Precise butt joint method for split mobile charging robot

Abstract

The invention relates to the technical field of charging, in particular to a split mobile charging robot accurate docking method, which comprises the following steps: step 1, arranging a reflective sticker on a to-be-docked object, scanning the reflective sticker through a laser radar arranged on a mobile charging robot, and identifying laser data of the reflective sticker; step 2, according to the point cloud data of the reflective sticker identified by the laser data, fitting and calculating a target center point; step 3, calculating a moving target point location according to the fitted target center point and a preset distance parameter; and step 4, adjusting the mobile charging robot according to the distance between the mobile charging robot and the mobile target point location, and controlling the mobile charging robot to move to the mobile target point location so as to implement docking. According to the method, connection between the mobile charging robot and the to-be-docked device is implemented by means of recognition of the reflective stickers, accurate data of points and lines are determined according to the task state, the adjacent point and line data are filtered, and the robustness of the accurate docking process is ensured.

Description

Technical Field

[0001] The present application relates to the field of charging technology, and in particular to a method for precise docking of a split mobile charging robot. Background Art

[0002] New energy vehicles have already established a strong position in the automotive market, but the development of charging infrastructure has lagged significantly. This has led to the emergence of mobile charging robots, which integrate battery packs and charging and discharging systems on a mobile chassis. These robots can be flexibly moved to target vehicles for charging via remote control or autonomous driving.

[0003] Currently, mobile charging robots rely on GPS maps to navigate to their target location and then perform the next related operations based on the target location. However, in places with poor signal, such as underground parking lots, mobile charging robots cannot use maps, making docking difficult. Summary of the Invention

[0004] The technical problem to be solved by the present invention is that when the mobile charging robot cannot use GPS, docking is difficult to perform.

[0005] To this end, the present invention provides a method for precise docking of a split mobile charging robot.

[0006] The technical solution adopted by the present invention to solve its technical problem is:

[0007] A method for accurately docking a split mobile charging robot includes the following steps:

[0008] Step 1: Place a reflective sticker on the object to be docked, and use the laser radar installed on the mobile charging robot to scan the reflective sticker and identify the laser data of the reflective sticker;

[0009] Step 2: Calculate the target center point based on the reflective sticker point cloud data identified by the laser data;

[0010] Step 3: Calculate the moving target point based on the fitted target center point and the preset distance parameters;

[0011] Step 4: Adjust the mobile charging robot according to the distance between the mobile charging robot and the moving target point, and control the mobile charging robot to move to the moving target point for docking.

[0012] Furthermore, in step one, during the process of collecting reflective tape data, laser data is collected through a lidar, and the laser data extraction angle is expanded by 10 degrees to the left and right based on the angle directly in front of the lidar, and then the reflective tape is moved back gradually by 3 meters until the reflective tape laser data collection is completed.

[0013] Furthermore, in step 1, the data within the 20-degree range extracted is fitted with a curve equation according to distance and intensity: intensity = b / range 2 , where b is a constant, which is a statistical value calculated based on the correspondence between laser intensity and distance; range is the length of the laser scanning point, and intensity is the intensity value of the reflection at the laser scanning point. The b value is calculated, and then the calculated result is determined based on whether it is within the set interval range, such as [1000,1500]. If it is within the range, it is considered to be reflective tape laser data, otherwise it is not.

[0014] Furthermore, in step 2, the point cloud p in the current laser coordinate system is calculated based on the laser data distance and angle. laser (x i ,y i ), where x i =range i *cosθ,y i =range i *sinθ,range i The i-th laser test distance, θ is the distance corresponding to the i-th laser point, according to the coordinate transformation between the laser coordinate system and the vehicle coordinate system Convert the point cloud under laser coordinates to the vehicle coordinate system

[0015]

[0016] Furthermore, in the step 2, the point cloud data converted into the vehicle coordinate system is clustered, and the DBSCAN algorithm is used to configure relevant parameters according to different laser resolutions; the clustered point cloud data is filtered according to the number of point clouds in each cluster.

[0017] Furthermore, in step 2, if the object to be docked is a charging station, and the reflective tape is set on the side wall opposite to its V-shaped charging notch, the RANSAC algorithm is used to perform a straight line fitting on each cluster of point cloud data after screening, and the straight line slope k and constant b of the cluster point cloud will be obtained, and the intersection of any two straight lines is used as the target center point.

[0018] Furthermore, in step 2, if the object to be docked is an energy vehicle, the average value of each cluster of point cloud data is calculated to obtain the cluster center point as the target center point, and the positions of the reflective stickers set on the left and right sides of the front end and the left and right sides of the rear end of the energy vehicle are identified.

[0019] Furthermore, in step four, during the horizontal movement of the mobile charging robot to dock with the energy vehicle or the recharging station, the obstacle avoidance range is linearly reduced according to the ratio between the distance the mobile charging robot has moved and the distance to the end point calculated when the movement starts, and the obstacle is avoided.

[0020] Furthermore, when the mobile charging robot and the energy vehicle are docked and rotated: the center point of the mobile charging robot is used as the two right-angled sides of a right triangle from the two adjacent sides of the vehicle body. The length of the hypotenuse is calculated as the inner circle radius according to the Pythagorean theorem, and the outer circle radius is calculated based on the inner circle radius plus the threshold. An obstacle avoidance zone is constructed between the outer circle and the vehicle body. If an obstacle is scanned during rotation, the vehicle will stop in the obstacle avoidance zone.

[0021] Furthermore, during the rotation process of the mobile charging robot docking with the recharging seat: the distance between the center point of the energy vehicle and a corner of the front or rear end of the energy vehicle is used as the inner circle radius, and the outer circle radius R is calculated based on the inner circle radius plus a threshold value. An obstacle avoidance interval is constructed between the outer circle and the vehicle body. If an obstacle is scanned during rotation, the robot will stop in the obstacle avoidance interval.

[0022] The beneficial effect of the present invention is that the mobile charging robot of the present application can be used to accurately dock the split mobile charging robot with the charging pile return seat and the energy vehicle in places such as underground parking lots where it is difficult to use GPS navigation. It relies on the recognition of reflective stickers to implement the connection between the mobile charging robot and the device to be docked, determines the precise data of the point line according to the task status, and filters the adjacent point line data to ensure the robustness of the precise docking process. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present invention will be further described below with reference to the accompanying drawings and examples.

[0024] Figure 1 It is a schematic diagram of the docking process of the mobile charging robot in the present invention.

[0025] Figure 2 It is a schematic diagram of the process of identifying reflective tape in the present invention.

[0026] Figure 3 It is a structural diagram of the recharging station in the present invention.

[0027] Figure 4 It is a structural schematic diagram of the reflective sticker on the recharging station in the present invention.

[0028] Figure 5 It is a structural diagram of the reflective sticker logo for energy vehicles in the present invention.

[0029] Figure 6 It is a schematic diagram of the obstacle avoidance range of the mobile charging robot when rotating in the present invention.

[0030] Figure 7 It is a schematic diagram of the mobile charging robot of the present invention avoiding obstacles while moving. DETAILED DESCRIPTION

[0031] The present invention will now be described in further detail with reference to the accompanying drawings, which are simplified schematic diagrams that illustrate the basic structure of the present invention in a schematic manner.

[0032] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, features defined as "first" or "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0033] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0034] Reference Figure 1 A method for accurately docking a split mobile charging robot comprises the following steps:

[0035] Step 1: Scan and identify reflective sticker point cloud

[0036] Reference Figure 2 First of all, it should be noted that reflective stickers need to be affixed to the recharging station of the mobile charging robot and the energy vehicle docked by the mobile charging robot.

[0037] Laser scanning of reflective tape extracts the point cloud based on intensity and distance, and identifies the tape using pre-collected data. First, place the tape directly in front of the laser and begin collecting laser data. (To ensure real-time capture of reflective tape data, the laser data extraction angle is expanded by 10 degrees to the left and right, based on the angle directly in front of each laser manufacturer.) Then, gradually move the tape back 3 meters until complete laser data is collected.

[0038] It should be noted that the reflective sticker on the charging station is Figure 4As shown in the virtual image, the recharging seat is provided with a V-shaped notch for docking the mobile charging robot. Figure 3 As shown, the reflective stickers are set on the side walls opposite to the V-shaped notch (K1, K2); the reflective stickers on the energy vehicle are set on both sides of the front end (A1, A2) and both sides of the rear end (B1, B2) of the energy vehicle.

[0039] Clustering calculation is performed based on the point cloud data attached to the recharging station and energy vehicle to select the point clouds in the same cluster:

[0040] Specifically, first extract the laser data and convert it into a point cloud, and then convert it from the laser coordinate system to the vehicle coordinate system: According to the laser data distance and angle, calculate the point cloud p in the current laser coordinate system laser (x i ,y i ), where x i =range i *cosθ,y i =range i *sinθ,range i is the i-th laser test distance, θ is the distance data corresponding to the i-th laser point; according to the coordinate transformation between the laser coordinate system and the vehicle coordinate system Convert the point cloud under the laser coordinate system to the vehicle coordinate system p vehicle (x i ,y i ), The vehicle coordinates are based on the center of the vehicle as the origin, with the positive direction of the X-axis set along the front of the vehicle, and the positive direction of the Y-axis pointing to the left and forming a 90-degree angle with the X-axis.

[0041] The converted point cloud data is clustered, and the DBSCAN algorithm is used to configure relevant parameters according to different laser resolutions, such as: the number of point clouds within the range of 0.02m is at least 5; thus, qualified point cloud data are obtained.

[0042] Step 2: Calculation of docking target point

[0043] Before data extraction, organize the reflective tape information into reflective tape data, and fit the extracted data within the 20-degree range to the curve equation according to distance and intensity. For example: intensity = b / range 2 , where b is a constant, a value calculated based on the relationship between laser intensity and distance; range is the length of the laser scanning point, and intensity is the intensity of the reflection at the laser scanning point. The b value is calculated based on the specific situation, and then the calculated result is determined based on whether it is within the set interval range, such as [1000,1500]. If it is within the range, it is considered to be reflective tape data, otherwise it is not.

[0044] When S2.1 is connected to the recharging station

[0045] Perform point cloud fitting on the reflective areas K1 and K2 to calculate two straight lines in K1 and K2, and use the intersection of the two straight lines in the horizontal plane (xy plane) as the target point A.

[0046] Specifically, the clustered point cloud data is screened, requiring the number of point clouds in each cluster to meet the conditions, such as the number of point clouds is greater than 12, otherwise it will not participate in the fitting;

[0047] When the mobile charging machine is docked back to the charging station, the RANSAC algorithm is used to perform a straight line fit on each cluster of point cloud data after screening, and the slope k and constant b of the straight line for the cluster point cloud are obtained;

[0048] Calculate the intersection point based on the equations of two lines

[0049] y=k1*x+b1

[0050] y=k²*x+b²

[0051] get:

[0052]

[0053] S2.2 When the mobile charging robot docks with the energy vehicle, the average value is calculated based on the clustered point cloud data of each cluster:

[0054]

[0055] n is the number of point clouds per cluster. A renewable energy vehicle has four reflective points, so four average point positions are obtained. The center of the renewable energy vehicle is used as the coordinate origin O, the front end of the renewable energy vehicle is the positive Y-axis direction, and the right side is the positive X-axis direction. The front and rear reflective tapes are distinguished by the size of A1, A2, B1, and B2 on the x-axis and the positive and negative signs on the y-axis.

[0056] Step 3: Adjust the position of the mobile charging robot

[0057] S3.1 Position adjustment during docking with the recharging station

[0058] The intersection point A of the two straight lines calculated by the straight line equation is used as the docking center point. The position of the mobile charging robot is adjusted according to the lateral distance and angle between the mobile robot and the target point A. Specifically, the mobile charging robot records its current position as M. It is known that the intersection point A is in the mobile robot coordinate system. Assuming that the coordinates of A are A(x, y), the distance from the intersection point A to the robot M is The angle from the intersection point A to the robot is a=tan -1 x / y, then according to the formula d=H*cosa, the horizontal movement distance can be calculated, such as Figure 4 shown.

[0059] After the vehicle is adjusted to the position corresponding to the target center point, the vehicle's forward angle and speed are adjusted in real time based on the distance and angle between the mobile robot's current position and the target point; through real-time calculation of the target point, it is determined whether the vehicle has reached the target point; the vehicle stops after reaching the target point.

[0060] The target point is calculated based on the target center point and the preset distance parameter t1. The preset distance parameter t1 refers to Figure 4 The preset parameter t1 is the optimal distance between the mobile charging robot and the recharging station when the mobile charging robot docks with the recharging station, which is obtained through multiple experiments.

[0061] S3.2 Position adjustment during docking with energy vehicle

[0062] Reference Figure 5 , Figure 5 Small picture a in the middle shows the state of the mobile charging cart when it uses the front reflective sticker of the energy vehicle as a docking guide, and small picture b shows the state of the mobile charging cart when it switches to the rear reflective sticker as a docking guide.

[0063] Calculate the distance between the vehicle's position M and the two reflective stickers closest to it, denoted as d1 and d2 respectively. The distance between M and the line connecting the two reflective stickers is denoted as L. Based on d1, d2, and L, calculate the offset distance from the vehicle to the center point O and the angle the vehicle needs to rotate, and adjust the vehicle's rotation and translation.

[0064] During the docking process of the energy vehicle, two areas are set up on the left, front, and right sides of the vehicle. Figure 5 As shown, when entering the energy vehicle, the area will scan the energy vehicle to determine whether to switch to the rear reflective sticker as a docking guide; after the vehicle is adjusted to the corresponding position of the target center point, it switches to the rear reflective strip data calculation, and calculates the reflective strip data in real time to adjust the mobile docking process.

[0065] After the mobile charging robot is adjusted to the position corresponding to the target center point (cluster center), the vehicle's forward angle and speed are adjusted in real time according to the distance and angle between the mobile robot's current position and the target point (energy vehicle center); through real-time calculation of the target point, it is determined whether the vehicle has reached the target point; the vehicle stops after reaching the target point.

[0066] It should be noted that during the position adjustment process, the mobile charging robot needs to avoid obstacles:

[0067] When docked with the energy vehicle, the mobile charging robot is initially unloaded. The robot uses the distance from the center point of the mobile charging robot to both sides, and the length of the hypotenuse is calculated according to the Pythagorean theorem as the inner circle radius. The outer circle radius is calculated by adding a threshold to the inner circle radius. An obstacle avoidance zone is constructed between the outer circle and the vehicle body. If an obstacle is detected during rotation, the robot stops in the obstacle avoidance zone.

[0068] When docked with the recharging station, the mobile charging robot is in a fully loaded state. At this time, the mobile charging robot has docked with the energy vehicle and drives the energy vehicle toward the recharging station. During the rotation of the mobile charging robot: Figure 6 , the distance between the center point of the energy vehicle and any corner of the energy vehicle is used as the inner circle radius, W is the width of the energy vehicle, L is the length of the energy vehicle, and the outer circle radius R is calculated by adding a threshold to the inner circle radius. An obstacle avoidance zone is constructed between the outer circle and the vehicle body. When rotating, if an obstacle is detected in the obstacle avoidance zone, the vehicle will stop.

[0069] During the horizontal movement of the mobile robot: according to the ratio between the distance moved and the distance to the end point calculated at the beginning of the movement, the obstacle avoidance range of the movement is linearly reduced to ensure that the mobile charging robot will not trigger obstacle avoidance when scanning the recharging station or energy vehicle when moving towards the end point, and complete the docking process, such as Figure 7 shown.

[0070] To sum up, the mobile charging robot of the present application can be used as a split mobile charging robot to accurately dock with charging piles and energy vehicles in places such as underground parking lots where GPS navigation is difficult to use. It can determine the precise data of points and lines by extracting the feature information of reflective stickers scanned by laser according to the task status without relying on existing maps and without changing the map features, and filter the data of adjacent points and lines to ensure the robustness of the precise docking process.

[0071] With the above-described preferred embodiments of the present invention as a guide, and with reference to the above description, relevant personnel are fully capable of making various changes and modifications without departing from the technical spirit of this invention. The technical scope of this invention is not limited to the contents of the specification, but must be determined according to the scope of the claims.

Claims

1. A method for precise docking of a split mobile charging robot, characterized in that: The following steps are included: Step 1: Place a reflective sticker on the object to be docked, and use the laser radar installed on the mobile charging robot to scan the reflective sticker and identify the laser data of the reflective sticker; Step 2: Calculate the target center point based on the reflective sticker point cloud data identified by the laser data; Step 3: Calculate the moving target point based on the fitted target center point and the preset distance parameters; Step 4: Adjust the mobile charging robot according to the distance between the mobile charging robot and the moving target point, and control the mobile charging robot to move to the moving target point for docking.

2. The precise docking method of the split mobile charging robot according to claim 1, characterized in that: In step one, during the process of collecting reflective tape data, laser data is collected through a lidar, and the laser data extraction angle is expanded by 10 degrees to the left and right based on the angle directly in front of the lidar. Then, the reflective tape is moved back gradually by 3 meters until the reflective tape laser data collection is completed.

3. The precise docking method of the split mobile charging robot according to claim 2, characterized in that: In step 1, the data within the 20-degree range extracted is fitted with a curve equation according to distance and intensity: intensity = b / range 2 , where b is a constant, which is a statistical value calculated based on the correspondence between laser intensity and distance; range is the length of the laser scanning point, and intensity is the intensity value of the reflection at the laser scanning point. The b value is calculated, and then the calculated result is determined based on whether it is within the set interval range, such as [1000,1500]. If it is within the range, it is considered to be reflective tape laser data, otherwise it is not.

4. The precise docking method of a split mobile charging robot according to claim 1, characterized in that: In step 2, the point cloud p in the current laser coordinate system is calculated based on the laser data distance and angle. laser (x i ,y i ), where x i =range i *cosθ,y i =range i *sinθ,range i The i-th laser test distance, θ is the distance corresponding to the i-th laser point, according to the coordinate transformation between the laser coordinate system and the vehicle coordinate system Convert the point cloud under laser coordinates to the vehicle coordinate system 5. The precise docking method of the split mobile charging robot according to claim 4, characterized in that: In the second step, the point cloud data converted into the vehicle coordinate system is clustered, and the DBSCAN algorithm is used to configure relevant parameters according to different laser resolutions; the clustered point cloud data is filtered according to the number of point clouds in each cluster.

6. The precise docking method of a split mobile charging robot according to claim 5, characterized in that: In step 2, if the object to be docked is a charging station and the reflective tape is set on the side wall opposite to its V-shaped charging notch, the RANSAC algorithm is used to perform a straight line fitting on each cluster of point cloud data after screening. The straight line slope k and constant b of the cluster point cloud will be obtained, and the intersection of any two straight lines is used as the target center point.

7. The precise docking method for a split mobile charging robot according to claim 5, characterized in that: In step 2, if the object to be docked is an energy vehicle, the average value of each cluster of point cloud data is calculated to obtain the cluster center point as the target center point, and the positions of the reflective stickers set on the left and right sides of the front end and the left and right sides of the rear end of the energy vehicle are identified.

8. The precise docking method for a split mobile charging robot according to claim 1, characterized in that: In step 4, during the horizontal movement of the mobile charging robot and the energy vehicle or the recharging station, the obstacle avoidance range is linearly reduced according to the ratio between the distance the mobile charging robot has moved and the distance to the end point calculated when the movement starts, and the obstacle is avoided.

9. The precise docking method of a split mobile charging robot according to claim 1, characterized in that: When the mobile charging robot and the energy vehicle are docked and rotated: the center point of the mobile charging robot is used as the two right-angled sides of a right triangle from the two adjacent sides of the vehicle body. The length of the hypotenuse is calculated as the inner circle radius according to the Pythagorean theorem, and the outer circle radius is calculated based on the inner circle radius plus a threshold. An obstacle avoidance zone is constructed between the outer circle and the vehicle body. If an obstacle is scanned during rotation, the vehicle will stop in the obstacle avoidance zone.

10. The precise docking method of a split mobile charging robot according to claim 1, characterized in that: During the rotation process of the mobile charging robot docking with the recharging station: the distance between the center point of the energy vehicle and a corner of the front or rear end of the energy vehicle is used as the inner circle radius, and the outer circle radius R is calculated by adding a threshold to the inner circle radius to construct an obstacle avoidance zone between the outer circle and the vehicle body. If an obstacle is detected during rotation, the robot will stop in the obstacle avoidance zone.

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