Truck loading method for cargo compartment loading tray steel drum aiming at inner wall concave defect

Abstract

The invention provides a truck loading method for loading tray steel drums on a cargo compartment aiming at the inner wall concave defect. The truck loading method comprises the steps that the inner wall of the cargo compartment is scanned by a laser radar, and modeling is conducted; the inner wall of the left cargo compartment is divided into rectangular recognition areas in a matrix mode, a steel drum recognition area and a tray recognition area are arranged in the recognition areas, and abscissas of protruding points of the steel drum recognition area and the tray recognition area are obtained respectively; according to the abscissa difference of the two points, the stacking benchmark of the tray steel drums is determined; sequentially stacking a horizontal row of tray steel drums from left to right; and then, stacking is performed row by row from bottom to top. According to the method, only the vertical surface distance between the two steel drums and the inner wall of the cargo compartment and the distance between the two steel drums and the corresponding position of the side face of the tray need to be calculated, so that the most reasonable stacking position is determined by using the minimum calculation modulus and comparing the difference between the two distances, and the problem that the tray steel drums collide and extrude with the inner wall of the cargo compartment in the stacking process is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent loading equipment, and particularly relates to a loading method for loading pallet steel drums in a cargo compartment with inner wall concave defects. Background Art

[0002] Using a container or a van to load pallet steel drums (the steel drums are stacked on the pallet in a 2×2 manner) is a commonly used loading and transportation method at present. Since the container and the van will collide during use, the side walls of the compartments of the container and the van will be deformed. Usually, the loading method is designed according to the original state of the compartment. Due to the deformation of the compartment, generally, after a simple visual inspection by the operator, the loading is still carried out according to the structure of the original state. As a result, during the loading process, the pallet, the steel drum and the inner wall of the compartment collide, and in serious cases, the loading cannot continue. Summary of the Invention

[0003] In order to solve the problems existing in the prior art, the present invention provides a loading method for loading pallet steel drums in a cargo compartment with inner wall concave defects, so as to solve the problem of difficult loading caused by the inner wall defects of the cargo compartment.

[0004] To achieve the above object, the following technical solutions are provided: A loading method for loading pallet steel drums in a cargo compartment with inner wall concave defects, comprising: S10. The lidar enters the cargo compartment, and continuously scans a plurality of cross-sections Zn of the cargo compartment where the lidar is located in the circumferential direction to obtain the polar coordinate scan data of the inner walls on both sides of the cargo compartment and the upper and lower endpoints A hi-n 、B hi-n 、A lo-n 、B lo-n in polar coordinates; S20. According to the polar coordinate scan data and the upper and lower endpoints of the inner walls on both sides obtained in step S10, model the bottom surface, the top surface and the inner walls on both sides of the cargo compartment; S30. Horizontally and vertically project the left inner wall of the cargo compartment, and divide it into rectangular recognition areas in a matrix manner. The width of each recognition area is D, and the height is H+h. A steel drum recognition area and a pallet recognition area are set in the recognition area. The pallet recognition area is located in the lower part, with a width of D and a height of H, and the steel drum recognition area has a width of D and a height of h; S40. Obtain the scan data of the inner wall of the left cargo compartment in each recognition area, and filter the abscissa Wlnx of the point Wln closest to the longitudinal central section of the cargo compartment in the pallet recognition area. Then, filter the abscissa Glnx of the point Gln closest to the longitudinal central section of the cargo compartment in the two vertical line areas at a distance of d / 2 from the vertical center line of the steel barrel recognition area; where d is the diameter of the steel barrel, and D > 2d, that is, when the steel barrels are stacked in a 2×2 manner in the center of the pallet, the four edges of the pallet protrude beyond the steel barrels. Using the data of the two vertical line areas as the calculation basis can maximize the saving of calculation pressure and the possibility of errors, and avoid the interference of data in other areas on the calculation result. Even if the abscissa data in the areas in the middle and on both sides of the vertical lines is too large, since it usually does not contact the surface of the steel barrel, the data error is overcome. Further considering that the concave shape is smoothly transitioned and there is no data protrusion (suddenly increasing coordinate data), only calculating the two vertical lines can meet the requirements of 99.9% of the usage scenarios. During the implementation process, preferably, the abscissa Wlnx of the circular area at the edge (or 1 - 2 cm inside the edge) of the pallet recognition area can be filtered, so as to further optimize the calculation and reduce errors. This strategy filters out the errors brought by the middle jack area of the pallet, making the calculation result more accurate and reliable. S50. Determine the benchmark for pallet and steel barrel stacking according to the difference in abscissa between the two points. S60. Stack a row of pallet and steel barrels horizontally in sequence from left to right; then stack row by row from bottom to top. S70. Horizontally project the inner wall of the right cargo compartment, project the recognition area onto the inner wall of the right cargo compartment, and refer to step S40 to obtain the scan data of the inner wall of the right cargo compartment in the recognition area. Filter the abscissa Wrnx of the point Wrn closest to the longitudinal central section of the cargo compartment in the pallet recognition area, and then filter the abscissa Grnx of the point Grn closest to the longitudinal central section of the cargo compartment in the two vertical line areas at a distance of d / 2 from the vertical center line of the steel barrel recognition area. S80. After stacking the pallets, calculate the difference between the right side of the pallet and the abscissa Wrnx of the point Wrn. When the difference is less than 2D and greater than or equal to D, determine the last pallet and steel barrel in the corresponding horizontal row to be stacked next. Then, judge the difference between the abscissa Grnx of the point Grn and the abscissa Mkx of the right endpoint Mk of the rightmost steel barrel on the already stacked pallet. When the difference is greater than or equal to D, stack normally. When the difference is less than D but greater than or equal to D - (D - 2d) / 2 = D / 2 + d, move the position of the last steel barrel on the pallet to the left by (D - 2d) / 2, and then stack. When the difference is less than D / 2 + d, alarm or abandon stacking.

[0005] In step S10, the abscissa X, ordinate Y, and vertical coordinate Z of the cargo box; In step S10, each cross-section n obtains a set of polar coordinate scan data; In step S10, A hi-n represents the upper endpoint of the left side, located in the second quadrant of the 90 - 180 degree interval; B hi-n represents the upper endpoint of the right side, located in the first quadrant of the 0 - 90 degree interval; A lo-n represents the lower endpoint of the left side, located in the third quadrant between 180 - 270 degrees; B lo-n represents the lower endpoint of the right side, located in the fourth quadrant between 270 - 0 degrees; The method for obtaining the four endpoints is to determine the maximum value of the polar radius by scanning with a lidar in each quadrant.

[0006] In step S20, the polar coordinate data obtained by lidar scanning is converted into Cartesian coordinate data according to the initial Cartesian coordinate system, and the bottom endpoints A lo-n and B lo-n are used to construct the bottom surface. Then, with the bottom surface as the coordinate plane, the horizontal center and vertical center are determined to establish the cargo box Cartesian coordinate system. Then, the angular relationship between the cargo box Cartesian coordinate system and the initial Cartesian coordinate system is determined, and the polar coordinate data is adjusted and then reconverted into the Cartesian coordinate data of the cargo box Cartesian coordinate system; the top endpoints A hi-n and B hi-n are used to construct the top surface, and the Cartesian coordinate data is projected onto the line segment A lo-n B lo-n to judge the distance Sn between the Cartesian coordinate data and A lo-n B lo-n and the inward distance δ at the endpoints of A lo-n B lo-n . Among them, Sn is used as a reference for dividing the recognition area in step S30, and δ is used to screen the point closest to the longitudinal center section in each recognition area in step S40.

[0007] In step S30, the tray recognition area is adapted to the shape of the tray side, and the height of the steel drum recognition area is the same as the height of the steel drum, and the width is greater than the width of the steel drum.

[0008] The horizontal in step S30 means that according to the set of the two lower endpoints A lo-n and B lo-n corresponding to the rectangle recognition area directly below, the bottom surface is drawn up, and this bottom surface is used as the horizontal reference plane. If it is parallel to the horizontal reference plane, it is considered to be the horizontal direction; the longitudinal center section corresponding to step S40 is the longitudinal section perpendicular to the center of the bottom surface.

[0009] Step S50 includes determining whether Glnx - Wlnx is greater than (D - 2d) / 2: If Glnx - Wlnx > (D - 2d) / 2, then use the abscissa value Glnx - (D - 2d) / 2 as the loading position of the first pallet close to the inner wall of the left cargo compartment; If Glnx - Wlnx ≤ (D - 2d) / 2, then use the abscissa value Wlnx as the loading position of the first pallet close to the inner wall of the left cargo compartment.

[0010] In step S70, when the two vertical lines at a distance of d / 2 from the vertical center line of the ladle identification area do not correspond to the cross-section Zn of the collected data, select the cross-section closest to the vertical line.

[0011] Compared with the prior art, the advantages of the present invention are as follows: The present invention conducts laser radar scanning and modeling, and then makes targeted designs for the stacking of pallet steel drums in each row. By identifying the inner wall of the cargo compartment and combining with the characteristics of the pallet steel drums for judgment, especially avoiding the complex calculations in the area far from the inner wall of the cargo compartment between the steel drums, only need to calculate the vertical distances between two steel drums close to the inner wall of the cargo compartment and the corresponding distances at the positions of the pallet sides, so as to use the smallest calculation modulus, compare the differences between the two distances, determine the most reasonable stacking position, and thus avoid the problem of collision and extrusion between the pallet steel drums and the inner wall of the cargo compartment during the stacking process. Description of the Drawings

[0012] Figure 1 It is a schematic diagram of obtaining four end points by laser radar scanning in four quadrants; Figure 2 It is a schematic diagram of dividing the identification area after horizontally and vertically projecting the inner wall of the left cargo compartment in step S30; Figure 3 It is a top view of the pallet steel drum; Figure 4 It is a side view of the pallet steel drum; Figure 5 It is a schematic diagram of the side projection dimensions of the pallet steel drum, showing the dimensions of the pallet and the steel drum in the figure; Figure 6 is opposite to Figure 5 showing a schematic diagram of the identification area; Figure 7 It is a schematic diagram of the side projection of the pallet steel drum, showing the positional relationship with the inner wall of the left cargo compartment in the figure; Figure 8 It is a schematic diagram of the partition of the identification area; Figure 9 It is a schematic diagram of the structure of the last pallet steel drum in a row stacked normally; Figure 10It is a schematic structural diagram of stacking after moving the steel drum on the last pallet to the left by (D - 2d) / 2; Figure 11 It is combined with Figures 9 - 10 A top view of the relative position relationship between the pallet and the steel drum. Specific implementation manner

[0013] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. Usually, the components of the embodiments of the present invention described and shown in the accompanying drawings here can be arranged and designed in various different configurations. Embodiment

[0014] Combined with Figures 1 - 8 As shown, a loading method for a cargo box loading pallet steel drum with an inner wall concave defect provided by the present invention includes: S10. The lidar enters the cargo box along with the loading machine system, and continuously scans multiple cross-sections Zn of the cargo box where the lidar is located in the circumferential direction to obtain the polar coordinate scan data of the inner walls on both sides of the cargo box and the upper and lower endpoints A hi-n , B hi-n , A lo-n , B lo-n of the polar coordinates; usually, the lidar enters the end of the cargo box along with the loading machine, and then the lidar is started to scan the inner wall of the cargo box in the circumferential direction. As the scanning progresses, the loading machine continuously retreats; since the rotational scanning of the lidar and the retreat of the loading machine can be carried out synchronously or step by step, when carried out synchronously, the circumferential data obtained by the scanning is actually spiral-shaped data. However, since the retreat speed is very slow and the rotational scanning speed of the lidar is very fast, the data obtained after each rotation of the lidar can be fitted on a plane. The fitted data is basically consistent with the situation of the inner wall of the cargo box and will not have a great impact on the progress of loading; each time the lidar rotates one week, it will scan a cross-section. For example, for the cross-section Z1, the four scanned endpoints are A hi-1 , B hi-1 , A lo-1 , B lo-1 ; and then so on until the scan data of the cross-section Zn; S20. According to the polar coordinate scan data of the inner walls on both sides and the upper and lower endpoints obtained in step S10, model the bottom surface, top surface, and inner walls on both sides of the cargo box, and the modeling makes all the detected data form a domain, so as to facilitate the division of the modeled left inner wall and right inner wall of the cargo box into recognition regions; S30. As Figure 2As shown in the figure, the horizontal vertical projection of the inner wall of the left cargo compartment is divided into rectangular recognition areas in the form of a matrix. The width of each recognition area is D, and the height is H + h (reference Figure 5 ). A steel drum recognition area 4 and a pallet recognition area 3 are set in the recognition area. The pallet recognition area 3 is located at the lower part, with a width of D and a height of H. The steel drum recognition area 4 has a width of D and a height of h. Each recognition area is in direct contact with the four adjacent recognition areas; S40. Obtain the scan data of the inner wall of the left cargo compartment in each recognition area, and screen the abscissa Wlnx of the point Wln closest to the longitudinal central section of the cargo compartment in the pallet recognition area. Then, screen the abscissa Glnx of the point Gln closest to the longitudinal central section of the cargo compartment in the two vertical line areas at a distance of d / 2 from the vertical center line of the steel drum recognition area. Here, d is the diameter of the steel drum, and D > 2d, that is, when the steel drums are stacked in a 2×2 manner in the center of the pallet, the four edges of the pallet protrude beyond the steel drums (reference Figures 3 - 4 ). Using the data of the two vertical line areas as the calculation basis can maximize the saving of calculation pressure and the possibility of errors, and avoid the interference of data in other areas on the calculation results. Even if the abscissa data in the areas in the middle and on both sides of the vertical lines is too large, since it usually does not contact the surface of the steel drum, data errors are overcome. Further considering that the concave shapes are all smoothly transitioned and there are no data protrusions (suddenly increased coordinate data), only calculating the two vertical lines can meet the requirements of 99.9% of the usage scenarios. During the implementation process, preferably, the abscissa Wlnx can be screened for the circular area at the edge (or 1 - 2 cm inside the edge) of the pallet recognition area, which can further optimize the calculation and reduce errors. This strategy eliminates the errors brought by the middle jack area of the pallet and can make the calculation results more accurate and reliable; S50. Determine the benchmark for stacking the pallet and steel drum according to the difference in the abscissas of the two points (as Figures 3 - 4 shown, pallet 1, steel drum 2); S60. Stack a row of pallet and steel drum in sequence from left to right. After each pallet and steel drum is stacked, the coordinates of the right edge of the pallet are recognized by the vision or ranging sensor of the loading machine, and then these coordinates are used as the initial coordinates for stacking the next pallet and steel drum. After the lower row of pallet and steel drum is stacked, stack the second row of pallet and steel drum on it until the entire section; S70. Horizontally and vertically project onto the inner wall of the right cargo compartment, project the recognition area onto the inner wall of the right cargo compartment, obtain the scan data of the inner wall of the right cargo compartment within the recognition area with reference to step S40, filter the abscissa Wrnx of the closest point Wrn to the longitudinal central section of the cargo compartment within the pallet recognition area, and then filter the abscissa Grnx of the closest point Grn to the longitudinal central section of the cargo compartment within the two vertical line areas at a distance of d / 2 from the vertical center line of the steel drum recognition area; S80. Combine Figures 9 - 11 , after stacking the pallets, calculate the difference between the right side of the pallet and the abscissa Wrnx of the closest point Wrn. When the difference is less than 2D and greater than or equal to D, then determine the last pallet steel drum in the corresponding horizontal row for the next stacking recognition area; then determine the difference between the abscissa Grnx of the closest point Grn and the abscissa Mk x of the rightmost endpoint Mk of the rightmost steel drum on the already stacked pallet. When the difference is greater than or equal to D, then stack normally. When the difference is less than D but greater than or equal to D - (D - 2d) / 2 = D / 2 + d, at this time, move the position of the last steel drum on the pallet to the left by (D - 2d) / 2, and then stack. When the difference is less than D / 2 + d, then alarm or abandon the stacking.

[0015] Normally, since the four steel drums on each pallet are located at the center of the pallet, after stacking the pallets, the distance between the right - hand steel drums on two adjacent pallets is exactly the width of one pallet, which is D; then the maximum adjustment distance of the steel drum on the pallet, that is, moving from the center of the pallet to the edge, referring to Figure 11 as shown, the distance from each steel drum to the edge of the pallet is (D - 2d) / 2, that is, the width D of the pallet minus the diameters d of two steel drums (2d in total), and then each edge accounts for half, which is (D - 2d) / 2. This is also the maximum distance that the steel drum on the pallet can move towards the edge. Exceeding this distance will cause the steel drum to press on other pallets.

[0016] So the distance Grnx - Mk x between the right - hand pallet and the closest point Grn. This distance being greater than D is okay (because normally, the distance between the right - hand steel drums on two adjacent pallets is D). If it is less than D, the steel drum on the last pallet needs to be moved to the left. Based on the foregoing, the maximum distance of its movement is (D - 2d) / 2. At this time, by reverse - derivation, the abscissa of the closest point Grn is exactly the same as the right - hand coordinate of the last steel drum at this time, that is, the extreme value of the abscissa of Grn. This extreme value needs to satisfy D - (D - 2d) / 2 = D / 2 + d.

[0017] In step S10, the abscissa X, ordinate Y, and vertical coordinate Z of the cargo compartment; In step S10, a set of polar coordinate scan data is obtained for each cross - section n; In step S10, A hi-n represents the upper endpoint of the left side face and is located in the second quadrant of the 90 - 180 - degree interval; B hi-n represents the upper endpoint of the right side face and is located in the first quadrant of the 0 - 90 - degree interval; A lo-n represents the lower endpoint of the left side face and is located in the third quadrant between 180 - 270 degrees; B lo-n represents the lower endpoint of the right side face and is located in the fourth quadrant between 270 - 0 degrees; The method for obtaining the four endpoints is to determine the maximum value of the polar radius by scanning with a lidar in each quadrant.

[0018] In step S20, the polar coordinate data obtained by lidar scanning is converted into rectangular coordinate data according to the initial rectangular coordinate system, and the bottom surface is constructed with the connection line of the two bottom endpoints A lo-n and B lo-n . Then, with the bottom surface as the coordinate plane, the horizontal center and the vertical center are determined to establish a carriage rectangular coordinate system. Then, the angular relationship between the carriage rectangular coordinate system and the initial rectangular coordinate system is determined, and the polar coordinate data is adjusted and then reconverted into the rectangular coordinate data of the carriage rectangular coordinate system; the top surface is constructed with the connection line of the two top endpoints A hi-n and B hi-n . The rectangular coordinate data is projected onto the line segment A lo-n B lo-n . The distance Sn between the rectangular coordinate data and A lo-n B lo-n and the inward - contraction distance δ at the endpoints of A lo-n B lo-n are judged. Among them, Sn is used as a reference for dividing the recognition area in step S30, and δ is used to screen the point closest to the longitudinal center section in each recognition area in step S40.

[0019] In step S30, the shape of the tray recognition area is adapted to the shape of the tray side, and the height of the steel barrel recognition area is the same as the height of the steel barrel, and the width is greater than the width of the steel barrel.

[0020] The "horizontal" in step S30 means that the bottom surface is drawn up according to the set of the two lower endpoints A lo-n and B lo-n directly below the rectangular recognition area, and this bottom surface is used as the horizontal reference surface. If it is parallel to the horizontal reference surface, it is considered to be in the horizontal direction; the longitudinal center section corresponding to step S40 is the longitudinal section perpendicular to the center of the bottom surface.

[0021] Step S50 includes judging whether Glnx - Wlnx is greater than (D - 2d) / 2: If Glnx - Wlnx > (D - 2d) / 2, then use the abscissa value Glnx - (D - 2d) / 2 as the loading position of the first pallet close to the inner wall of the left cargo compartment; If Glnx - Wlnx ≤ (D - 2d) / 2, then use the abscissa value Wlnx as the loading position of the first pallet close to the inner wall of the left cargo compartment.

[0022] This step combines the combined structural characteristics of the steel barrel and the pallet with the depression on the surface of the inner wall of the cargo compartment, so that the pallet and the steel barrel are placed inside the cargo compartment in the optimal way, and the collision with the depression on the surface of the inner wall of the cargo compartment can be avoided during placement, thus avoiding the extrusion between the steel barrel, the pallet and the inner wall of the cargo compartment.

[0023] In step S70, when the two vertical lines at a distance of d / 2 from the vertical center line of the steel barrel identification area in the cross-section Zn of the collected data do not correspond, select the cross-section closest to the vertical line.

[0024] Compared with the prior art, the advantages of the present invention are as follows: The present invention conducts laser radar scanning and modeling, and then makes targeted designs for the stacking of each row of pallet steel barrels. By identifying the inner wall of the cargo compartment and combining with the characteristics of the pallet steel barrels, especially avoiding the complex calculations in the area far from the inner wall of the cargo compartment between the steel barrels, only the vertical distances between two steel barrels close to the inner wall of the cargo compartment and the distances at the corresponding positions of the side faces of the pallets need to be calculated, so as to use the smallest calculation modulus, compare the differences between the two distances, determine the most reasonable stacking position, and thus avoid the problem of collision and extrusion between the pallet steel barrels and the inner wall of the cargo compartment during the stacking process.

[0025] Note that the above is only the preferred embodiment of the present invention and the technical principles applied. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described here, and various obvious changes, re-adjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments. Without departing from the concept of the present invention, more other equivalent embodiments can be included, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for loading steel drums of a cargo compartment loading tray with inner wall concave defects, characterized in that, Including: S10. Enter the cargo compartment by the lidar, and continuously scan multiple cross-sections Zn of the cargo compartment where the lidar is located in the circumferential direction to obtain the polar coordinate scan data of the inner walls on both sides of the cargo compartment on each cross-section and the upper and lower endpoints A hi-n , B hi-n , A lo-n , B lo-n polar coordinates; S20. Model the bottom surface, top surface and inner walls on both sides of the cargo compartment according to the polar coordinate scanning data and the upper and lower endpoints of the inner walls on both sides obtained in step S10. S30. Horizontally and vertically project the inner wall of the left cargo compartment, divide it into rectangular recognition areas in the form of a matrix, the width of each recognition area is D, the height is H + h, and a steel drum recognition area and a pallet recognition area are set in the recognition area. The pallet recognition area is located in the lower part, with a width of D and a height of H, and the steel drum recognition area has a width of D and a height of h. S40. Obtain the scanning data of the inner wall of the left cargo compartment in each recognition area, screen the abscissa Wlnx of the point Wln closest to the longitudinal central section of the cargo compartment in the pallet recognition area, and then screen the abscissa Glnx of the point Gln closest to the longitudinal central section of the cargo compartment in the two vertical line areas at a distance of d / 2 from the vertical center line of the area in the steel drum recognition area; where d is the diameter of the steel drum, D > 2d, that is, when the steel drums are stacked in a 2×2 manner in the center of the pallet, the four edges of the pallet protrude beyond the steel drums. S50. Determine the benchmark for pallet and steel drum stacking according to the difference in abscissa between the two points. S60. Stack a row of pallet and steel drums horizontally in sequence from left to right; then stack row by row from bottom to top.

2. The loading method according to claim 1, wherein, Also including: S70. Horizontally and vertically project the inner wall of the right cargo compartment, project the recognition area onto the inner wall of the right cargo compartment, obtain the scanning data of the inner wall of the right cargo compartment in the recognition area with reference to step S40, screen the abscissa Wrnx of the point Wrn closest to the longitudinal central section of the cargo compartment in the pallet recognition area, and then screen the abscissa Grnx of the point Grn closest to the longitudinal central section of the cargo compartment in the two vertical line areas at a distance of d / 2 from the vertical center line of the area in the steel drum recognition area. S80. After stacking the pallets, calculate the difference between the right side of the pallet and the abscissa Wrnx of the closest point Wrn. When the difference is less than 2D and greater than or equal to D, then determine to stack the last pallet and steel drum in the corresponding horizontal row of the recognition area next; then judge the difference between the abscissa Grnx of the closest point Grn and the abscissa Mkx of the right endpoint of the rightmost steel drum on the stacked pallet. When the difference is greater than or equal to D, stack normally. When the difference is less than D but greater than or equal to D - (D - 2d) / 2 = D / 2 + d, at this time, move the position of the last steel drum on the pallet to the left by (D - 2d) / 2, and then stack. When the difference is less than D / 2 + d, alarm or abandon stacking.

3. The loading method according to claim 1, wherein In step S10, the abscissa X, ordinate Y and vertical coordinate Z of the cargo compartment.

4. The loading method according to claim 3, characterized in that In step S10, a set of polar coordinate scanning data is obtained for each section n.

5. The loading method according to claim 1, characterized in that In step S10, A hi-n represents the upper endpoint of the left side face and is located in the second quadrant of the 90 - 180 degree interval; B hi-n represents the upper endpoint of the right side face and is located in the first quadrant of the 0 - 90 degree interval; A lo-n represents the lower endpoint of the left side face and is located in the third quadrant between 180 - 270 degrees; B lo-n represents the lower endpoint of the right side face and is located in the fourth quadrant between 270 - 0 degrees; The method for obtaining the four endpoints is to determine the maximum value of the polar radius by scanning with a lidar in each quadrant.

6. The loading method according to claim 1, wherein In step S20, the polar coordinate data obtained by lidar scanning is converted into Cartesian coordinate data according to the initial Cartesian coordinate system, and the bottom endpoints A lo-n , B lo-n are used to construct the bottom surface. Then, with the bottom surface as the coordinate plane, the horizontal center and the vertical center are determined to establish the Cartesian coordinate system of the carriage. Next, the angular relationship between the Cartesian coordinate system of the carriage and the initial Cartesian coordinate system is determined, and the polar coordinate data is adjusted and then reconverted into the Cartesian coordinate data of the Cartesian coordinate system of the carriage. The top endpoints A hi-n , B hi-n are used to construct the top surface, and the Cartesian coordinate data is projected onto the line segment A lo-n B lo-n . The distance Sn between the Cartesian coordinate data and A lo-n B lo-n and the inward distance δ at the endpoints of A lo-n B lo-n are judged. Here, Sn is used as a reference for dividing the recognition area in step S30, and δ is used to screen the points closest to the longitudinal center section in each recognition area in step S40.

7. The loading method according to claim 1, wherein In step S30, the shape of the pallet recognition area fits the side of the pallet, the height of the steel drum recognition area is the same as the height of the steel drum, and the width is greater than the width of the steel drum.

8. The loading method according to claim 1, characterized in that The "horizontal" in step S30 means that the bottom surface is determined according to the set of the two lower endpoints A lo-n and B lo-n directly below the rectangular recognition area, and this bottom surface is used as the horizontal reference plane. If it is parallel to the horizontal reference plane, it is considered to be in the horizontal direction; the longitudinal central section corresponding to step S40 is the longitudinal section perpendicular to the center of the bottom surface.

9. The loading method according to claim 1, wherein Step S50 includes judging whether Glnx - Wlnx is greater than (D - 2d) / 2: If Glnx - Wlnx > (D - 2d) / 2, then use the abscissa value Glnx - (D - 2d) / 2 as the loading position of the first pallet close to the inner wall of the left cargo compartment; If Glnx - Wlnx ≤ (D - 2d) / 2, then use the abscissa value Wlnx as the loading position of the first pallet close to the inner wall of the left cargo compartment.

10. The loading method according to claim 2, wherein In steps S70 and S40, when the two vertical lines at a distance of d / 2 from the vertical center line of the ladle identification area do not correspond to the cross-section Zn of the collected data, select the cross-section closest to the vertical line.

Images