Laser navigation system for agv trolley

Abstract

The invention discloses a laser navigation system for an agv trolley, and relates to the technical field of laser navigation. According to the laser navigation system for the agv trolley, a data acquisition module is used for acquiring three-dimensional laser point cloud data in a set range of the to-be-controlled agv trolley in real time; the data analysis module is used for performing data analysis on the three-dimensional laser point cloud data to obtain three-dimensional position coordinates of a plurality of obstacle areas; and the comprehensive analysis module is used for acquiring real-time three-dimensional position coordinates of the agv trolley and performing comprehensive analysis in combination with the three-dimensional position coordinates of each obstacle area to obtain an actual transportation track point, and the track control module is used for repeating the steps of data analysis, prediction analysis and comprehensive analysis after the agv trolley arrives at the actual transportation track point, so that the real-time three-dimensional position coordinates of the agv trolley are obtained. Therefore, the path can be dynamically adjusted in the running process of the trolley, obstacles are avoided, the collision risk is reduced, and then the safety of the transportation process is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of laser navigation, and particularly to a laser navigation system for an AGV cart. Background Art

[0002] As an important part of intelligent logistics and automated transportation, AGV carts have been widely used in fields such as manufacturing, warehousing, and logistics. One of its core technologies is the laser navigation system, which obtains precise information about the surrounding environment through a laser sensor to assist the AGV cart in autonomous positioning and path planning. The laser navigation system uses a lidar to emit laser beams and receive reflected signals. By processing the laser point cloud data, it realizes the detection of surrounding obstacles and the construction of a spatial map, thereby providing high-precision positioning information for the AGV cart.

[0003] Based on the above solution, it is found that the limitations of the prior art at least include the following problems. The prior art lacks sufficient adaptability and real-time performance in the process of path planning and execution, and it is difficult to make real-time adjustments according to the dynamically changing environment in actual operation, which easily causes the AGV cart to be unable to avoid obstacles in time or adjust the path. Summary of the Invention

[0004] Aiming at the deficiencies of the prior art, the present invention provides a laser navigation system for an AGV cart, which solves the problem of insufficient adaptability and real-time performance of the prior art in the process of path planning and execution.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: A laser navigation system for an AGV cart includes: a data acquisition module, a data analysis module, a comprehensive analysis module, and a trajectory control module; the data acquisition module is used to, when the AGV cart transports goods to the target area, acquire the three-dimensional laser point cloud data within the set range of the AGV cart to be controlled in real time; the data analysis module is used to perform data analysis on the three-dimensional laser point cloud data within the set range of the AGV cart to be controlled to obtain the three-dimensional position coordinates of several obstacle areas within the set range of the AGV cart to be controlled; the comprehensive analysis module is used to simultaneously acquire the real-time three-dimensional position coordinates of the AGV cart to be controlled, and perform comprehensive analysis in combination with the three-dimensional position coordinates of each obstacle area to obtain the actual transportation trajectory points of the AGV cart to be controlled; the trajectory control module is used to, after the AGV cart to be controlled reaches the actual transportation trajectory points, repeat the steps of data analysis, predictive analysis, and comprehensive analysis until the AGV cart to be controlled reaches the target area.

[0006] Further, the three-dimensional laser point cloud data is specifically the three-dimensional coordinates of each voxel point, and the three-dimensional coordinates take the starting point of the AGV vehicle as the origin of the three-dimensional coordinate system, the forward direction of the AGV vehicle as the X-axis, the left side direction of the AGV vehicle as the Y-axis, and the vertical direction of the AGV vehicle as the Z-axis.

[0007] Further, the set range of the AGV vehicle to be controlled is a semi-circular range centered on the AGV vehicle.

[0008] Further, the specific steps to obtain the three-dimensional position coordinates of several obstacle regions within the set range of the AGV vehicle to be controlled are as follows: comprehensively analyze the three-dimensional coordinates of each voxel point within the set range of the AGV vehicle to be controlled with the three-dimensional coordinates of each voxel point in the set neighborhood to obtain the distance values between each voxel point within the set range of the AGV vehicle to be controlled and each voxel point in the set neighborhood; and respectively judge and analyze the distance values between each voxel point within the set range of the AGV vehicle to be controlled and each voxel point in the set neighborhood with a preset distance threshold, and perform statistical analysis based on the judgment results to obtain several obstacle regions within the set range of the AGV vehicle to be controlled; and read and comprehensively analyze the three-dimensional coordinates of each voxel point of each obstacle region within the set range of the AGV vehicle to be controlled to obtain the three-dimensional position coordinates of several obstacle regions within the set range of the AGV vehicle to be controlled.

[0009] Further, the specific steps to obtain the actual transportation trajectory points of the AGV vehicle to be controlled are as follows: generate several predicted movement points of the AGV vehicle to be controlled based on linear interpolation; read the three-dimensional coordinates of each predicted movement point of the AGV vehicle to be controlled, and comprehensively analyze them with the obstacle movement distance values of each obstacle region to obtain the predicted obstacle distance values of each predicted movement point of the AGV vehicle to be controlled; respectively judge and analyze the predicted obstacle distance values of each predicted movement point of the AGV vehicle to be controlled with a preset safety distance to obtain several predicted safe movement points of the AGV vehicle to be controlled; read the three-dimensional coordinates of each predicted safe movement point of the AGV vehicle to be controlled, and comprehensively analyze them with the real-time three-dimensional position coordinates to obtain the actual transportation trajectory points of the AGV vehicle to be controlled.

[0010] Further, the specific steps to obtain several predicted safe movement points of the AGV vehicle to be controlled are as follows: if the predicted obstacle distance value of each predicted movement point of the AGV vehicle to be controlled is lower than the preset safety distance, do not mark it; if the predicted obstacle distance value of each predicted movement point of the AGV vehicle to be controlled is not lower than the preset safety distance, mark it as a predicted safe movement point and perform statistical analysis to obtain several predicted safe movement points of the AGV vehicle to be controlled.

[0011] Further, the specific steps for reading the three-dimensional coordinates of each predicted safe movement point of the to-be-controlled AGV vehicle and performing comprehensive analysis with the real-time three-dimensional position coordinates are as follows: Analyze each predicted safe movement point of the to-be-controlled AGV vehicle and the real-time three-dimensional position coordinates to obtain the movement reliability value of each predicted safe movement point of the to-be-controlled AGV vehicle; and sort the movement reliability values of each predicted safe movement point of the to-be-controlled AGV vehicle in descending order to generate a movement transportation trajectory point table, and perform comprehensive analysis based on the movement transportation trajectory point table to obtain the actual transportation trajectory points of the to-be-controlled AGV vehicle.

[0012] Further, the specific steps for performing comprehensive analysis based on the movement transportation trajectory point table are as follows: Select the predicted safe movement points in the first sequence in the movement transportation trajectory point table as the actual transportation trajectory points of the to-be-controlled AGV vehicle.

[0013] The present invention has the following beneficial effects:

[0014] (1) The laser navigation system for AGV vehicles can effectively avoid the blind spots or misidentification problems in traditional navigation systems by introducing a three-dimensional laser point cloud data acquisition and analysis module, so as to accurately obtain the obstacle information in the environment around the AGV vehicle in real time. Especially in complex environments, such as narrow channels or the presence of dynamic obstacles, it can timely detect and accurately calculate the three-dimensional position coordinates of the obstacles, enabling the AGV vehicle to adjust the driving path in real time, avoid potential obstacles, and reduce the collision risk, thereby improving the safety of the transportation process.

[0015] (2) The laser navigation system for AGV vehicles can dynamically adjust the path during the driving process of the vehicle by the comprehensive analysis module, which can obtain the three-dimensional position coordinates of the AGV vehicle in real time and perform comprehensive analysis with the coordinates of the obstacles, so as to ensure that it always drives along the optimal route. Even when the environment changes, it can react immediately, avoid deviating from the target path, and thus improve the automation level and reduce the dependence on manual intervention.

[0016] (3) The laser navigation system for AGV vehicles further eliminates the possible errors in path planning in traditional navigation systems by repeating the processes of data analysis, predictive analysis, and comprehensive analysis after the AGV vehicle reaches the actual transportation trajectory points, so as to ensure that the AGV vehicle can continuously respond to environmental changes during the transportation process, further improving the positioning accuracy and the accuracy of path planning. Through continuous real-time data update and path adjustment, the AGV vehicle can complete tasks more efficiently and reduce the repeated adjustment time caused by wrong paths, thereby improving the overall transportation efficiency.

[0017] Of course, it is not necessary for any product implementing the present invention to simultaneously achieve all the above-mentioned advantages. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a block diagram of a laser navigation system for an AGV cart according to the present invention.

[0019] Figure 2 It is a flowchart of the steps for obtaining the actual transportation trajectory points of the AGV cart to be controlled in a laser navigation system for an AGV cart according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] Please refer to Figure 1 , an embodiment of the present invention provides a technical solution: a laser navigation system for an AGV cart, including: a data acquisition module, a data analysis module, a comprehensive analysis module, and a trajectory control module; the data acquisition module is configured to, when the AGV cart transports goods to the target area, acquire in real time the three-dimensional laser point cloud data within the set range of the AGV cart to be controlled; the data analysis module is configured to perform data analysis on the three-dimensional laser point cloud data within the set range of the AGV cart to be controlled to obtain the three-dimensional position coordinates of several obstacle areas within the set range of the AGV cart to be controlled; the comprehensive analysis module is configured to simultaneously acquire the real-time three-dimensional position coordinates of the AGV cart to be controlled, and perform comprehensive analysis in combination with the three-dimensional position coordinates of each obstacle area to obtain the actual transportation trajectory points of the AGV cart to be controlled; the trajectory control module is configured to, after the AGV cart to be controlled reaches the actual transportation trajectory points, repeat the data analysis, prediction analysis, and comprehensive analysis steps until the AGV cart to be controlled reaches the target area.

[0021] The three-dimensional laser point cloud data is specifically the three-dimensional coordinates of each voxel point, and the three-dimensional coordinates take the starting point of the AGV cart as the origin of the three-dimensional coordinate system, the forward direction of the AGV cart as the X-axis, the left direction of the AGV cart as the Y-axis, and the vertical direction of the AGV cart as the Z-axis.

[0022] The set range of the AGV cart to be controlled is a semi-circular range centered on the AGV cart, and the radius is 1.5 m.

[0023] Specifically, the specific steps to obtain the three-dimensional position coordinates of several obstacle regions within the set range of the to-be-controlled AGV vehicle are as follows: comprehensively analyze the three-dimensional coordinates of each voxel point within the set range of the to-be-controlled AGV vehicle with the three-dimensional coordinates of each voxel point in the set neighborhood to obtain the distance values between each voxel point within the set range of the to-be-controlled AGV vehicle and each voxel point in the set neighborhood; and respectively compare the distance values between each voxel point within the set range of the to-be-controlled AGV vehicle and each voxel point in the set neighborhood with a preset distance threshold for judgment and analysis, and conduct statistical analysis based on the judgment results to obtain several obstacle regions within the set range of the to-be-controlled AGV vehicle; and read and comprehensively analyze the three-dimensional coordinates of each voxel point in each obstacle region within the set range of the to-be-controlled AGV vehicle (i.e., take the three-dimensional coordinates of the center point of the obstacle region) to obtain the three-dimensional position coordinates of several obstacle regions within the set range of the to-be-controlled AGV vehicle.

[0024] In this implementation scheme, by comprehensively analyzing the three-dimensional coordinates of each voxel point within the set range of the AGV vehicle and each voxel point in the neighborhood, and calculating the distance values, it can accurately judge which voxel points belong to the obstacle region, thereby avoiding misjudgment caused by sensor errors or environmental complexity, and then effectively improving the positioning accuracy of obstacles. Subsequently, it ensures that the AGV vehicle can accurately identify surrounding obstacles during operation and make corresponding avoidance or path adjustments. By judging the distance values between each voxel point and the neighboring points and comparing them with the preset distance threshold, it can flexibly respond to the continuously changing obstacles in the environment, thereby ensuring that the AGV vehicle can always adjust its path according to the latest obstacle distribution in a real-time dynamic environment, and improving the intelligence and response speed of the AGV vehicle in a complex environment. Finally, by statistically analyzing the distances between each voxel point and the neighboring voxel points, and on this basis, extracting the center point coordinates of the obstacle region, the actual position of the obstacle can be more accurately located, reducing the situation of misjudgment or missed judgment.

[0025] Specifically, as Figure 2 shown, the specific steps to obtain the actual transportation trajectory points of the to-be-controlled AGV vehicle are as follows: generate several predicted moving points of the to-be-controlled AGV vehicle based on linear interpolation; read the three-dimensional coordinates of each predicted moving point of the to-be-controlled AGV vehicle, and comprehensively analyze them with the obstacle movement blocking distance values of each obstacle region to obtain the predicted blocking distance values of each predicted moving point of the to-be-controlled AGV vehicle; respectively compare the predicted blocking distance values of each predicted moving point of the to-be-controlled AGV vehicle with a preset safety distance for judgment and analysis to obtain several predicted safe moving points of the to-be-controlled AGV vehicle; read the three-dimensional coordinates of each predicted safe moving point of the to-be-controlled AGV vehicle, and comprehensively analyze them with the real-time three-dimensional position coordinates to obtain the actual transportation trajectory points of the to-be-controlled AGV vehicle.

[0026] The specific steps for obtaining several predicted safe moving points of the AGV cart to be controlled are as follows: If the predicted obstacle distance value of each predicted moving point of the AGV cart to be controlled is lower than the preset safe distance, it is not marked and discarded; if the predicted obstacle distance value of each predicted moving point of the AGV cart to be controlled is not lower than the preset safe distance, it is marked as a predicted safe moving point, and statistical analysis is performed to obtain several predicted safe moving points of the AGV cart to be controlled.

[0027] In this implementation plan, several predicted moving points are generated based on linear interpolation, and combined with the obstacle distance values between each predicted point and the obstacles for analysis, so as to anticipate potential obstacles in the future path of the AGV cart in advance, calculate the possible collision risks, which enables the AGV cart to actively avoid collisions with obstacles, and further ensures that the AGV cart can move more smoothly and safely during the actual transportation process. By continuously judging the relationship between the predicted obstacle distance value of each predicted moving point and the preset safe distance, safe moving points are dynamically identified, thereby improving the flexibility and adaptability of the AGV cart. Especially in complex or changing environments, the AGV cart can quickly adjust its travel route to ensure safe and efficient arrival at the target area.

[0028] Specifically, the specific steps for reading the three-dimensional coordinates of each predicted safe moving point of the AGV cart to be controlled and performing comprehensive analysis with the real-time three-dimensional position coordinates are as follows: Analyze each predicted safe moving point of the AGV cart to be controlled and the real-time three-dimensional position coordinates to obtain the movement reliability value of each predicted safe moving point of the AGV cart to be controlled; and sort the movement reliability values of each predicted safe moving point of the AGV cart to be controlled in descending order to generate a movement transportation trajectory point table, and perform comprehensive analysis based on the movement transportation trajectory point table to obtain the actual transportation trajectory points of the AGV cart to be controlled.

[0029] The specific steps for performing comprehensive analysis based on the movement transportation trajectory point table are as follows: Select the predicted safe moving points in the first sequence in the movement transportation trajectory point table as the actual transportation trajectory points of the AGV cart to be controlled.

[0030] In this embodiment, by comprehensively analyzing each predicted safe moving point and the real-time three-dimensional position coordinates, the "moving reliability value" of each predicted safe moving point is calculated and sorted in descending order, so as to preferentially select the path point with the highest reliability, effectively eliminating the uncertainty in path selection. This ensures that when the AGV car performs the transportation task, it can select the most stable and safest path, reduce the trajectory deviation caused by misjudgment or external environment changes, and thus improve the accuracy and stability of navigation. At the same time, by sorting the moving reliability values in descending order and generating a moving transportation trajectory point table based on this, the safety and reliability of each path point are evaluated, so that when the AGV car selects the actual transportation trajectory point, it can preferentially select the path with the least risk and the strongest stability, thereby effectively reducing the path deviation or collision risk caused by obstacles or environmental changes.

[0031] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concept. Therefore, the appended claims are intended to be construed as including the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0032] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

Claims

1. A laser navigation system for an AGV vehicle, characterized in that: include: Data acquisition module, data analysis module, comprehensive analysis module, trajectory control module; The data acquisition module is used to acquire the three-dimensional laser point cloud data within the set range of the AGV vehicle to be controlled in real time when the AGV vehicle transports the goods to the target area; The data analysis module is used to perform data analysis on the three-dimensional laser point cloud data within the set range of the AGV vehicle to be controlled, and obtain the three-dimensional position coordinates of several obstacle areas within the set range of the AGV vehicle to be controlled; The comprehensive analysis module is used to simultaneously obtain the real-time three-dimensional position coordinates of the AGV vehicle to be controlled, and to perform comprehensive analysis in combination with the three-dimensional position coordinates of each obstacle area to obtain the actual transportation trajectory points of the AGV vehicle to be controlled; The trajectory control module is used to repeat the data analysis, prediction analysis, and comprehensive analysis steps after the AGV vehicle to be controlled reaches the actual transportation trajectory point until the AGV vehicle to be controlled reaches the target area.

2. The laser navigation system for AGV vehicles according to claim 1 is characterized in that: The three-dimensional laser point cloud data specifically refers to the three-dimensional coordinates of each voxel point, and the three-dimensional coordinates take the starting point of the agv car as the origin of the three-dimensional coordinate system, the forward direction of the agv car as the X-axis, the left direction of the agv car as the Y-axis, and the vertical direction of the agv car as the Z-axis.

3. The laser navigation system for AGV vehicles according to claim 1 is characterized in that: The setting range of the AGV car to be controlled is a semicircular range with the AGV car as the center.

4. The laser navigation system for AGV vehicles according to claim 2 is characterized in that: The specific steps to obtain the three-dimensional position coordinates of several obstacle areas within the set range of the AGV vehicle to be controlled are as follows: Comprehensively analyze the three-dimensional coordinates of each voxel point within the set range of the AGV vehicle to be controlled and the three-dimensional coordinates of each voxel point in the set neighborhood, and obtain the distance value between each voxel point within the set range of the AGV vehicle to be controlled and each voxel point in the set neighborhood; And the distance value of each voxel point within the set range of the AGV car to be controlled and each voxel point in the set neighborhood is respectively judged and analyzed with the preset distance threshold, and statistical analysis is performed based on the judgment results to obtain several obstacle areas within the set range of the AGV car to be controlled; And read the three-dimensional coordinates of each voxel point of each obstacle area within the set range of the AGV car to be controlled for comprehensive analysis, and obtain the three-dimensional position coordinates of several obstacle areas within the set range of the AGV car to be controlled.

5. The laser navigation system for AGV vehicles according to claim 1 is characterized in that: The specific steps to obtain the actual transport trajectory points of the AGV vehicle to be controlled are as follows: Generate several predicted moving points of the AGV to be controlled based on linear interpolation; Read the three-dimensional coordinates of each predicted moving point of the AGV vehicle to be controlled, and make a comprehensive analysis with the obstruction moving distance value of each obstacle area to obtain the predicted obstruction distance value of each predicted moving point of the AGV vehicle to be controlled; The predicted obstacle distance value of each predicted moving point of the AGV to be controlled is judged and analyzed with the preset safety distance to obtain several predicted safe moving points of the AGV to be controlled; The three-dimensional coordinates of each predicted safe moving point of the AGV vehicle to be controlled are read, and a comprehensive analysis is performed with the real-time three-dimensional position coordinates to obtain the actual transportation trajectory point of the AGV vehicle to be controlled.

6. The laser navigation system for AGV vehicles according to claim 5 is characterized in that: The specific steps to obtain several predicted safe moving points of the AGV vehicle to be controlled are as follows: If the predicted obstacle distance value of each predicted moving point of the AGV vehicle to be controlled is lower than the preset safety distance, it will not be marked; If the predicted obstacle distance value of each predicted moving point of the AGV vehicle to be controlled is not less than the preset safety distance, it is marked as a predicted safe moving point, and statistical analysis is performed to obtain several predicted safe moving points of the AGV vehicle to be controlled.

7. The laser navigation system for AGV vehicles according to claim 5 is characterized in that: The specific steps to read the 3D coordinates of each predicted safe moving point of the AGV vehicle to be controlled and conduct a comprehensive analysis with the real-time 3D position coordinates are as follows: Analyze each predicted safe moving point and real-time three-dimensional position coordinates of the AGV vehicle to be controlled to obtain the moving reliability value of each predicted safe moving point of the AGV vehicle to be controlled; The mobile reliability value of each predicted safe moving point of the AGV vehicle to be controlled is arranged in descending order to generate a mobile transportation trajectory point table, and a comprehensive analysis is performed based on the mobile transportation trajectory point table to obtain the actual transportation trajectory point of the AGV vehicle to be controlled.

8. The laser navigation system for AGV vehicles according to claim 1 is characterized in that: The specific steps for comprehensive analysis based on the mobile transport trajectory point table are as follows: The predicted safe moving points in the first sequence in the moving transport trajectory point table are selected as the actual transport trajectory points of the AGV vehicle to be controlled.

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