Walking path decision-making method for orderly charging guide rail type robot for new energy automobile

Abstract

The invention discloses a walking path decision-making method of a guide rail type robot for orderly charging of a new energy automobile. The walking path decision-making method comprises the following steps that S1, the guide rail type robot and a guide rail used for running of the guide rail type robot are provided; s2, two rows of parking spaces are provided, the number of one row of parking spaces is from the minimum parking space to the minimum parking space + m, the number of the other row of parking spaces is from the maximum parking space to the maximum parking space-n, and m and n are natural numbers larger than 1; s3, the position of the guide rail type robot is set as the current parking position of the robot and the target position, and the target position is the current idle charging position; and S4, the guide rail type robot is conveyed to the target position through a path calculation method and position recognition and verification, the walking path of the robot can be optimized, the operation efficiency can be improved, the vehicle waiting time can be shortened, and high practical value and popularization prospects are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent robots, and in particular to a walking path decision model and method of a rail-type robot used for orderly charging in a new energy vehicle charging station. Background Art

[0002] With the popularity of new energy vehicles, charging efficiency and charging order of charging stations have become key issues. Existing charging stations mostly use fixed charging piles, which often have problems with oil vehicles occupying the space and occupying the space overtime, seriously wasting charging resources and affecting the operating efficiency of charging stations. In order to effectively solve this problem, rail-type robots are introduced into charging stations to allocate charging resources to the location of vehicles that need to be charged. How to optimize the robot's walking path to improve charging efficiency and reduce waiting time is a problem that current technology needs to solve. Summary of the invention

[0003] In view of the shortcomings of the prior art, the present invention provides a walking path decision method for a rail-type robot for orderly charging of new energy vehicles. The purpose of the present invention is to provide a walking path decision model and method for a rail-type robot for orderly charging of new energy vehicles, so as to optimize the robot's walking path, improve charging efficiency, and reduce vehicle waiting time.

[0004] To achieve the above object, the present invention provides the following technical solutions: A walking path decision method for a rail-type robot for orderly charging of new energy vehicles comprises the following steps: Step S1: providing a rail-type robot and a rail for the rail-type robot to operate; Step S2: providing two rows of parking spaces, wherein one row of parking spaces is numbered from the smallest parking space to the smallest parking space+m, and the other row of parking spaces is numbered from the largest parking space to the largest parking space-n, wherein m and n are natural numbers greater than 1; Step S3: setting the position of the rail-type robot as the current docking position of the robot and the target position, wherein the target position is the current idle charging position; Step S4: The rail-type robot is transported to the target position through path calculation method, position recognition and verification.

[0005] As a further solution of the present invention, the path calculation method includes a scene 1 path calculation method and a scene 2 path calculation method; wherein the scene 1 path calculation method is: when the distance of the target position ≥ the distance of the current parking position, there are two paths: path 1 = target position - current parking position; path 2 = (current parking position - minimum parking space) + (maximum parking space - target parking space).

[0006] As a further solution of the present invention, scenario 2: when the distance to the target position is less than the distance to the current parking position, there are two paths: path 11 = current parking position - target position and path 12 = (maximum parking space - current parking position) + (maximum parking space - target position).

[0007] As a further solution of the present invention, first determine that the self-marked position is ≥ the current position, then calculate the path length according to scenario 1; if it is determined that the target position is < the current docking position, then calculate the path length according to scenario 2, and then compare the lengths of the two paths to determine which path to select.

[0008] As a further solution of the present invention, after the path is determined, the rail-type robot is moved to the target position and the code is scanned to identify the position.

[0009] The present invention has the following beneficial effects: The present invention provides an effective walking path decision model and method for a rail-type robot for orderly charging of new energy vehicles, which can optimize the robot's walking path, improve operating efficiency, and reduce vehicle waiting time, and has high practical value and promotion prospects.

[0010] In order to more clearly illustrate the structural features and effects of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1-Figure 2 Schematic diagram of different application scenarios mentioned in the present invention.

[0012] Figure 3 This is a schematic diagram of a walking path decision method for a rail-type robot for orderly charging of new energy vehicles mentioned in the present invention. DETAILED DESCRIPTION

[0013] The present invention will be further explained below in conjunction with the accompanying drawings and related knowledge, and described clearly and completely. Obviously, the described application is only a part of the embodiments of the present invention, rather than all the embodiments.

[0014] The present invention discloses a walking path decision method for a rail-type robot for orderly charging of new energy vehicles. The existing rail-type robots have limited scene adaptability and usually only support linear rails or ordinary curved rails, but not O-type rails and their supporting path optimization algorithms.

[0015] Reference Figure 1-Figure 3 As shown, the present invention provides a walking path decision method for a rail-type robot for orderly charging of a new energy vehicle, comprising the following steps: Step S1: providing a rail-type robot and a rail for the operation of the rail-type robot, wherein the rail provides a specific trajectory for the movement of the robot, ensuring that the robot can move within a specified range, and facilitating path planning and control; Step S2: two rows of parking spaces are provided, one row of parking spaces is numbered from the smallest parking space to the smallest parking space + m, and the other row of parking spaces is numbered from the largest parking space to the largest parking space - n, where m and n are natural numbers greater than 1, which is helpful for orderly management and positioning of parking spaces. When planning a path, the relative relationship between the target position can be quickly determined according to the current position of the robot and the parking space number, which is convenient for calculating and selecting the optimal path; Step S3: Set the position of the rail robot to the current docking position of the robot and the target position, where the target position is the current idle charging position. Set the position of the rail robot to the current docking position of the robot and the target position (the target position is the current idle charging position). Clarifying the current position and target position of the robot is the key information for path decision-making. Based on these two position information, the specific path of the robot from the current position to the target position is planned through the subsequent path calculation method; Step S4: The rail robot is transported to the target position through path calculation method, position identification and verification. Comprehensive factors such as the current position of the robot, the target position, the shape and layout of the rail, and possible obstacles. Different path calculation formulas may also be designed according to different charging scenarios. During the movement of the robot, it is necessary to continuously identify its own position through equipment such as the code scanning system to ensure that it is consistent with the calculated path. At the same time, the identified position information must be verified to prevent errors or deviations. If the position information is found to be abnormal, automatic error correction may be required, such as detecting whether the physical limit position of the rail is reached through the limit sensor as described above, and adjusting and updating the current actual position through the built-in error correction algorithm.

[0016] Reference Figure 1 As shown, the path calculation method includes the path calculation method for scenario 1 and the path calculation method for scenario 2; the path calculation method for scenario 1 is: when the distance to the target position ≥ the distance to the current parking position, there are two paths: path 1 = target position - current parking position; path 2 = (current parking position - minimum parking space) + (maximum parking space - target parking space).

[0017] Reference Figure 2 As shown, scenario 2: when the distance to the target position is less than the distance to the current parking position, there are two paths: path 11 = current parking position - target position and path 12 = (maximum parking space - current parking position) + (maximum parking space - target position).

[0018] Reference Figure 3As shown, the specific working process of the present invention is as follows: the robot receives a charging task. According to the current position and the target position, it determines whether it belongs to scene 1 or scene 2. According to the scene, the length of path 1 and path 2 is calculated. Path 1 and path 2 are compared and the shorter path is selected. The robot executes the selected path and moves to the target position. After arriving at the target position, the position is identified and verified.

[0019] In the present invention, after the robot receives the charging task, the first task is to determine whether the scene is scene 1 or scene 2 based on the distance relationship between its current position and the target position. Scene judgment is the basis for subsequent path calculation and selection, and determines the path calculation method used by the robot to plan the moving route; after determining the scene, the robot calculates the length of path 1 and path 2 in the scene respectively. By accurately calculating the lengths of different paths, a quantitative basis is provided for path selection. After comparing the lengths of path 1 and path 2, the robot selects the shorter path as the execution path. The selection strategy aims to optimize the robot's movement process, reduce the moving distance, and improve efficiency. Subsequently, the robot moves to the target position along the selected path. After the robot reaches the target position, position identification and verification are performed. By identifying and verifying the current position, it is ensured that the robot accurately reaches the target charging position. If deviations are found in position identification and verification, the corresponding error correction mechanism may be triggered to ensure the smooth progress of the charging task.

[0020] The present invention selects the shortest path by calculating and comparing multiple paths in different scenarios, thereby reducing the robot's moving time and energy consumption and improving the charging efficiency. The path calculation method is designed for different distances between the target position and the current parking position, which can adapt to different guide rail layouts and parking space distributions and improve the robot's ability to work in various environments. The position recognition and verification mechanism after reaching the target position effectively ensures the accuracy of the robot's positioning and provides a guarantee for the smooth implementation of subsequent charging operations. It is suitable for various types of rail robot systems for orderly charging of new energy vehicles. Whether it is a large charging station or a small charging facility, this method can optimize the robot's walking path and improve the overall charging service quality.

[0021] The technical principle of the present invention is described above in combination with the specific embodiments, which are only preferred implementations of the present invention. The protection scope of the present invention is not limited to the above embodiments, and all technical solutions under the idea of ​​the present invention belong to the protection scope of the present invention. Those skilled in the art can think of other specific implementations of the present invention without creative work, and these methods will fall within the protection scope of the present invention.

Claims

1. A walking path decision method for a rail-type robot for orderly charging of new energy vehicles, characterized in that: The following steps are involved: Step S1: providing a rail-type robot and a rail for the rail-type robot to operate; Step S2: providing two rows of parking spaces, wherein one row of parking spaces is numbered from the smallest parking space to the smallest parking space+m, and the other row of parking spaces is numbered from the largest parking space to the largest parking space-n, wherein m and n are natural numbers greater than 1; Step S3: setting the position of the rail-type robot as the current docking position of the robot and the target position, wherein the target position is the current idle charging position; Step S4: The rail-type robot is transported to the target position through path calculation method, position recognition and verification.

2. A walking path decision method for a rail robot for orderly charging of new energy vehicles as claimed in claim 1, characterized in that: The path calculation method includes a scenario 1 path calculation method and a scenario 2 path calculation method; The path calculation method for scenario 1 is: when the distance to the target position ≥ the distance to the current parking position, there are two paths: Path 1 = target position - current parking position; Path 2 = (current parking position - minimum parking space) + (maximum parking space - target parking space).

3. A walking path decision method for a rail robot for orderly charging of new energy vehicles as claimed in claim 2, characterized in that: Scenario 2: When the distance to the target position is less than the distance to the current parking position, there are two paths: path 11 = current parking position - target position and path 12 = (maximum parking space - current parking position) + (maximum parking space - target position).

4. A walking path decision method for a rail-type robot for orderly charging of new energy vehicles as claimed in claim 3, characterized in that: First, if the self-target position is ≥ the current position, the path length is calculated according to scenario 1; if the target position is < the current stop position, the path length is calculated according to scenario 2, and then the lengths of the two paths are compared to determine which path to select.

5. A walking path decision method for a rail robot for orderly charging of new energy vehicles as claimed in claim 4, characterized in that: After determining the path, move the rail-mounted robot to the target location and scan the code to identify the location.

Images