Material taking method of ship unloader and ship unloading system

Abstract

The invention relates to a material taking method of a ship unloader and a ship unloading system.The method comprises the steps that information of a cabin and information of materials located in the cabin are obtained, the information of the cabin comprises coordinates of the cabin, and the information of the materials comprises surface features of the materials; acquiring a plurality of candidate paths of a material taking device of the ship unloader from a starting position to a target position, wherein the material taking device is a scraper material taking device mounted on a vertical arm of the ship unloader; selecting a working path from the plurality of candidate paths; and material taking is executed based on the working path.

Description

Technical Field

[0001] This disclosure relates to the field of port material handling, and more specifically, to a material handling method for a ship unloader, a ship unloading system, a medium, and electronic equipment. Background Technology

[0002] A ship unloader is a mechanical device that unloads cargo from a ship to a dock. Cargo includes ores, coal, grains, and fertilizers. Ship unloaders can grab cargo using grab buckets, bucket wheels, auger blades, pneumatic airflow, or rubber belts.

[0003] Currently, the operation of ship unloaders largely relies on manual operation and simple auxiliary systems. Problems such as low automation efficiency still exist in the positioning and path planning of the ship unloader's cargo-picking device. Summary of the Invention

[0004] The purpose of this disclosure is to overcome the above-mentioned deficiencies in the prior art and to provide a material handling method, unloading system, medium and electronic equipment for a ship unloader.

[0005] According to a first aspect of this disclosure, a material handling method for a ship unloader is provided, comprising: acquiring information about a ship hold and information about materials located within the ship hold, wherein the information about the ship hold includes the coordinates of the ship hold and the information about the materials includes surface features of the materials; acquiring a plurality of candidate paths for a material handling device of the ship unloader from a starting position to a target position, wherein the material handling device is a scraper material handling device mounted on a vertical arm of the ship unloader; selecting a working path from the plurality of candidate paths; and performing material handling based on the working path.

[0006] In some embodiments, acquiring information about the cabin and the materials located within the cabin includes: acquiring the location of the material handling device and the location of the data acquisition device; acquiring three-dimensional scan data of the cabin and the materials from the data acquisition device; establishing a point cloud model based on the three-dimensional scan data; and processing the point cloud model to identify the boundaries of the cabin and the surface of the materials.

[0007] In some embodiments, the method further includes: identifying a work area based on the boundaries of the cabin and the surface of the material; and dividing the work area into multiple sub-work areas.

[0008] In some embodiments, the method further includes rendering a point cloud data image based on the point cloud model; and performing obstacle detection on the point cloud data image.

[0009] In some embodiments, obtaining multiple candidate paths from the starting position to the target position of the unloader's material handling device includes: obtaining the multiple candidate paths based on multiple different targets; optimizing each of the multiple candidate paths in terms of spatial location; and obtaining multiple optimized candidate paths.

[0010] In some embodiments, optimizing the spatial location of each of the plurality of candidate paths includes: determining a plurality of three-dimensional spatial points for each candidate path; and adjusting the positions of the plurality of three-dimensional spatial points to perform smooth optimization on each candidate path.

[0011] In some embodiments, the number of the plurality of three-dimensional spatial points is 5-10.

[0012] In some embodiments, selecting a working path from the plurality of candidate paths includes selecting the working path from the plurality of optimized candidate paths using a particle swarm optimization algorithm.

[0013] In some embodiments, the method further includes: obtaining a local region on the work path, the local region being a region where a sudden obstacle is detected; adjusting the local region to prevent collisions; and obtaining an updated work path in some embodiments.

[0014] In some embodiments, the method further includes: importing the updated work path; detecting collision risks on the updated work path and comparing the collision risks with a safety threshold; and adjusting the control parameters of the unloader based on the comparison results.

[0015] According to a second aspect of this disclosure, an electronic device is provided, comprising: at least one processor; and a memory for storing computer-executable instructions that, when executed, cause the at least one processor to perform the unloading method of the ship unloader according to the aforementioned first aspect.

[0016] According to a third aspect of this disclosure, a computer-readable storage medium is provided having computer-executable instructions stored thereon for performing the material handling method of the unloader according to the first aspect described above.

[0017] According to a fourth aspect of this disclosure, a computer program product is provided, which is tangibly stored on a computer-readable storage medium and includes computer-executable instructions that, when executed by at least one processor, cause at least one processor to perform the material handling method of the unloader according to the first aspect described above.

[0018] According to a fifth aspect of this disclosure, a ship unloading system is provided, comprising: a ship unloader including a trolley, a horizontal transport device and a vertical material handling device, wherein the vertical material handling device is a scraper material handling device; a data acquisition device for detecting information about the ship hold and information about the material located in the ship hold; and a control unit configured to execute the material handling method of the ship unloader according to the aforementioned first aspect.

[0019] According to the material handling method, unloading system, medium, and electronic equipment of the ship unloader disclosed herein, the information of the ship's hold and the material located within the hold are first acquired, thereby obtaining data such as the coordinates of the hold and the surface characteristics of the material. Based on the information of the hold and the material, a dataset containing multiple candidate paths is determined, and a working path is selected from the multiple datasets. Material handling is performed based on the selected working path. This method can automatically plan the working path of the material handling device according to the state of the ship and the material, and select the optimal working path by considering multiple factors, thereby providing automation efficiency and safety. Attached Figure Description

[0020] Other features and advantages of this disclosure will be better understood through the following detailed description of preferred embodiments in conjunction with the accompanying drawings, wherein the same reference numerals denote the same or similar parts.

[0021] Figure 1 A schematic flowchart of an exemplary unloader material handling method according to an embodiment of the present disclosure is shown.

[0022] Figure 2 A flowchart illustrating an exemplary method for obtaining cabin information and material information according to an embodiment of this disclosure is shown.

[0023] Figure 3 A flowchart illustrating an exemplary method for obtaining multiple candidate paths for a material handling device according to an embodiment of this disclosure is shown.

[0024] Figure 4 A flowchart illustrating an exemplary working path update method according to an embodiment of this disclosure is shown.

[0025] Figure 5 A flowchart illustrating a pre-running method for an exemplary working path according to an embodiment of this disclosure is shown.

[0026] Figure 6 A block diagram of an exemplary electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0027] To enable those skilled in the art to better understand the technical solutions of this disclosure, the disclosure will be further described in detail below with reference to the accompanying drawings and specific embodiments, but this is not intended to limit the disclosure.

[0028] To improve the automation level and unloading efficiency of ship unloaders, this disclosure provides a material handling method and an unloading system for ship unloaders.

[0029] Figure 1 A schematic flow diagram of a material handling method 100 for a ship unloader according to an embodiment of this disclosure is shown. Method 100 includes steps S1-S4. Any one or more steps in method 100 can be performed by, for example... Figure 6 The electronic device 600, or any device of the unloading system disclosed herein, can be used to achieve this.

[0030] In S1, information about the ship's hold and the materials located within the hold is obtained. The ship's hold information includes the coordinates of the hold, and the material information includes the surface features of the materials.

[0031] The ship unloader mainly consists of a trolley, a horizontal conveyor system, and a vertical reclaiming system. The trolley moves horizontally across the dock. The horizontal conveyor system, for example, is a belt conveyor that transports materials horizontally to the dock. The vertical reclaiming system is used to grab and move materials located in the ship's hold. The vertical reclaiming system uses a hydraulic motor-driven scraper to retrieve materials from the hold and transfer them to the horizontal conveyor system.

[0032] Information about the ship's hold and materials can be acquired through various data acquisition devices. The ship's hold information includes its coordinates, its external layout when opened, and the position of its bulkheads. Material information includes surface characteristics such as surface contours and material level at different locations.

[0033] The data acquisition device includes a lidar system. A lidar unit can be installed on top of the unloader to scan the entire ship hold and surrounding objects from above. This top location can be below the main beam or on either side of the top of the vertical arm. The lidar constructs a 3D or 2D point cloud map of the surrounding environment by emitting laser beams and measuring the return time, enabling environmental perception and obstacle detection. Before unloading begins, the lidar can initiate a horizontal scan of the ship hold and the materials within it. Alternatively, a gimbal can be activated to drive the lidar for a comprehensive scan of the ship hold and its materials. The lidar's scanning frequency can be 5-15Hz, with a resolution of 0.0625°-1° and a scanning angle of 360°.

[0034] Data acquisition equipment may also include sensors such as cameras and ultrasonic radar. Cameras are mounted on the front of the unloader's boom to collect data on the ship's hold, cargo, and the position and orientation of the material handling device. The camera controller receives instructions from the PLC and controls the corresponding camera to enter working mode. The camera pan-tilt unit dynamically adjusts its posture based on the unloader's real-time posture data to ensure optimal monitoring visibility. Distributed ultrasonic ranging devices are deployed in the motion interference risk zone of the unloader's main structure to measure the distance parameters between the equipment body and the working surface (including static obstacles such as ship bulkheads and other dock equipment) in real time. The system triggers motion interlock control plans through graded distance thresholds to achieve active collision avoidance.

[0035] In S2, multiple candidate paths for the material handling device of the ship unloader from the starting position to the target position are obtained. The material handling device is a scraper material handling device installed on the vertical arm of the ship unloader.

[0036] In some examples, the material handling device is a scraper reclaiming mechanism. Material in the hold sequentially enters the scraper reclaiming mechanism, and is then transported to the dockside machinery via a vertical lifting mechanism and a horizontal scraper conveyor. Compared to grab buckets, the vertical scraper reclaiming mechanism uses a hydraulic motor to drive the scraper conveyor, allowing for continuous operation and thus higher unloading efficiency. Furthermore, the reclaiming mechanism can operate close to the bottom of the hold, resulting in less material residue. Additionally, the entire reclaiming and transport process is conducted in a closed system, eliminating dust pollution.

[0037] Based on the acquired information about the ship's hold and the materials, the working area of ​​the material handling device can be determined. In some examples, the working area can be divided into multiple sub-areas. The material handling device can operate within these sub-areas. Multiple candidate paths for the material handling device from its starting position to its target position can be preset. The starting position can be the position before the material handling device enters the ship's hold; the starting position can be a fixed position. The target position can be the material handling device's ending point, and the target position can be determined according to the operational rules, such as the material handling point of a certain grid in the current ship's hold, or the material handling point of the last grid in the current ship's hold to be handled, etc.

[0038] Each of the multiple candidate paths represents a location point where the material handling device is located. For example, the material handling device may start from a starting position above the hull, or from a position within a specific sub-area. The actions of the vertical material handling device include boom rotation, vertical boom pitch and swing, and automatic lowering of the vertical boom.

[0039] In S3, the working path is selected from multiple candidate paths.

[0040] In different candidate paths, the movement sequence of the material-collecting device, or the dwell time at different collection points, varies. In some examples, within the current hold, the material-collecting device can collect material from sub-regions of the grid row by row. For instance, it might first collect material from the sub-region near the sea side. Once that side is complete, the movement sequence for the adjacent second row is reversed compared to the first row, meaning the movement sequence of adjacent rows is reversed. Another example is to first collect material from the sub-region near the sea side, and once that side is complete, move to the sub-region near the land side. When that side is finished, move to the middle sub-region for further collection. In some examples, material can be collected layer by layer. For instance, in sub-regions with higher material levels, the dwell time of the material-collecting device is longer or the collection speed is faster; in sub-regions with lower material levels, the dwell time is shorter or the collection speed is slower, keeping the remaining material at similar heights.

[0041] Different candidate paths have different objectives. For example, candidate path A has the shortest working time, candidate path B has the highest safety, and candidate path C is closest to the manual operation mode. A working path is selected from the candidate path dataset for subsequent material retrieval.

[0042] In S4, material handling is performed based on the work path.

[0043] The material handling action is executed based on a defined working path. "Executing material handling" here refers to sending a material handling instruction to the material handling device, which includes the working path of the material handling device.

[0044] In method 100, the ship's hold information and the information of the material located within the hold are first acquired, thereby obtaining data such as the coordinates of the hold and the surface characteristics of the material. Based on the information of the hold and the material, a dataset containing multiple candidate paths is determined, and a working path is selected from the multiple datasets. Material handling is performed based on the selected working path. Method 100 can automatically plan the working path of the material handling device according to the state of the ship and the material, and select the optimal working path by considering multiple factors, thereby providing automation efficiency and safety.

[0045] In some embodiments, method 100 may also include an update to the material handling method. For example, method 100 may further include steps S5-S6.

[0046] In S5, material loading information is obtained after each material retrieval is completed.

[0047] In S6, repeat steps S2-S4.

[0048] During the material handling process, the data acquisition device collects the status of the work area in real time. As material handling progresses, the remaining work area can be adjusted based on the areas that have been cleared. For example, when the task in a certain work area is completed, the relative coordinates of the equipment with respect to the ship's hold are recorded, and the sub-map of that work area in the global map is updated. In some examples, the update of the material handling method can be performed when the material handling device finishes handling at a certain target location, or it can be performed when the material handling device has been working at a certain target location for a period of time.

[0049] In some implementations, acquiring information about the ship's hold and materials in S1 includes acquiring three-dimensional scan data of both. Specifically, method 10 may include the following sub-steps S11-S14, which can be found in [reference needed]. Figure 2 .

[0050] In S11, the positions of the material handling device and the data acquisition device are obtained.

[0051] The position of the material handling device on the vertical boom can be determined using sensors mounted on it. These sensors can detect the boom's pitch and swing angles. Here, the position of the material handling device refers to its position relative to the dock's coordinate system. The dock's coordinate system can be determined using the BeiDou Navigation Satellite System.

[0052] To determine the location of the data acquisition device, it can first be calibrated on the vertical arm to obtain the position of the LiDAR relative to the material handling device on the vertical arm. Then, the position of the data acquisition device relative to the material handling device on the vertical arm can be converted into the position in the dock coordinate system.

[0053] In S12, three-dimensional scan data of the ship's hold and materials are acquired from the data acquisition device.

[0054] As mentioned earlier, the data acquisition device includes one or more of lidar, cameras, and ultrasonic radar. Lidar is used to perform a full-angle scan of the ship's cabin at a fixed frequency to acquire point cloud data. The point cloud data contains XYZ coordinates and intensity values. In some examples, filtering algorithms can be used to filter the acquired point cloud data to remove outliers and noise points. In some examples, a pre-stored ship database can also be retrieved and fitted to the point cloud data.

[0055] Point cloud data comprises a set of vectors in three-dimensional coordinates. In the operational scenario of a scraper unloader, these vectors can represent discrete points on the surfaces of various objects in the environment surrounding the unloader, such as buildings on the dock, stacked cargo, and other equipment. The three-dimensional coordinates of these surface feature points constitute the point cloud data.

[0056] In S13, a point cloud model is built based on the 3D scan data.

[0057] The acquired point cloud data can be processed, registered, and stitched to create a point cloud model. This point cloud model can include ships and shore-based unloaders. Triangulation can be used on the point cloud model, forming triangular patches by connecting representative points in voxels to generate a 3D mesh model. In some examples, the modeling algorithm is the Unity 3D algorithm. In some examples, the triangulation method is, for example, Delaunay triangulation or TIN triangulation.

[0058] In S14, the point cloud model is processed to identify the boundaries of the cabin and the surfaces of materials.

[0059] For the ship's hold, surface fitting can be performed on the point cloud data related to the hold to identify structures such as hold boundaries and bulkheads. For materials, the height gradient of the point cloud data can be calculated, the density distribution of the accumulated materials can be analyzed, and the contour features of the accumulated materials can be extracted. The boundaries of the hold and the surface of the materials can define the working area of ​​the unloader's material handling device.

[0060] S1 utilizes a sensor network to acquire the positions of the ship's hold and materials, enabling real-time acquisition of the three-dimensional coordinates and boundary information of the hold and materials. The three-dimensional mesh model boasts a mesh accuracy of up to 10cm*10cm, with an error controllable within 5cm.

[0061] In some implementations, the identified work area can be divided to refine the material handling process. Specifically, S1 also includes steps S15-S16.

[0062] In S15, the work area is identified based on the boundaries of the cabin and the surface of the materials.

[0063] The coordinates of the hold boundaries and the material surface can be calculated. The working area of ​​the material handling device can then be determined based on the range defined by these coordinates.

[0064] In S16, the work area is divided into multiple sub-work areas.

[0065] Multiple work points are pre-set based on the ship's loading status, hold layout, and material distribution. During the operation, the unloading area of ​​the hold can be divided into N different zones, and the unloader can select from N different zones to carry out the operation.

[0066] In some examples, the work area can be divided into basic grid cells, each assigned unique spatial coordinates. Spatial mapping of material surface feature data within each grid cell allows for the statistical analysis of material height data for that cell. Key feature points in each grid cell can be extracted, and characteristic parameters such as grid center coordinates, average height, and highest and lowest point parameters can be calculated. Furthermore, spatial relationships between grid cells can be established to generate a complete work area model.

[0067] In some implementations, the point cloud data in S1 can also be rendered. For example, S1 may also include steps S15-S16.

[0068] In S15, point cloud data images are rendered based on the point cloud model.

[0069] Rendering refers to mapping each point in a point cloud dataset, containing three-dimensional coordinate information, onto a two-dimensional plane according to certain rules. Furthermore, the color or grayscale value of each point in the image can be determined based on its intensity. For example, in a point cloud dataset representing a material pile, points near the top of the pile, being closer to the sensor, have higher reflectivity and will appear as brighter colors or higher grayscale values ​​in the rendered image. Points at the bottom of the pile, being partially occluded or relatively far from the sensor, have lower reflectivity and will appear as darker colors or lower grayscale values ​​in the rendered image. In this way, the entire point cloud dataset is converted into a rendered point cloud image that visually represents the environment surrounding the ship unloader.

[0070] In S16, obstacle detection is performed on the point cloud data image.

[0071] Obstacle prediction algorithms are used to detect obstacles in point cloud rendered images. Obstacles include, for example, structures on a ship's deck, personnel, other cargo piles, dock buildings, etc.

[0072] Figure 3 A flowchart illustrating a method 20 for obtaining multiple candidate paths for a material handling device according to an embodiment of the present disclosure is shown. Method 20 includes steps S21-S23.

[0073] In S21, multiple candidate paths are obtained based on multiple different objectives.

[0074] The starting point of each candidate path is the initial position of the material handling device, for example, the position before the scraper material handling device enters the ship's hold. Each candidate path includes a target position. When the material accumulation in the ship's hold is relatively uniform, such as when the cargo ship has just arrived at port or after material has been being handled layer by layer for some time, the target position of the material handling device can be randomly determined. When the material surface exhibits significant undulations, such as after random material handling for some time, if the handling is consistently concentrated in one spot, the ship's center of gravity will shift, potentially leading to capsizing, and it will also be detrimental to unloading efficiency. In some examples, the material accumulation state can be determined based on the height coordinates of the material in the 3D mesh model. Based on the material accumulation state, the position with the highest height coordinates is preferentially set as the target position of the unloader's material handling device.

[0075] During the material handling process, different candidate paths may have different objectives, and these objectives may conflict with each other. For example, candidate path P1 may have the shortest material handling time, candidate path P2 may have the lowest collision risk, and candidate path P3 may have the lowest equipment wear. Candidate paths can be determined based on different objectives. Various multi-objective algorithms can be used to determine multiple candidate paths, such as the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm.

[0076] In S22, spatial optimization is performed on each of the multiple candidate paths.

[0077] Each candidate path can include a series of discrete points, where unnatural sharp turns may occur at the corners. To improve the smoothness of the path in space, the initial candidate paths can be processed. For example, interpolation can be used to generate smooth curves, making the material handling device more stable when turning.

[0078] In some examples, S22 includes steps S221-S222.

[0079] In S221, for each candidate path, multiple three-dimensional spatial points are determined.

[0080] For each candidate path, multiple 3D spatial points are used to determine the curve. These 3D spatial points serve as control points, ensuring that the candidate path satisfies geometric constraints while also meeting requirements such as curvature continuity and natural transitions. In some examples, the number of 3D spatial points is 5-10. The more 3D spatial points there are, the higher the degrees of freedom of the resulting curve, and consequently, the greater the computational load. Therefore, the number of 3D spatial points needs to be controlled within a reasonable range. In a scraper unloader, the actions include boom rotation, vertical boom pitch and swing, automatic vertical boom descent, and the starting and target positions, thus requiring at least 5 points. If each action is isolated, at least 10 points are needed. This approach ensures the degrees of freedom of the curve while reducing the computational load.

[0081] In S222, the positions of multiple three-dimensional spatial points are adjusted to perform smooth optimization for each candidate path.

[0082] In some examples, Bézier curves can be used, which optimize each candidate path by adjusting the position of points in three-dimensional space, so that each candidate path reaches the optimal and more closely resembles the actual operation trajectory.

[0083] In S23, multiple optimized candidate paths are obtained.

[0084] By optimizing the spatial location of each of the multiple candidate paths, multiple optimized candidate paths are obtained.

[0085] Method 20 considers multiple objectives to generate multiple candidate paths and optimizes the spatial location of each candidate path. The optimized candidate path set can be used to select the working path.

[0086] In some examples, multi-objective particle swarm optimization can be used again to select the working path from multiple optimized candidate paths. For instance, an adaptive weighting mechanism can be used to increase the inertia weight in the early stages of computation to enhance overall search capability, and decrease the weight in the later stages of computation to focus on local optimization. The optimized paths are then filtered by comprehensively considering preset weights (such as job efficiency and safety) to determine the final global path.

[0087] In some examples, the working path can be adjusted locally. Figure 4 A flowchart illustrating a working path update method 30 according to an embodiment of this disclosure is shown. Method 30 includes steps S31-S33.

[0088] In S31, a local region on the working path is obtained, which is the area where a sudden obstacle is detected.

[0089] Fine-tuning is performed on a localized area within the selected work path. This localized area refers to the region where sudden obstacles are detected. Sudden obstacles could be, for example, clearance equipment detected by data detection devices. In some examples, a path safety boundary threshold can be set to identify obstacles.

[0090] In S32, local areas are adjusted to prevent collisions in those areas.

[0091] In some examples, artificial potential field algorithms can be used to adjust local areas to ensure the safety of unloading equipment and prevent collisions.

[0092] In S33, obtain the updated working path.

[0093] The updated working path is obtained based on the adjusted local region.

[0094] In some examples, the updated work path can be previewed and simulated after it has been determined and before the material picking action is performed. Figure 5 A flowchart illustrating a pre-running method 40 for a working path according to an embodiment of this disclosure is shown. Method 40 includes steps S41-S43.

[0095] In S41, import the updated working path.

[0096] In some examples, the updated working path can be imported into the EMED simulation system to preview the updated working path.

[0097] In S42, collision risks on the updated work path are detected and compared with safety thresholds.

[0098] Detect collision risks on the updated work path and compare the detected collision risk in a certain area with the corresponding safety threshold.

[0099] In S43, the control parameters of the ship unloader are adjusted based on the comparison results.

[0100] When the collision risk in a certain area exceeds a safety threshold, the control parameters of the ship unloader are dynamically adjusted. For example, if the collision risk at a certain bend exceeds 30%, the acceleration of the trolley can be reduced. Although the total time will increase, the collision risk can be reduced to a lower level. Another example is that if the distance between the material handling device and the hatch cover is too small, the height of the material handling device can be raised. Although this results in a longer working path, it improves safety. Yet another example is that if the distance between the material handling device and the edge of the hatch is small, the range of motion of the material handling device can be reduced to bring it closer to the center of the hatch. Although this increases the amount of material cleared, it improves safety.

[0101] Figure 6 A schematic diagram of an exemplary electronic device 600 according to an embodiment of the present disclosure is shown. The electronic device 60 includes at least one processor 610 and a memory 620 coupled to the at least one processor 610. The memory 620 is used to store computer-executable instructions that, when executed, cause the processor 610 to perform the methods in the above embodiments (e.g., any one or more steps of the foregoing methods 100, 10, 20, 30, 40).

[0102] The processor 610 is the control center of the electronic device. It can connect to various parts of the electronic device through various interfaces and lines. It can set up resources by running or executing instructions stored in the memory 620 and calling data stored in the memory 620.

[0103] Optionally, processor 610 may include one or more processing units. In some examples, processor 610 and memory 620 may be implemented on the same chip; in some embodiments, they may be implemented on separate chips.

[0104] The processor 610 can be a general-purpose processor, such as a central processing unit (CPU), digital signal processor, application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this disclosure. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this disclosure can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0105] Memory 620, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory 620 may include at least one type of storage medium, such as flash memory, hard disk, multimedia card, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), magnetic memory, magnetic disk, optical disk, etc. Memory 620 can be any other medium capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer, but is not limited thereto. Memory 620 in this embodiment of the disclosure may also be a circuit or any other device capable of implementing storage functions for storing program instructions and / or data.

[0106] Based on the same technical concept, this disclosure also provides a computer-readable storage medium storing a computer-executable program for causing a computer to perform the unloading method of the ship unloader listed in any of the above methods.

[0107] This disclosure also proposes a computer program product tangibly stored on a computer-readable storage medium and including computer-executable instructions that, when executed, cause at least one processor to perform the unloading method of the ship unloader listed in any of the above embodiments.

[0108] An embodiment of this disclosure also provides a ship unloading system, including the ship unloader described above, a data acquisition device, and a control unit. The control unit is used to execute the methods described above (e.g., any one or more steps of the aforementioned methods 100, 10, 20, 30, and 40).

[0109] Furthermore, although exemplary embodiments have been described herein, their scope includes any and all embodiments based on this disclosure that have equivalent elements, modifications, omissions, combinations (e.g., schemes involving intersections of various embodiments), adaptations, or alterations. Elements in the claims will be interpreted broadly based on the language used in the claims and are not limited to the examples described in this specification or during the implementation of this disclosure, which will be interpreted as non-exclusive. Therefore, this specification and examples are intended to be considered illustrative only, and the true scope and spirit are indicated by the various claims in the claims and the full scope of their equivalents.

[0110] The above description is intended to be illustrative and not restrictive. For example, the above examples (or one or more thereof) can be used in combination with each other. Other embodiments can be used by those skilled in the art when reading the above description. Furthermore, in the above specific embodiments, various features may be grouped together to simplify this disclosure. Features disclosed that are not claimed in the claims are not essential to any claim. Rather, the subject matter of this disclosure may be less than all the features of a particular disclosed embodiment.

[0111] Therefore, the claims are incorporated herein by way of example or embodiment, wherein each claim is an independent, separate embodiment, and these embodiments are contemplated to be combined with each other in various combinations or arrangements. The scope of protection of this disclosure should be determined by reference to the appended claims and the full scope of their equivalents.

Claims

1. A method for unloading materials using a ship unloader, comprising: Acquire information about the ship's hold and the materials located within the ship's hold, wherein the information about the ship's hold includes the coordinates of the ship's hold and the information about the materials includes the surface features of the materials; Obtain multiple candidate paths from the starting position to the target position for the material handling device of the ship unloader, wherein the material handling device is a scraper material handling device installed on the vertical arm of the ship unloader. Select a working path from the plurality of candidate paths; as well as Material retrieval is performed based on the described work path.

2. The material handling method of the ship unloader according to claim 1, wherein, Obtaining information about the ship's hold and the materials located within the hold includes: Obtain the position of the material handling device and the position of the data acquisition device; The data acquisition device acquires three-dimensional scan data of the cabin and the materials. Based on the aforementioned 3D scan data, a point cloud model is established; and The point cloud model is processed and the boundaries of the cabin and the surface of the material are identified.

3. The material handling method of the ship unloader according to claim 2, wherein, Also includes: The work area is identified based on the boundaries of the cabin and the surface of the material; as well as The work area is divided into multiple sub-work areas.

4. The material handling method of the ship unloader according to claim 2, wherein, It also includes rendering point cloud data images based on the point cloud model; and performing obstacle detection on the point cloud data images.

5. The material handling method of the ship unloader according to claim 1, wherein, Obtaining multiple candidate paths for the unloader's material handling device from the starting position to the target position includes: The multiple candidate paths are obtained based on multiple different objectives; Optimize the spatial location of each of the plurality of candidate paths; and Obtain multiple optimized candidate paths.

6. The material handling method of the ship unloader according to claim 5, wherein, Optimizing the spatial location of each of the plurality of candidate paths includes: For each candidate path, multiple three-dimensional spatial points are determined; and The positions of the multiple three-dimensional spatial points are adjusted to perform smooth optimization on each candidate path.

7. The material handling method of the ship unloader according to claim 6, wherein, The number of the multiple three-dimensional spatial points is 5-10.

8. The material handling method of the ship unloader according to claim 5, wherein, Selecting a working path from the plurality of candidate paths includes using a particle swarm optimization algorithm to select the working path from the plurality of optimized candidate paths.

9. The material handling method of the ship unloader according to claim 8, wherein, Also includes: Obtain a local region on the work path, where the local region is the area where a sudden obstacle is detected; Adjust the local area to prevent collisions in the local area; as well as Get the updated working path.

10. The material handling method of the ship unloader according to claim 9, wherein, Also includes: Import the updated working path; Detect the collision risk on the updated work path and compare the collision risk with a safety threshold; as well as The control parameters of the ship unloader are adjusted based on the comparison results.

11. An electronic device, comprising: At least one processor; as well as A memory for storing computer-executable instructions that, when executed, cause the at least one processor to perform the material handling method of the unloader according to any one of claims 1-10.

12. A computer-readable storage medium having computer-executable instructions stored thereon for performing a material handling method of a ship unloader according to any one of claims 1-10.

13. A computer program product tangibly stored on a computer-readable storage medium and comprising computer-executable instructions that, when executed by at least one processor, cause at least one processor to perform the material handling method of the unloader according to any one of claims 1-10.

14. A ship unloading system, comprising: The ship unloader includes a trolley, a horizontal transport device, and a vertical material handling device, wherein the vertical material handling device is a scraper material handling device. Data acquisition device for detecting information about the ship's hold and the materials located within the ship's hold; as well as The control unit is configured to execute the material handling method of the unloader according to any one of claims 1-10.

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