results.
[0081] The intelligent excavator bucket trajectory automatic control system provided in this embodiment of the invention can execute the intelligent excavator bucket trajectory automatic control method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
[0082] Although this application makes various references to certain modules in the system according to the embodiments of this application, any number of different modules can be used and run on user terminals and / or servers. The various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention.
[0083] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.
Claims
1. A method for automatic control of the bucket trajectory of an intelligent excavator, characterized in that, The method includes: Based on the structural and functional information of the target excavator, a multi-sensor module is deployed. Read the target task and, based on the target task, obtain basic data of the work area to construct a virtual construction scenario; Based on the target operation task and the virtual construction scenario, plan the initial bucket control trajectory; The target operation task is executed with reference to the initial bucket control trajectory, and multi-dimensional real-time sensor data is acquired through the multi-sensor module. Based on the aforementioned multi-source real-time sensor data, trajectory deviation analysis is performed, and trajectory compensation is generated according to the trajectory deviation results. The trajectory compensation is used to correct and compensate the initial bucket control trajectory, thereby generating a corrected bucket control trajectory. Intelligent excavator bucket trajectory control is achieved through the aforementioned corrected bucket control trajectory. Simultaneously, based on the aforementioned multi-source real-time sensor data, trajectory deviation analysis is performed, and trajectory compensation is generated according to the trajectory deviation results, including: Based on the aforementioned multi-source real-time sensor data, combined with the initial bucket control trajectory, standard sub-trajectory operation information is obtained; Based on the standard sub-trajectory operation information, a trajectory deviation analysis is performed with the multi-dimensional real-time sensor data to obtain trajectory deviation results, including position deviation, attitude deviation and time deviation. Based on the trajectory deviation result, the trajectory compensation is generated.
2. The automatic control method for the bucket trajectory of an intelligent excavator as described in claim 1, characterized in that, Based on the structural and functional information of the target excavator, a multi-sensor module is deployed, including: Obtain structural and performance information of the target excavator; Based on the structural and functional information, a sensing requirement analysis is performed to obtain the sensing requirements of the target bucket. Based on the target bucket sensing requirements and the structural information, sensing nodes are extracted to obtain multiple key sensing nodes; For the multiple key sensing nodes, a multi-sensor module is deployed in accordance with the sensing requirements of the target bucket.
3. The method for automatic control of the bucket trajectory of an intelligent excavator as described in claim 1, characterized in that, Read the target work task, and based on the target work task, obtain basic data of the work area to construct a virtual construction scene, including: Interactively obtain the target task, which includes task type, task size, and task requirements data; Based on the target task, basic data of the work area is obtained, including terrain data, geological data, environmental data, and obstacle data. Using the basic data of the work area, the virtual construction scene is constructed through three-dimensional simulation technology.
4. The automatic control method for the bucket trajectory of an intelligent excavator as described in claim 1, characterized in that, Based on the target operation task and the virtual construction scenario, the initial bucket control trajectory is planned, including: Based on the target task, the target task type is obtained, which includes excavation, loading, and leveling operations; Based on the target task type, determine the target task requirements; Using the virtual construction scenario and referring to the target operation requirements, a construction operation simulation plan is performed to obtain the initial bucket control trajectory, which includes multiple segments of trajectory.
5. The method for automatic control of the bucket trajectory of an intelligent excavator as described in claim 4, characterized in that, The method further includes: Based on the initial bucket control trajectory, multiple sets of bucket control parameters of the multi-segment sub-trajectory are obtained, including bucket movement speed, acceleration, digging force and bucket attitude angle. Based on the multiple sets of bucket control parameters, the operation efficiency, operation accuracy, and mechanical safety are evaluated to obtain the control evaluation results; Based on the control evaluation results, the initial bucket control trajectory is optimized and adjusted.
6. The method for automatic control of the bucket trajectory of an intelligent excavator as described in claim 5, characterized in that, The method further includes: Based on the control evaluation results, multiple sub-trajectory parameters to be adjusted are identified and obtained. Based on the multiple sub-trajectory parameters to be adjusted, and by referring to the parameter adjustment step size, multiple sub-trajectory parameter adjustment schemes are obtained. For the multiple sub-trajectory parameter adjustment schemes, the efficiency, accuracy and safety of the schemes are evaluated, and the optimal adjustment scheme is obtained based on the evaluation results to optimize the initial bucket control trajectory.
7. An intelligent excavator bucket trajectory automatic control system, characterized in that, The system is used to implement the automatic control method for the bucket trajectory of an intelligent excavator according to any one of claims 1-6, the system comprising: A multi-sensor module deployment module is used to deploy multi-sensor modules based on the structural and functional information of the target excavator. A virtual construction scene construction module is used to read the target work task and, based on the target work task, obtain basic data of the work area to construct a virtual construction scene. An initial bucket control trajectory planning module is used to plan the initial bucket control trajectory based on the target operation task and the virtual construction scenario. The target operation task execution module is used to execute the target operation task with reference to the initial bucket control trajectory, and to acquire multi-dimensional real-time sensor data through the multi-sensor module. The trajectory deviation analysis module is used to perform trajectory deviation analysis based on the multi-source real-time sensor data, and generate trajectory compensation based on the trajectory deviation results. The correction compensation module is used to correct and compensate the initial bucket control trajectory using the trajectory compensation, and generate a corrected bucket control trajectory. A bucket trajectory control module is used to perform intelligent excavator bucket trajectory control by correcting the bucket control trajectory.