Method and system for detecting rail defects

Abstract

A storage and fulfillment system is known in which stacks of storage containers are arranged in a grid storage structure. The containers are accessible from above by a load handling device running on a rail or track on the top of the grid storage structure. A method and system for detecting defects on a track or track on which a load handling device moves is provided.

Description

Technical Field

[0001] The present invention relates to a method and a system for detecting defects in a track or a rail on which a load handling device moves. Background Art

[0002] Some industrial and commercial activities require systems that can store and retrieve large quantities of different products. WO2015 / 185628A describes a storage and fulfillment system in which stacks of storage containers are arranged in a grid storage structure. The containers can be accessed from above by a load handling device running on a rail or a track on top of the grid storage structure.

[0003] To ensure the reliable operation of the storage and fulfillment system, it is important that the rail or the track is free of defects. It is in this context that the present invention has been devised. Summary of the Invention

[0004] A computer-executed method for determining a defect in a system is provided. The system includes a load handling device, a first set of tracks extending in a first direction, and a second set of tracks extending in a second direction transverse to the first direction. The load handling device is configured to move on the tracks. The load handling device includes a sensor configured to monitor the movement of the load handling device. The method includes: acquiring data generated by the sensor when the load handling device moves along the first set and / or the second set of tracks; determining that the data includes abnormal data; and identifying a defect in a region of the first set and / or the second set of tracks by mapping the abnormal data to the positioning data of the load handling device, wherein if the number of times the abnormal data is mapped to the positioning data corresponding to this region reaches a first threshold, the defect is identified. This means that defects in the system can be identified with a high degree of confidence.

[0005] The sensor can detect the vibration of the load handling device when the load handling device moves along the first set and / or the second set of tracks. This means that defects in the system will be detected by the sensor.

[0006] The sensor can include an accelerometer, an inertial measurement unit, a gyroscope, an encoder, or a torque sensor coupled to at least one wheel or axle of the load handling device. This means that data indicating system defects can be acquired.

[0007] Determining data abnormality includes detecting that the data deviates from the mode, median, or average value by a predetermined value, or exceeds a reference value. This means that data indicating system defects can be identified.

[0008] Data generated by the sensor during acceleration and deceleration of the loading handling device can be excluded so that when it is determined that the data includes abnormal data, the loading handling device is traveling at a constant speed. This means that only acceleration / deceleration due to system defects will be detected by the sensor.

[0009] The sensor can generate data only on an axis transverse to the direction of movement of the loading handling device. This reduces the data processing and / or storage burden when analyzing the data generated by the sensor.

[0010] The sensor can generate data on a first axis corresponding to a first direction, on a second axis corresponding to a second direction, and on a third axis transverse to the first and second directions. This improves the accuracy in detecting system defects.

[0011] The first threshold can be a numerical value or a percentage value, and optionally, the percentage value can include the ratio between the number of times abnormal data is mapped to the positioning data corresponding to the area and the number of times the positioning data corresponds to this area. This means that different usage scenarios can be considered when identifying system defects.

[0012] If the number of times the positioning data corresponds to the area reaches a second threshold, the defect can be verified. This ensures that the area has been sampled a sufficient number of times before identifying a system defect.

[0013] The system can include a plurality of loading handling devices, wherein, for the plurality of loading handling devices, if the number of times abnormal data is mapped to the positioning data corresponding to the area reaches a third threshold, the defect is verified. This increases the confidence in identifying the defect and excludes defective sensors and / or errors in processing data from the sensors.

[0014] For a plurality of loading handling devices, if the number of times the positioning data corresponds to the area reaches a fourth threshold, the defect can be verified. This ensures that the area has been sampled a sufficient number of times before identifying a system defect.

[0015] The system can include a plurality of loading handling devices, wherein the method can further include: determining the percentage of unique loading handling devices in the area where the data includes abnormal data to define a first value, and, if the first value exceeds a fifth threshold, verifying the defect in this area. This further increases the confidence in identifying the defect and excludes defective sensors and / or errors in processing data from the sensors.

[0016] The system may include a plurality of load handling devices, wherein the method may further include: determining a total number of unique load handling devices corresponding to the location data for a region to define a second value, and if the second value exceeds a sixth threshold, then verifying a defect in the region. This ensures that the region has been sampled a sufficient number of times before identifying a system defect.

[0017] Each of the second, third, fourth, fifth, and sixth thresholds may be reached to verify a defect in the region. This maximizes the confidence in identifying a defect.

[0018] The method may further include determining the type of defect by detecting a corresponding unique pattern in the data. This means that the nature of subsequent operations and / or repairs can be determined without first inspecting the system.

[0019] The type of defect may include at least one of the following: debris on the first and / or second set of tracks, misalignment along the first and / or second set of tracks and / or misalignment between the first set of tracks and the second set of tracks, damaged segments on the first and / or second set of tracks, and damaged intersections along the first and / or second set of tracks and / or damaged intersections between the first set of tracks and the second set of tracks. This means that the method is able to detect a wide variety of defects that adversely affect the reliable operation of the system.

[0020] The first and second sets of tracks may be in a substantially horizontal plane to form a grid, the grid including a plurality of grid spaces to form a plurality of vertical storage locations below the grid for allowing containers to be stacked vertically between uprights and to be guided vertically by the uprights through the plurality of grid spaces, and optionally, wherein the load handling device or each load handling device is configured to lift a container from a vertical storage location below the grid and / or lower a container to a vertical storage location. This means that the reliable operation of the system can be ensured.

[0021] The region may include a grid space. This means that it is possible to identify regions in the system where there are operational problems. The method may further include reconfiguring the system to avoid operating the load handling device in the grid space. This means that the system can operate in a manner that minimizes the risk of failure (e.g., the load handling device falling due to a defect in the grid space).

[0022] The data may include a plurality of average values, wherein each average value is derived from sensors when the load handling device moves over respective grid spaces. This helps to isolate the grid spaces where there are system defects.

[0023] The method is performed over a predefined time period. This means that it is possible to periodically evaluate and compare the system for defects.

[0024] The method may further include generating a map that indicates areas within the system that have defects. This means that defects within the system can be easily located.

[0025] A computer program including instructions is provided, where when the computer executes the program, the instructions cause the computer to implement the method described in the above aspects.

[0026] A data processing system including a processor is provided, where the processor is configured to implement the method described in the above aspects.

[0027] A system is provided that includes: a load handling device, a first set of tracks extending in a first direction, and a second set of tracks extending in a second direction transverse to the first direction, where the load handling device is configured to move on the tracks, and where the load handling device includes a sensor configured to monitor the movement of the load handling device; and The data processing system described in the above aspects.

[0028] A map is provided, where the map is generated using the method, the computer program, or the system described in the above aspects, and the map indicates areas within the system that have defects. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The present invention is described with reference to one or more exemplary embodiments depicted in the accompanying drawings, where: FIG. 1 shows a storage structure and a container; FIG. 2 shows tracks on top of the storage structure shown in FIG. 1; FIG. 3 shows a load handling device on top of the storage structure shown in FIG. 1; FIG. 4 shows a single load handling device with the container lifting tool in a lowered configuration; FIGS. 5A and 5B show cross-sectional views of a single load handling device with the container lifting tool in raised and lowered configurations; FIG. 6 shows a known load handling device, where X-direction and Y-direction position sensors are shown in the form of "fifth" wheels mounted thereon; Figure 7 A diagram showing a movement sensor and a positioning system for a load handling device according to an embodiment is shown; Figure 8 A communication between a load handling device and a main controller via a network according to an embodiment is shown; Figure 9 A method for determining defects in a system is shown, where the system includes tracks and a load handling device; Figure 10Illustrates a method for verifying defects in a system according to an embodiment, where the system includes tracks and a load handling device; Figure 11 Illustrates a method for determining defects in a system according to an embodiment, where the system includes tracks and a load handling device; and Figure 12 Illustrates a "heat" map indicating the location of defects in a system according to an embodiment. Detailed embodiments

[0030] Online retailers that sell multiple product lines, such as online grocers and supermarkets, need systems that can store tens of thousands or hundreds of thousands of different product lines. In such cases, using a single product stack may be impractical because it would require a very large floor area to accommodate all the required stacks. Additionally, only a small quantity of some items, such as perishable or infrequently ordered goods, may need to be stored, making a single product stack an inefficient solution.

[0031] International Patent Application WO 98 / 049075A (Autostore) describes a system in which stacks of multi-product containers are arranged within a framework structure, the content of this application being incorporated herein by reference.

[0032] PCT Publication No. WO2015 / 185628A (Ocado) describes a further known storage and fulfillment system in which stacks of containers are arranged within a grid frame structure. The containers can be accessed by one or more load handling devices (also referred to as "robots") running on tracks at the top of the grid frame structure. This type of system is schematically shown in FIGS. 1 to 3 of the accompanying drawings.

[0033] As shown in FIGS. 1 and 2, stackable containers 10, also referred to as "bins", are stacked on top of each other to form a stack 12. The stack 12 is arranged within a grid frame structure 14 in, for example, a warehousing or manufacturing environment. The grid frame structure 14 consists of a plurality of storage columns or grid columns. Each grid in the grid frame structure has at least one grid column for storing a stack of containers. FIG. 1 is a schematic perspective view of the grid frame structure 14, and FIG. 2 is a schematic top view showing the stack 12 of bins 10 arranged within the frame structure 14. Each bin 10 typically contains a plurality of product items (not shown). The product items within the bin 10 can be of the same or different product types, depending on the application.

[0034] The grid frame structure 14 includes a plurality of upright members 16 that support the horizontal members 18, 20. A first set of parallel horizontal grid members 18 are arranged in a grid pattern perpendicular to a second set of parallel horizontal members 20 to form a horizontal grid structure 15 supported by the upright members 16. The members 16, 18, 20 are typically made of metal. The bins 10 are stacked between the members 16, 18, 20 of the grid frame structure 14 such that the grid frame structure 14 prevents horizontal movement of the stack 12 of bins 10 and guides vertical movement of the bins 10.

[0035] The top layer of the grid frame structure 14 includes a grid or grid structure 15 that includes tracks 22 arranged in a grid pattern on top of the stack 12. Referring to FIG. 3, the tracks or rails 22 guide a plurality of load handling devices 30. A first set 22a of parallel tracks 22 guides movement of the robotic load handling devices 30 along a first direction (e.g., the X direction) on top of the grid frame structure 14. A second set 22b of parallel tracks 22 arranged perpendicular to the first set 22a guides movement of the load handling devices 30 along a second direction perpendicular to the first direction (e.g., the Y direction). In this way, the tracks 22 allow the robotic load handling devices 30 to move two-dimensionally laterally within the horizontal X-Y plane. The load handling devices 30 can be moved to a position above any stack 12.

[0036] PCT Patent Publication No. WO2015 / 019055 (Ocado) describes a known form of load handling device 30 as shown in FIGS. 4, 5A, and 5B, where each load handling device 30 covers a single grid space 17 of the grid frame structure 14, which is incorporated herein by reference. This arrangement allows for a higher density of load processors, resulting in a higher throughput for a system of a given size.

[0037] The loading handling device 30 includes a vehicle 32 which is arranged to travel on the track 22 of the framework structure 14. A first set of wheels 34, which consists of a pair of wheels 34 at the front of the vehicle 32 and a pair of wheels 34 at the rear of the vehicle 32, is arranged to engage with two adjacent tracks of the first set 22a of tracks 22. Similarly, a second set of wheels 36, which consists of a pair of wheels 36 on each side of the vehicle 32, is arranged to engage with two adjacent tracks of the second set 22b of tracks 22. Each set of wheels 34, 36 can be lifted and lowered so that either the first set of wheels 34 or the second set of wheels 36 engages with the respective set of tracks 22a, 22b at any time. For example, when the first set of wheels 34 engages with the first set of tracks 22a and the second set of wheels 36 is lifted off the track 22, the first set of wheels 34 can be driven by a drive mechanism (not shown) housed in the vehicle 32 to move the loading handling device 30 in the X direction. To effect movement in the Y direction, the first set of wheels 34 is lifted off the track 22 while the second set of wheels 36 is lowered to engage with the second set 22b of tracks 22. The drive mechanism can then be used to drive the second set of wheels 36 so as to move the loading handling device 30 in the Y direction.

[0038] The loading handling device 30 is equipped with lifting equipment, such as a crane mechanism, for lifting a storage container from above. The lifting equipment includes a winch tether or cable 38 wound around a reel or spool (not shown) and a clamping device 39. The lifting equipment shown in FIG. 4 includes a set of four lifting cables 38 extending in the vertical direction. The cables 38 are connected respectively at or near the four corners of the clamping device 39 (such as a lifting framework) for releasably connecting to the storage container 10. For example, the respective cables 38 are arranged at or near each of the four corners of the lifting framework. The clamping device 39 is configured to releasably clamp the top of the storage container 10 to lift the storage container from a stack of containers in a storage system of the type shown in FIGS. 1 and 2. For example, the lifting framework 39 may include pins (not shown) that mate with corresponding holes (not shown) in the edge, and sliding clamps (not shown) that can engage with the edge to clamp the box 10, where the edge forms the top surface of the box 10. The clamps are driven by a suitable drive mechanism to engage with the box 10, the drive mechanism being housed in the lifting framework 39 and powered and controlled by signals transmitted by the cable 38 itself or a separate control cable (not shown).

[0039] To remove the box 10 from the top of the stack 12, the loading handling device 30 is first moved in the X and Y directions to position the gripping device 39 above the stack 12. As shown in FIGS. 4 and 5B, the gripping device 39 is then vertically lowered in the Z direction to engage the box 10 at the top of the stack 12. The gripping device 39 grips the box 10 and is then pulled upward by the cable 38 together with the attached box 10. When traveling vertically to the top, the box 10 is held above the rail track 22 and is received within the vehicle body 32. In this way, the loading handling device 30 can be moved to different positions in the X-Y plane, carry the box 10 along with it and transport the box 10 to another location. Once reaching the target location (such as another stack 12, an access point of the storage system or a conveyor belt), the box or container 10 can be lowered from the container receiving portion and released from the gripping device 39. The cable 38 is long enough to allow the loading handling device 30 to retrieve and place the box from any level of the stack 12 (for example, including the floor level).

[0040] As shown in FIG. 4, a plurality of identical loading handling devices 30 are provided so that each loading handling device 30 can operate simultaneously to increase the throughput of the system. The system shown in FIG. 4 may include specific locations (referred to as ports) where the box 10 can be transported into or out of the system. An additional conveying system (not shown) is associated with each port such that the box 10 transported to the port by the loading handling device 30 can be transported to another location, such as a picking station (not shown), by the conveying system. Similarly, the box 10 can be moved from an external location to the port through the conveying system, such as moved to a box filling station (not shown), and transported to the stack 12 by the loading handling device 30 to replenish the inventory in the system.

[0041] Each loading handling device 30 can lift and move one box 10 at a time. The loading handling device 30 has a container receiving cavity or recess 40 in its lower part. As shown in FIGS. 5A and 5B, when the container 10 is lifted by the lifting mechanism, the recess 40 is sized to receive the container 10. When in the recess, the container 10 is lifted off the underlying rail track 22 so that the vehicle 32 can move laterally to different grid locations. If it is necessary to retrieve the box 10b ("target box") that is not at the top of the stack 12, the upper box 10a ("non-target box") must first be moved to allow access to the target box 10b. This is achieved by an operation hereinafter referred to as "digging". Referring to FIG. 3, during the digging operation, one of the loading handling devices in the loading handling device 30 sequentially lifts each non-target box 10a from the stack 12 containing the target box 10b and places it in an empty position within another stack 12. Then, the target box 10b can be accessed by the loading handling device 30 and moved to the port for further transportation.

[0042] Each of the provided loading handling devices 30 operates remotely under the control of a central computer. Each individual bin 10 in the system is tracked so that the appropriate bin 10 can be retrieved, transported, and replaced as needed. For example, during an excavation operation, the location of each non-target bin is recorded so that non-target bin 10a can be tracked.

[0043] Wireless communication and networks can be used to provide a communication infrastructure from a master controller to one or more loading handling devices operating on a grid structure, for example via one or more base stations. In response to receiving an instruction from the master controller, the controller in the loading handling device is configured to control various drive mechanisms to control the movement of the loading handling device. For example, the loading handling device can be instructed to retrieve a container from a target storage post at a specific location on the grid structure. The instructions can include various movements in the X-Y plane of the grid structure 15. As previously described, once at the target storage post, the lifting mechanism can be operated to grip and lift the storage container 10. Once the container 10 is received in the container receiving space 40 of the loading handling device 30, the container 10 is then transported to another location on the grid structure 15, such as a "drop-off port". At the drop-off port, the container 10 is lowered to a suitable picking station to allow any item to be retrieved from the storage container. The movement of the loading handling device 30 on the grid structure 15 can also include the loading handling device 30 being instructed to move to a charging station, which is typically located at the periphery of the grid structure 15. To maneuver the loading handling device 30 on the grid structure 15, each loading handling device 30 is equipped with motors for driving the wheels 34, 36. The wheels 34, 36 can be driven by one or more belts connected to the wheels, or by motors integrated into the wheels individually. For a single-unit loading handling device (where the coverage area of the loading handling device 30 occupies a single grid cell 17), due to limited available space within the vehicle body, the motors for driving the wheels can be integrated into the wheels. For example, the wheels of a single-unit loading handling device are driven by respective hub motors. Each hub motor includes an outer rotor with a plurality of permanent magnets, and the outer rotor is arranged to rotate around a hub including coils, and the coils form an inner stator.

[0044] The system described with reference to FIGS. 1 to 4 has many advantages and is applicable to a wide range of storage and retrieval operations. Specifically, it allows for very dense storage of products and provides a very economical way to store a large number of different items in bins 10, while also allowing for reasonably economical access to all bins 10 when picking is required.

[0045] In a storage system of the type shown in FIGS. 1-3, it is beneficial to determine the exact position of a given load handling device 30 operating on the grid structure 15. Each load handling device 30 is sent control signals, such as in the form of a motion control profile, to move along a predetermined path from one position to another position on the grid structure. For example, a given load handling device 30 can be instructed to move to a specific position in the grid structure 15 to lift a target container from a stack of containers at a specific location. When multiple such devices 30 move along their respective trajectories on the grid structure 15, it is beneficial to know the exact position of each given load handling device 30 (e.g., its exact position relative to the grid structure 15) so that the predetermined trajectories can be monitored in real time relative to the "actual" position of the corresponding load handling device 30. For example, one or more trajectories can be adjusted, and / or the control signals sent to the device 30 to follow the corresponding trajectory can be adjusted so that the device 30 arrives at the target position accurately enough and / or avoids other devices 30 following their respective trajectories.

[0046] FIG. 6 shows a known load handling device 30 with one or more position sensors 98a, 98b to measure the position of the load handling device relative to the grid structure 15. The position sensors 98a, 98b each include a so-called "fifth" wheel, that is, an additional fifth wheel exists among each set of wheels in the first set and the second set of wheels, respectively, for monitoring the position of the load handling device on the grid structure in the first direction and in the second direction.

[0047] As shown in FIG. 6, the first "fifth" wheel 98a is mounted adjacent to one of the wheels in the first set of wheels 34, and the second "fifth" wheel 98b is mounted adjacent to one of the wheels in the second set of wheels 36. The first "fifth" wheel 98a corresponding to the first position sensor is configured to engage with the track (or "rail") 22 when the load handling device 30 travels in the first direction, so that the rotation of the first "fifth" wheel indicates the position and travel direction of the load handling device 30 relative to time. Similarly, the second "fifth" wheel 98b corresponding to the second position sensor is configured to engage with the track 22 when the load handling device 30 travels in the second direction, so that the rotation of the second "fifth" wheel indicates the position and travel direction of the load handling device 30 in the second direction relative to time. The first direction and the second direction can be the X and Y directions along the track 22, respectively.

[0048] In FIG. 6, each of one or more position sensors 98a, 98b includes an incremental encoder that includes a rotating electromechanical device that generates pulses as the respective "fifth" wheel rotates. For example, for a predetermined angular rotation amount of the "fifth" wheel, pulses are generated. Thereby, the pulses indicate the position and the direction of rotation of the "fifth" wheels 98a, 98b, and the position and the direction of rotation can be converted into the displacement of the load handling device 30 relative to the grid structure 15. The "fifth" wheels are mounted on the arm and are biased downward to engage with the tracks 22 of the grid structure 15. As an alternative to the "fifth" wheels 98a, 98b, an incremental encoder can be used to generate pulses when any one of the wheels of the sets of wheels 34, 36 rotates to determine the position of the load handling device 30.

[0049] The reliable operation of the storage and fulfillment system described above with reference to FIGS. 1 to 6 depends on the unobstructed movement of the load handling device along the tracks. In practical applications, the tracks may have defects that impede the movement of the load handling device. For example, debris (such as metal fragments, nuts or bolts) may get stuck in the tracks. Additionally, the first set and / or the second set of tracks may be misaligned. In other words, a set of tracks in the X direction (or Y direction) may no longer be parallel to an adjacent set of tracks in the X direction (or Y direction), or the first set and the second set of tracks may no longer be perpendicular. Similarly, segments of the tracks in the X direction (or Y direction) may be misaligned. For example, the guides on the tracks for the wheels of the load handling device may be deformed or bent inward, causing the sides of the wheels of the load handling device to experience greater friction as they pass through the deformed segment. As another example, the intersection points may be damaged, where the intersection points are the points where the X-direction tracks and the Y-direction tracks intersect and are joined by nuts / bolts, welding, or any suitable connection means. A segment of the tracks in the X direction (or Y direction) may break away from the intersection point (possibly due to the failure of the connection means), causing the load handling device to drop as it moves towards the intersection point and then to rise steeply (or jitter upward) when it moves onto the intersection point. Similarly, a segment of the tracks in the X direction (or Y direction) may move upward, causing the load handling device to rise as it moves towards the intersection point and then to drop suddenly (or jitter downward) when it moves onto the intersection point.

[0050] To ensure the reliable operation of the storage and fulfillment system, it is important to identify any such defects. Due to the large size of the horizontal grid structure 15 and the large number of load handling devices, it is difficult and almost impossible to directly detect any such defects by visual inspection or indirectly by cameras. Additionally, the defects may be minor and not easily identifiable, but may still have an adverse impact on the reliable operation of the storage and fulfillment system. A method and system for detecting track defects are needed.

[0051] Figure 7Figure 200 shows a schematic diagram corresponding to the loading handling device 30 of the present invention. One or more encoders 210 are used for a plurality of wheels of the loading handling device. As described above, one or more encoders 210 are used to detect the positioning of the loading handling device on the horizontal grid structure 15. In this embodiment, one or more encoders are located within the loading handling device. In Figure 7 only a pair of wheels 234 for moving the loading handling device 30 in the X direction on the grid structure 115 are shown. However, a complete set of wheels for each of the X and Y directions, i.e., the first set 134 and the second set 136 of wheels described in the previous embodiment, may also be included.

[0052] In addition, at least one movement sensor 220 is used to monitor the movement of the loading handling device. The output of the movement sensor 220 indicates whether the loading handling device is moving unobstructed and "normally" along the horizontal grid structure 15. The movement sensor 220 also indicates whether the movement of the loading handling device is "abnormal" due to being obstructed by a defect on the horizontal grid structure 15. More generally, the movement sensor is configured to monitor the movement of the loading handling device when it moves along the first set and / or the second set of tracks and generate data that can be used to distinguish between "normal" and "abnormal" movements of the loading handling device. How to use the data from the movement sensor 220 to distinguish between "normal" and "abnormal" will be described in more detail below. The sensor can take the form of an accelerometer, an inertial measurement unit, a gyroscope, an encoder, or a torque sensor coupled to at least one wheel or axle of the loading handling device.

[0053] Although in Figure 7 the encoder 210 and the movement sensor 220 used to determine the position are shown as separate elements, it can be understood that the encoder can also be configured to monitor the movement. For example, the encoder can detect a pattern associated with the "normal" movement of the loading handling device, and a deviation from the expected pattern indicates an "abnormal" movement of the loading handling device. In other words, a single sensor can be used to detect the positioning of the loading handling device and monitor its movement. The loading handling device 200 can use a processor 240 to process the data from the encoder 210 and the movement sensor and store this data in a memory 230. The data in the memory 230 can be transmitted periodically through one or more networks (such as a base station) for further processing.

[0054] Figure 8 It is shown that each loading handling device transmits data to the computing device 174 through the network 176. Therefore, the data related to the monitored movement and positioning of each loading handling device 30 on the horizontal grid structure 15 is acquired by the computing device 174.

[0055] Figure 9shows the steps of a method 900 for determining defects in a system. The system includes a loading handling device 30, a first set of tracks 17 extending in a first direction, and a second set of tracks 19 extending in a second direction transverse to the first direction, the loading handling device being configured to move on the tracks, wherein the loading handling device includes a sensor (e.g., Figure 7 the sensor shown) configured to monitor the movement of the loading handling device. In step 910, data generated by the sensor as the loading handling device moves along the first and / or second set of tracks is acquired. The data can be acquired by a computing device 174, which then implements Figure 9 the method. In step 920, the data is analyzed and it is determined that the data includes abnormal data. In other words, at least one subset or portion of the data indicates that a section of the first and / or second set of tracks obstructs the movement of the loading handling device. How the obstruction of the movement of the loading handling device is determined from the data is described in more detail below. In step 930, by mapping the abnormal data to the positioning data of the loading handling device, a defect in an area (e.g., a grid space) of the first and / or second set of tracks is identified, wherein if the number of times the abnormal data maps to the positioning data corresponding to this area (e.g., the data generated as described above in connection with FIG. 6) reaches a first threshold, the defect is identified. In other words, if an area of the horizontal grid structure causes the loading handling device to have abnormal movements multiple times, this area stores a defect. The mapping process can be achieved by using the data generated by the movement sensor 910 and the timestamps on the positioning data. Alternatively, the data generated by the movement sensor 210 and the positioning data can be periodically combined as the data is generated.

[0056] The first threshold can be set considering different factors, such as the time period for analyzing the data, the number and length of trips or travels of the loading handling device, and the size of the horizontal grid structure 15. For example, if the loading handling device is involved in a large area of the horizontal grid structure 15 multiple times a day, the threshold can be set higher because it can be assumed that the loading handling device will visit the area multiple times, and thus a defect should be detected each time it visits. The first threshold can be a numerical value or a percentage value, where the percentage value includes the ratio of the number of times the abnormal data maps to the positioning data corresponding to the area to the number of times the positioning data corresponds to this area. The first threshold can be set according to the actual situation and is used to indicate the confidence level that a defect actually exists. If the first threshold is not used and only the mapping of abnormal data to positioning data is used, other reasons for the abnormal data cannot be excluded. Other reasons include abnormal readings caused by vigorously lifting / lowering containers in adjacent areas during normal operation, or inaccurate data recording by the movement sensor 220. Of course, it should be understood that using the first threshold is not mandatory, and the mapping of abnormal data to positioning data alone can also be used to mark any potential defects.

[0057] Assuming there are segments without defects in the first and / or second set of tracks, the movement sensor 210 of the load handling device moving along this segment will record a data range belonging to a normal distribution. In an embodiment where the movement sensor 210 is an accelerometer, the acceleration data recorded on each axis (along the X direction, Y direction, and the Z direction transverse to the X and Y directions) should belong to a normal distribution. Theoretically, when the load handling device moves at a constant speed, the accelerometer should record zero acceleration along the X and Y directions. Similarly, due to gravity, the Z axis should experience a constant acceleration, but it can also be corrected to zero. Therefore, the reference data used to derive the normal distribution can also exclude the acceleration and deceleration phases of the load handling device and only include the data generated when the load handling device moves at a constant speed. This means that any detected vibration or acceleration is due to a defect. It is understandable that the normal distribution can be derived using multiple different track segments. It is also understandable that any one of the acceleration axes can be used to generate the normal distribution. Alternatively, the data from all axes can be summed or averaged to generate the normal distribution.

[0058] After generating the normal distribution, the data obtained from the movement sensor 210 on any segment of the first and / or second set of tracks can be compared with the normal distribution. Given that the normal distribution is derived to only include the data generated when the load handling device moves at a constant speed, the data obtained from the movement sensor 210 can be filtered so as to only include the data generated when the load handling device moves at a constant speed (on any segment of the first and / or second set of tracks). The comparison can be based on the average readings from the movement sensor derived over a time period (such as the time period typically required to move over a grid space). Similarly, the comparison can be based only on the axis transverse to the direction of movement, where the axis corresponds to one of the X direction, Y direction, or Z direction. This can reduce the amount of data that needs to be accumulated and compared with minimal impact on accuracy. For example, if the load handling device travels along the Y direction, the X-direction sensor axis (and vice versa) should detect the lateral movement generated by the rocking motion due to deformation or bending or debris. Similarly, by only using the Z-direction sensor axis, the bumps on the track due to debris or sudden rises / drops can be detected. Therefore, a specific axis can be analyzed separately to determine the nature of the defect. Alternatively, the data from any two axes or all axes can be compared to maximize accuracy while still retaining the data from a single axis to determine the nature of the defect. More generally, any axis capable of detecting the vibration of the load handling device can be used.

[0059] Therefore, any data outside the normal distribution obtained from the mobile sensor 210 on any segment of the first set and / or the second set of tracks can be classified as abnormal. Although the option considered to be outside the normal distribution can be freely selected, it can be, for example, a value that is an integer number of standard deviations outside the normal distribution. In other words, determining data abnormality includes detecting that the data deviates from the mode, median, or average by a predetermined value. Similarly, determining data abnormality includes detecting that the data is out of range and its absolute value. (Or its distance to 0, where 0 is the mode, median, or average of the normal distribution). Similarly, the normal distribution provides a reference value by which abnormal data can be determined. Although the above has described a specific embodiment of the accelerometer, it is understood that an inertial measurement unit, gyroscope, encoder (as described above in connection with Figure 7 ), or torque sensor coupled to at least one wheel or axle of the load handling device can also be used to generate the normal distribution or reference value. Generally, any sensor capable of detecting the vibration of the load handling device can be contemplated.

[0060] In addition, each defect can produce a "signature" vibration pattern, so it is conceivable that the type of defect can be identified by analyzing the presence of the "signature" in the data. In other words, a specific defect will be reflected as a corresponding unique pattern in the data. For example, once enough data has been collected and analyzed, it can be inferred that debris on the first set and / or the second set of tracks produces a first unique pattern in the data, misalignment along the first set and / or the second set of tracks and / or between the first set of tracks and the second set of tracks produces a second unique pattern in the data, a damaged segment on the first set and / or the second set of tracks produces a third unique pattern in the data, and a damaged intersection along the first set and / or the second set of tracks and / or between the first set of tracks and the second set of tracks produces a fourth unique pattern in the data. This means that the type of defect can be determined without having to inspect the system first.

[0061] Figure 10 illustrates a method 1000 for verifying a defect determined by the Figure 9 method. In step 1010, the method of Figure 9 can be improved by ensuring that the load handling device has "sampled" the area a sufficient number of times. Even if the first threshold has been reached, it may be based on an insufficient sample size. A second threshold can be used to ensure that the area has been sufficiently sampled. The second threshold can be set considering different factors, such as the time period for analyzing the data and the size of the horizontal grid structure 15. Therefore, if the number of times the positioning data corresponds to the area reaches the second threshold, the defect is verified. It should be understood that in addition to using the second threshold to verify the defect, it may also be necessary to reach both the first threshold and the second threshold before identifying the defect.

[0062] Defects can be further verified by obtaining data from all loading handling devices on the horizontal grid structure 15 at 1020.

[0063] In step 1030, for a plurality of loading handling devices, if the number of times the abnormal data is mapped to the positioning data corresponding to the area reaches a third threshold, the defect is verified. The third threshold can be set considering different factors, such as the time period for analyzing the data, the number of loading handling devices, and the size of the horizontal grid structure 15. The third threshold can be a numerical value or a percentage value, where the percentage value includes the ratio between the number of times the abnormal data is mapped to the positioning data corresponding to the area and the number of times the positioning data corresponds to this area. The third threshold can be set according to the actual situation and is used to indicate the confidence level that a defect actually exists. In step 1040, a fourth threshold can be used to ensure that the area has been sufficiently sampled. The fourth threshold can be set considering different factors, such as the time period for analyzing the data, the number of loading handling devices, and the size of the horizontal grid structure 15. Thus, for a plurality of loading handling devices, if the number of times the positioning data corresponds to the area reaches the fourth threshold, the defect is verified. It should be understood that in addition to using either or both of the third and fourth thresholds to verify the defect, it may also be necessary to reach all of the first, second, third, and / or fourth thresholds before a defect is identified.

[0064] In step 1050, a first value is defined using the percentage of unique load handling devices in the area for which the data includes anomalous data. In other words, for all the different load handling devices in operation, it is determined how many of the load handling devices in the area have produced anomalous data. The more unique load handling devices that are detected to have anomalous movement, the more certain it is that there is a defect. Other causes, such as a malfunction of the movement sensor 210 or a data transmission error, are less likely to occur on multiple unique load handling devices. Subsequently, if the first value reaches a fifth threshold, the defect can be verified. The fifth threshold can be set considering different factors, such as the time period for which the data is analyzed, the number of load handling devices, and the size of the horizontal grid structure 15. The fifth threshold can be a numerical value or a percentage value, where the percentage value includes the ratio between the number of times the anomalous data (of the unique load handling devices) is mapped to the positioning data corresponding to the area and the number of times the positioning data corresponds to this area. The fifth threshold can be set according to the actual situation and is used to indicate the confidence level that there is indeed a defect. In step 1060, a sixth threshold can be used to ensure that the unique load handling devices have adequately sampled the area. The sixth threshold can be set considering different factors, such as the time period for which the data is analyzed, the number of unique load handling devices, and the size of the horizontal grid structure 15. Thus, for a plurality of load handling devices, if the number of times the positioning data corresponds to the area reaches the sixth threshold, the defect is verified. It should be understood that in addition to using either or both of the fifth and sixth thresholds to verify the defect, it may also be necessary to reach all of the first, second, third, fourth, fifth, and / or sixth thresholds before a defect can be identified.

[0065] It should be understood that with respect to Figure 10 , any combination of thresholds can be selected to verify or identify a defect. That is, any one or combination of the first, second, third, fourth, fifth, or sixth thresholds can be selected according to the actual situation.

[0066] Although Figure 10 's method is used to supplement the data from a single load handling device in accordance with Figure 9 , it should be understood that data from all load handling devices may be required before a defect can be identified. For example, Figure 9 's process can be modified to use the data generated by each movement sensor 210 of each individual load handling device. Thus, any instance of anomalous data from any load handling device is mapped to the positioning data. Subsequently, if the number of times the mapping occurs within the area reaches the first threshold, a defect in the area is identified. Of course, the aforementioned first threshold (as well as the fourth, fifth, and sixth thresholds) can be adjusted proportionally according to the number of load handling devices in use. In this embodiment, the first threshold can be substantially equal to the aforementioned third threshold. Accordingly, Figure 11illustrates the steps of method 1000 for determining defects in a system. The system includes a plurality of load handling devices 30, a first set of tracks 17 extending in a first direction, and a second set of tracks 19 extending in a second direction transverse to the first direction. Each load handling device is configured to move on the tracks, and each load handling device includes a sensor configured to monitor the movement of the load handling device. In step 1110, data generated by the sensor as the load handling device moves along the first set and / or the second set of tracks is acquired. The data can be acquired by computing device 174, which then implements Figure 11 the method. In step 1120, the data is analyzed as described above, and it is determined that the data includes abnormal data. In step 1130, by mapping the abnormal data to the positioning data of the load handling device, a defect in a region (e.g., a grid space) of the first set and / or the second set of tracks is identified, where if the number of times the abnormal data maps to the positioning data corresponding to this region (e.g., the data generated as described above) reaches a first threshold, the defect is identified. In other words, if a region of the horizontal grid structure causes the load handling device to have abnormal movements multiple times, this region stores a defect.

[0067] The defect determined by Figure 11 the method can be further verified using Figure 10 steps 1040, 1050, and 1060. Similarly, it should be understood that in addition to using any of the fourth, fifth, and sixth thresholds to verify the defect, all of the fourth, fifth, and sixth thresholds must be reached before the defect can be identified. It should also be understood that any combination of thresholds can be selected to verify or identify the defect. That is, any one or combination of the first, fourth, fifth, or sixth thresholds can be selected according to the actual situation.

[0068] The above method can be executed on data collected over a period of time (e.g., several hours, several days, several weeks, and several months). Once the above method is run, the defective regions of the horizontal grid structure can be identified. The location and severity (i.e., persistent abnormal data) can be presented on a map (or "heat" map). The heat map or map is a 2D representation of the horizontal grid structure 15, where the color of the region with the defect can be used to indicate the severity of the defect. Figure 12 An exemplary heat map 1200 is shown in, where region 1210 is shown to have data with a high level of abnormality consistent with scale 1220 (e.g., the load handling device encounters severe vibrations when traveling in this region). The two axes of the heat map can be used to indicate the exact region / location of the defect. Daily snapshots of the heat map can be used to create a video or time-lapse of the horizontal grid structure 15 to observe the development of the defect over time.

[0069] Although the above method is described in the context of detecting defects, it should be understood that the same method can be easily used to detect the normal operation of the system. That is, if the mobile sensor only generates normal data, it can be considered that there are no defects in the grid. This is particularly useful when verifying the stability of newly built tracks and / or repaired sections.

[0070] In this document, the term "movement along the n direction" (and related phrases) is intended to mean movement substantially along or parallel to the n-axis in either direction (i.e., towards the positive end of the n-axis or towards the negative end of the n-axis), where n is one of x, y, and z.

[0071] In this document, the words "connected" and its derivatives are intended to include the possibility of direct connection and indirect connection. For example, "x is connected to y" is intended to include the possibility that x is directly connected to y without intermediate components, and the possibility that x is indirectly connected to y with one or more intermediate components. When the intention is to express direct connection, expressions such as "is directly connected", "directly connected" or similar will be used. Similarly, the words "supported" and its derivatives are intended to include the possibility of direct contact and indirect contact. For example, "x supports y" is intended to include the possibility that x directly supports and is in direct contact with y without intermediate components, and the possibility that x indirectly supports y with one or more intermediate components that contact x and / or y. The words "mounted" and its derivatives are intended to include the possibility of direct mounting and indirect mounting. For example, "x is mounted on y" is intended to include the possibility that x is directly mounted on y without intermediate components, and the possibility that x is indirectly mounted on y with one or more intermediate components. In this document, the word "comprises" and its derivatives are intended to have an open meaning rather than a closed meaning. For example, "x comprises y" is intended to include the possibility that x comprises one and only one y, multiple y's, or one or more y's and one or more other elements. When the intention is to express a closed meaning, "x consists of y" will be used, indicating that x only comprises y and no other.

[0072] In this document, "controller" is intended to include any hardware suitable for controlling (e.g., providing instructions to) one or more other components. For example, a processor equipped with one or more memories and appropriate software to process data related to the component or components and send appropriate instructions to the component(s) to enable the component(s) to perform its intended function(s).

[0073] In this application, unless the context clearly dictates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms. It should also be understood that although the term "comprising" as used in this specification specifies the presence of the stated features, integers, steps, operations, elements and / or components, it does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0074] The present invention may take the following forms: an embodiment entirely in hardware, an embodiment entirely in software, or an embodiment containing both hardware elements and software elements. In a preferred embodiment, the present invention is implemented in software.

[0075] In addition, the present invention may take the form of a computer program embodied in a computer-readable medium having computer-executable code for use by or in connection with a computer. For the purposes of this specification, a computer-readable medium can be any tangible device that can contain, store, transmit, propagate, or transport the program for use by or in connection with a computer. In addition, a computer-readable medium can be an electronic system, a magnetic system, an optical system, an electromagnetic system, an infrared system, or a semiconductor system (or apparatus or device), or a propagation medium. Examples of computer-readable media include semiconductor or solid state memory, magnetic tape, removable computer diskette, random access memory (RAM), read-only memory (ROM), hard disk, and optical disk. Currently, examples of optical disks include compact disk read-only memory (CD-ROM), read / write compact disk (CD-R / W), and DVD.

[0076] The flowcharts in the figures illustrate the architecture, functionality, and operation of possible implementations of the methods according to various embodiments of the present invention. In this regard, each block in the flowchart may represent a module, segment, or portion of code that includes one or more executable instructions for implementing the specified logical function(s). It should also be noted that in some alternative implementations, the functions recited in the blocks may not be performed in the order mentioned in the figures. For example, two blocks shown in succession may in fact be executed substantially simultaneously, or sometimes the blocks may be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the flowchart, and combinations of blocks in the flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or acts, or by a combination of dedicated hardware and computer instructions.

[0077] It should be understood that the above description is made only by way of examples, and various modifications can be made by those skilled in the art. Although the above various embodiments have been described in a certain degree of detail, or have been described with reference to one or more than one single embodiment, many changes can be made to the disclosed embodiments by those skilled in the art without departing from the scope of the present invention.

[0078] The following is a non-exhaustive list of embodiments that can be claimed or have been claimed.

[0079] 1. A computer-implemented method for determining a defect in a system, the system including a loading handling device (30), a first set of tracks (17) extending in a first direction, and a second set of tracks (19) extending in a second direction transverse to the first direction, the loading handling device being configured to move on the tracks, wherein the loading handling device includes a sensor configured to monitor the movement of the loading handling device, and wherein the method includes: Obtaining data generated by the sensor when the loading handling device moves along the first set of tracks and / or the second set of tracks; Determining that the data includes abnormal data; and Identifying a defect in the region of the first set of tracks and / or the second set of tracks by mapping the abnormal data to the positioning data of the loading handling device.

[0080] 2. The method according to embodiment 1, wherein the defect is identified if the number of times the abnormal data is mapped to the positioning data corresponding to the region reaches a first threshold.

[0081] 3. The method according to any of the preceding embodiments, wherein the sensor detects vibrations of the loading handling device when the loading handling device moves along the first set of tracks and / or the second set of tracks.

[0082] 4. The method according to any of the preceding embodiments, wherein the sensor includes an accelerometer, an inertial measurement unit, a gyroscope, an encoder, or a torque sensor coupled to at least one wheel or axle of the loading handling device.

[0083] 5. The method according to any of the preceding embodiments, wherein determining that the data is abnormal data includes detecting the data: Deviating from the mode, median, or average by a predetermined value; or Exceeding a reference value.

[0084] 6. The method according to any of the foregoing embodiments, wherein data generated by the sensor during acceleration and deceleration of the loading handling device is excluded so that when it is determined that the data includes abnormal data, the loading handling device is traveling at a constant speed.

[0085] 7. The method according to any of the foregoing embodiments, wherein the sensor generates only data on an axis transverse to the direction of movement of the loading handling device.

[0086] 8. The method according to embodiments 1 to 6, wherein the sensor generates data on a first axis corresponding to the first direction, data on a second axis corresponding to the second direction, and data on a third axis transverse to the first direction and the second direction.

[0087] 9. The method according to any of the foregoing embodiments, wherein the first threshold is a numerical value or a percentage value, and optionally, wherein the percentage value includes the ratio between the number of times abnormal data is mapped to the positioning data corresponding to the area and the number of times the positioning data corresponds to the area.

[0088] 10. The method according to any of the foregoing embodiments, wherein if the number of times the positioning data corresponds to the area reaches a second threshold, the defect is verified.

[0089] 11. The method according to any of the foregoing embodiments, wherein the system includes a plurality of loading handling devices, and wherein for the plurality of loading handling devices, if the number of times abnormal data is mapped to the positioning data corresponding to the area reaches a third threshold, the defect is verified.

[0090] 12. The method according to embodiment 11, wherein for the plurality of loading handling devices, if the number of times the positioning data corresponds to the area reaches a fourth threshold, the defect is verified.

[0091] 13. The method according to embodiments 1 to 10, wherein the system includes a plurality of loading handling devices, and wherein the method further includes: determining the percentage of unique loading handling devices in the area in which the data includes abnormal data to define a first value; and if the first value exceeds a fifth threshold, verifying that there is a defect in the area.

[0092] 14. The method according to embodiments 1 to 10, wherein the system includes a plurality of loading handling devices, and wherein the method further includes: determining the total number of unique loading handling devices for which the positioning data corresponds to the area to define a second value; and If the second value exceeds the sixth threshold, the verification defect is in the region.

[0093] 15. The method according to any one of embodiments 10 to 14, wherein each of the first threshold, the second threshold, the third threshold, the fourth threshold, the fifth threshold, and the sixth threshold is reached to verify that the defect is in the region, or any combination of the first threshold, the second threshold, the third threshold, the fourth threshold, the fifth threshold, and the sixth threshold is reached to verify that the defect is in the region.

[0094] 16. The method according to any of the foregoing embodiments, wherein the method further comprises determining the type of the defect by detecting a corresponding unique pattern in the data.

[0095] 17. The method according to any of the foregoing embodiments, wherein the type of the defect includes at least one of the following: Debris on the first set of tracks and / or the second set of tracks; Misalignment along the first set of tracks and / or the second set of tracks and / or misalignment between the first set of tracks and the second set of tracks; Damaged sections on the first set of tracks and / or the second set of tracks; and Damaged intersections along the first set of tracks and / or the second set of tracks and / or damaged intersections between the first set of tracks and the second set of tracks.

[0096] 18. The method according to any of the foregoing embodiments, wherein the first set of tracks and the second set of tracks are in a substantially horizontal plane to form a grid, the grid including a plurality of grid spaces to form a plurality of vertical storage positions below the grid for stacking containers vertically between columns and guiding the containers vertically through the plurality of grid spaces by the columns, and optionally, wherein the loading handling device or each loading handling device is configured to lift a container from a vertical storage position below the grid and / or lower a container to a vertical storage position.

[0097] 19. The method according to embodiment 18, wherein the region includes a grid space, and the method optionally further comprises reconfiguring the system to avoid operating the loading handling device or each loading handling device in the grid space.

[0098] 20. The method according to embodiment 19, wherein the data includes a plurality of average values, wherein each average value is derived from the sensor when the loading handling device moves over respective grid spaces.

[0099] 21. The method as described in any of the foregoing embodiments, wherein the method is performed within a predefined time period.

[0100] 22. The method as described in any of the foregoing embodiments, further comprising generating a map, wherein the map indicates areas within the system that have defects.

[0101] 23. A computer program comprising instructions which, when executed by a computer, cause the computer to implement the method as described in Embodiments 1 to 22.

[0102] 24. A data processing system comprising a processor configured to implement the method as described in Embodiments 1 to 22.

[0103] 25. A system comprising: a load handling device (30), a first set of tracks (17) extending in a first direction, and a second set of tracks (19) extending in a second direction transverse to the first direction, the load handling device being configured to move on the tracks, wherein the load handling device includes sensors configured to monitor the movement of the load handling device; and The data processing system as described in Embodiment 24.

[0104] 26. A map, wherein the map is generated using the method as described in Embodiments 1 to 212, the computer program as described in Embodiment 23, or the system as described in Embodiments 24 or 25, and the map indicates areas within the system that have defects.

[0105] 27. A computer-implemented method for determining defects in a system, the system comprising a load handling device (30), a first set of tracks (17) extending in a first direction, and a second set of tracks (19) extending in a second direction transverse to the first direction, the load handling device being configured to move on the tracks, wherein each load handling device includes sensors configured to monitor the movement of the load handling device, wherein the method comprises: Obtaining data generated by the sensors when the load handling device moves along the first set of tracks and / or the second set of tracks; Determining that the data includes abnormal data; and Identifying a defect in an area of the first set of tracks and / or the second set of tracks by mapping the abnormal data to the positioning data of the load handling device.

[0106] 28. The method as described in Embodiment 27, wherein if the number of times the abnormal data is mapped to the positioning data corresponding to the area reaches a first threshold, the defect is identified.

[0107] 29. The method according to embodiment 27 or 28, wherein the sensor detects vibrations of the load handling device as the load handling device moves along the first set of tracks and / or the second set of tracks.

[0108] 30. The method according to embodiments 27 to 29, wherein the sensor comprises an accelerometer, an inertial measurement unit, a gyroscope, an encoder or a torque sensor coupled to at least one wheel or axle of the load handling device.

[0109] 31. The method according to embodiments 27 to 30, wherein determining that the data is abnormal data comprises detecting the data: deviating from the mode, median or average by a predetermined value; or exceeding a reference value.

[0110] 32. The method according to embodiments 27 to 31, wherein data generated by the sensor during acceleration and deceleration of the load handling device is excluded so that when determining that the data includes abnormal data, the load handling device is traveling at a constant speed.

[0111] 33. The method according to embodiments 27 to 32, wherein the sensor generates data only on an axis transverse to the direction of movement of the load handling device.

[0112] 34. The method according to embodiments 27 to 33, wherein the sensor generates data on a first axis corresponding to the first direction, data on a second axis corresponding to the second direction, and data on a third axis transverse to the first direction and the second direction.

[0113] 35. The method according to embodiments 27 to 34, wherein the first threshold is a numerical value or a percentage value, and optionally, wherein the percentage value comprises a ratio between the number of times abnormal data is mapped to the positioning data corresponding to the area and the number of times the positioning data corresponds to the area.

[0114] 36. The method according to embodiments 27 to 35, wherein for the plurality of load handling devices, if the number of times the positioning data corresponds to the area reaches a second threshold, the defect is verified.

[0115] 37. The method according to embodiments 27 to 36, wherein the method further comprises: determining a percentage of unique load handling devices in the area for which the data includes abnormal data to define a first value; and if the first value exceeds a fifth threshold, verifying that the defect is in the area.

[0116] 38. The method according to any one of embodiments 26 to 37, wherein the method further comprises: Determining a total number of unique loading handling devices corresponding to the positioning data for the region to define a second value; and Verifying that a defect is in the region if the second value exceeds a sixth threshold.

[0117] 39. The method according to any one of embodiments 35 to 38, wherein reaching each of the first threshold, the second threshold, the fifth threshold, and the sixth threshold verifies that a defect is in the region, or reaching any combination of the first threshold, the second threshold, the fifth threshold, and the sixth threshold verifies that a defect is in the region.

[0118] 40. The method according to any one of embodiments 26 to 39, wherein the method further comprises determining a type of the defect by detecting a corresponding unique pattern in the data.

[0119] 41. The method according to any of the foregoing embodiments, wherein the type of the defect includes at least one of the following: Debris on the first set of tracks and / or the second set of tracks; Misalignment along the first set of tracks and / or the second set of tracks and / or misalignment between the first set of tracks and the second set of tracks; Damaged segments on the first set of tracks and / or the second set of tracks; and Damaged intersections along the first set of tracks and / or the second set of tracks and / or damaged intersections between the first set of tracks and the second set of tracks.

[0120] 42. The method according to any of embodiments 27 to 41, wherein the first set of tracks and the second set of tracks are in a substantially horizontal plane to form a grid, the grid including a plurality of grid spaces to form a plurality of vertical storage positions below the grid for containers to be stacked vertically between uprights and guided vertically by the uprights through the plurality of grid spaces, and optionally, wherein the loading handling device or each loading handling device is configured to lift a container from a vertical storage position below the grid and / or lower a container to a vertical storage position.

[0121] 43. The method according to any of embodiments 42, wherein the region includes a grid space, and the method optionally further comprises reconfiguring the system to avoid operating the loading handling device or each loading handling device in the grid space.

[0122] 44. The method according to embodiment 43, wherein the data includes a plurality of average values, and each average value is derived from the sensor when the loading processing device moves on respective grid spaces.

[0123] 45. The method according to embodiments 27 to 44, wherein the method is executed within a predefined time period.

[0124] 46. The method according to embodiments 27 to 45, further comprising generating a map, wherein the map indicates areas with defects within the system.

[0125] 47. A computer program including instructions that, when executed by a computer, cause the computer to implement the method according to embodiments 27 to 46.

[0126] 48. A data processing system including a processor configured to implement the method according to embodiments 27 to 47.

[0127] 49. A system, the system comprising: a loading processing device (30), a first set of tracks (17) extending in a first direction, and a second set of tracks (19) extending in a second direction transverse to the first direction, the loading processing device being configured to move on the tracks, wherein each loading processing device includes a sensor configured to monitor the movement of the loading processing device; and The data processing system according to embodiment 48.

[0128] 50. A map, wherein the map is generated using the method according to embodiments 27 to 46, the computer program according to embodiment 47, or the system according to embodiment 48 or 49, and the map indicates areas with defects within the system.

[0129] 51. A computer-executed method for verifying system construction and / or repair, the system including a loading processing device (30), a first set of tracks (17) extending in a first direction, and a second set of tracks (19) extending in a second direction transverse to the first direction, the loading processing device being configured to move on the tracks, wherein the loading processing device includes a sensor configured to monitor the movement of the loading processing device. The method includes: Obtaining data generated by the sensor when the loading processing device moves along the first set of tracks and / or the second set of tracks; Determining that the data includes normal data; and Verify the system construction and / or repair in the area of the first set of tracks and / or the second set of tracks by mapping the normal data to the positioning data of the loading handling device.

[0130] 52. The method according to embodiment 51, wherein if the number of times the normal data is mapped to the positioning data corresponding to the area reaches a first threshold, the construction and / or repair is verified.

[0131] 53. The method according to embodiment 51 or 52, wherein the sensor detects the vibration of the loading handling device when the loading handling device moves along the first set of tracks and / or the second set of tracks.

[0132] 54. The method according to embodiments 51 to 53, wherein the sensor includes an accelerometer, an inertial measurement unit, a gyroscope, an encoder or a torque sensor coupled to at least one wheel or axle of the loading handling device.

[0133] 55. The method according to embodiments 51 to 54, wherein determining that the data is normal includes detecting that the data deviates from a predetermined value in a manner smaller than a predetermined value with respect to the mode, median or average; or is less than a reference value.

[0134] 56. The method according to embodiments 51 to 55, wherein the data generated by the sensor during acceleration and deceleration of the loading handling device is excluded so that when determining that the data includes normal data, the loading handling device is traveling at a constant speed.

[0135] 57. The method according to embodiments 51 to 56, wherein the sensor generates data only on an axis transverse to the moving direction of the loading handling device.

[0136] 58. The method according to embodiments 51 to 57, wherein the sensor generates data on a first axis corresponding to the first direction, data on a second axis corresponding to the second direction, and data on a third axis transverse to the first direction and the second direction.

[0137] 59. The method according to embodiments 51 to 58, wherein the first threshold is a numerical value or a percentage value, and optionally, wherein the percentage value includes the ratio between the number of times the normal data is mapped to the positioning data corresponding to the area and the number of times the positioning data corresponds to the area.

[0138] 60. The method according to embodiments 51 to 59, wherein if the number of times the positioning data corresponds to the area reaches a second threshold, the construction and / or repair is verified.

[0139] 61. The method according to any one of Embodiments 51 to 60, wherein the system includes a plurality of loading processing devices, and wherein, for the plurality of loading processing devices, if the number of times that the normal data is mapped to the positioning data corresponding to the area reaches a third threshold, the construction and / or repair is verified.

[0140] 62. The method according to Embodiment 61, wherein, for the plurality of loading processing devices, if the number of times that the positioning data corresponds to the area reaches a fourth threshold, the construction and / or repair is verified.

[0141] 63. The method according to any one of Embodiments 51 to 60, wherein the system includes a plurality of loading processing devices, and wherein the method further includes: determining a percentage of unique loading processing devices in the area in which the data includes abnormal data to define a first value; and if the first value exceeds a fifth threshold, verifying the construction and / or repair.

[0142] 64. The method according to any one of Embodiments 51 to 60, wherein the system includes a plurality of loading processing devices, and wherein the method further includes: determining a total number of unique loading processing devices in which the positioning data corresponds to the area to define a second value; and if the second value exceeds a sixth threshold, verifying that there is a defect in the area.

[0143] 65. The method according to any one of Embodiments 60 to 64, wherein reaching each of the first threshold, the second threshold, the third threshold, the fourth threshold, the fifth threshold, and the sixth threshold, or reaching any combination of the first threshold, the second threshold, the third threshold, the fourth threshold, the fifth threshold, and the sixth threshold verifies that there is a defect in the area.

[0144] 66. The method according to any one of Embodiments 51 to 65, wherein verifying the construction and / or repair includes at least one of the following: there is no debris on the first set of tracks and / or the second set of tracks; alignment along the first set of tracks and / or the second set of tracks and / or alignment between the first set of tracks and the second set of tracks; the segments on the first set of tracks and / or the second set of tracks are not damaged; and the intersection points along the first set of tracks and / or the second set of tracks are not damaged and / or the intersection points between the first set of tracks and the second set of tracks are not damaged.

[0145] 67. The method according to any one of embodiments 51 to 66, wherein the first set of tracks and the second set of tracks are in a substantially horizontal plane to form a grid, the grid including a plurality of grid spaces, to form a plurality of vertical storage positions below the grid, to allow containers to be stacked vertically between the uprights and to be guided vertically by the uprights through the plurality of grid spaces, and optionally, wherein the loading handling device or each loading handling device is configured to lift a container from a vertical storage position below the grid and / or lower a container to a vertical storage position.

[0146] 68. The method according to embodiment 67, wherein the area includes grid spaces, and the method optionally further includes reconfiguring the system to avoid operating the loading handling device or each loading handling device in the grid spaces until the construction and / or repair has been verified.

[0147] 69. The method according to embodiment 68, wherein the data includes a plurality of average values, each average value being derived from the sensor when the loading handling device moves over respective grid spaces.

[0148] 70. The method according to any one of embodiments 51 to 69, wherein the method is performed within a predefined time period.

[0149] 71. The method according to any one of embodiments 51 to 70, further including generating a map, wherein the map indicates areas within the system where the construction and / or repair has been verified.

[0150] 72. A computer program including instructions which, when executed by a computer, cause the computer to implement the method according to any one of embodiments 51 to 71.

[0151] 73. A data processing system including a processor, the processor being configured to implement the method according to any one of embodiments 51 to 71.

[0152] 74. A system, the system including: a loading handling device (30), a first set of tracks (17) extending in a first direction, and a second set of tracks (19) extending in a second direction transverse to the first direction, the loading handling device being configured to move on the tracks, wherein the loading handling device includes a sensor configured to monitor the movement of the loading handling device; and the data processing system according to embodiment 73.

[0153] 75. A map, wherein the map is generated using the method as described in Embodiments 51 to 71, the computer program as described in Embodiment 72, or the system as described in Embodiments 73 or 74, and wherein the map indicates areas within the system where the construction and / or repair has been verified.

Claims

1. A computer-implemented method for determining a defect in a system, the system including a loading handling device (30), a first set of tracks (17) extending in a first direction, and a second set of tracks (19) extending in a second direction transverse to the first direction, the loading handling device being configured to move on the tracks, wherein, the loading handling device includes a sensor configured to monitor the movement of the loading handling device, and wherein the method includes: acquiring data generated by the sensor when the loading handling device moves along the first set of tracks and / or the second set of tracks; determining that the data includes abnormal data; and identifying a defect in the area of the first set of tracks and / or the second set of tracks by mapping the abnormal data to the positioning data of the loading handling device, wherein the defect is identified if the number of times the abnormal data is mapped to the positioning data corresponding to the area reaches a first threshold.

2. The method according to claim 1, wherein, the sensor detects vibrations of the loading handling device when the loading handling device moves along the first set of tracks and / or the second set of tracks.

3. The method according to any of the preceding claims, wherein, the sensor includes an accelerometer, an inertial measurement unit, a gyroscope, an encoder or a torque sensor coupled to at least one wheel or axle of the loading handling device.

4. The method according to any of the preceding claims, wherein, determining the data as abnormal data includes detecting the data: deviating from a mode, median or average by a predetermined value; or exceeding a reference value.

5. The method according to any of the preceding claims, wherein, data generated by the sensor during acceleration and deceleration of the loading handling device is excluded so that the loading handling device is traveling at a constant speed when it is determined that the data includes abnormal data.

6. The method according to any of the preceding claims, wherein, the sensor only generates data on an axis transverse to the direction of movement of the loading handling device.

7. The method according to claims 1 to 6, wherein, the sensor generates data on a first axis corresponding to the first direction, data on a second axis corresponding to the second direction, and data on a third axis transverse to the first direction and the second direction.

8. The method according to any of the preceding claims, wherein, the first threshold is a numerical or percentage value, and optionally, wherein the percentage value includes the ratio between the number of times the abnormal data is mapped to the positioning data corresponding to the area and the number of times the positioning data corresponds to the area.

9. The method according to any of the preceding claims, wherein, the defect is verified if the number of times the positioning data corresponds to the area reaches a second threshold.

10. The method according to any of the preceding claims, wherein, the system includes a plurality of loading handling devices, and for the plurality of loading handling devices, the defect is verified if the number of times the abnormal data is mapped to the positioning data corresponding to the area reaches a third threshold.

11. The method according to claim 10, wherein, for the plurality of loading handling devices, if the number of times the positioning data corresponds to the area reaches a fourth threshold, the defect is verified.

12. The method according to claims 1 to 9, wherein, the system includes a plurality of loading handling devices, and wherein the method further includes: determining a percentage of unique loading handling devices in the area where the data includes abnormal data to define a first value; and if the first value exceeds a fifth threshold, verifying that a defect is in the area.

13. The method according to claims 1 to 9, wherein, the system includes a plurality of loading handling devices, and wherein the method further includes: determining the total number of unique loading handling devices for which the positioning data corresponds to the area to define a second value; and if the second value exceeds a sixth threshold, verifying that a defect is in the area.

14. The method according to claims 9 to 11, wherein, reaching each of the second threshold, the third threshold, the fourth threshold, the fifth threshold, and the sixth threshold to verify that a defect is in the area.

15. The method according to any of the preceding claims, wherein, the method further includes determining the type of the defect by detecting a corresponding unique pattern in the data.

16. The method according to any of the preceding claims, wherein, the type of the defect includes at least one of the following: debris on the first set of tracks and / or the second set of tracks; misalignment along the first set of tracks and / or the second set of tracks and / or misalignment between the first set of tracks and the second set of tracks; damaged sections on the first set of tracks and / or the second set of tracks; and damaged intersections along the first set of tracks and / or the second set of tracks and / or damaged intersections between the first set of tracks and the second set of tracks.

17. The method according to any of the preceding claims, wherein, the first set of tracks and the second set of tracks are in a substantially horizontal plane to form a grid, the grid includes a plurality of grid spaces, to form a plurality of vertical storage positions below the grid, to allow containers to be stacked vertically between columns and to be guided vertically by the columns through the plurality of grid spaces, and optionally, wherein the loading handling device or each loading handling device is configured to lift a container from a vertical storage position below the grid and / or lower a container to a vertical storage position.

18. The method according to claim 17, wherein, the area includes a grid space, and the method optionally further includes reconfiguring the system to avoid operating the loading handling device or each loading handling device in the grid space.

19. The method according to claim 18, wherein, the data includes a plurality of average values, wherein each average value is derived from the sensor when the loading handling device moves over its respective grid space.

20. The method according to any of the preceding claims, wherein, the method is performed within a predefined time period.

21. The method according to any of the preceding claims, further comprising generating a map, wherein, the map indicates an area within the system having a defect.

22. A computer program comprising instructions which, when executed by a computer, cause the computer to perform the method according to claims 1 to 21.

23. A data processing system comprising a processor configured to perform the method according to claims 1 to 21.

24. A system, the system comprising: a loading handling device (30), a first set of tracks (17) extending in a first direction, and a second set of tracks (19) extending in a second direction transverse to the first direction, the loading handling device being configured to move on the tracks, wherein the loading handling device includes a sensor configured to monitor the movement of the loading handling device; and the data processing system according to claim 23.

25. A map, wherein, the map is generated using the method according to claims 1 to 21, the computer program according to claim 22, or the system according to claim 23 or 24, and the map indicates an area within the system having a defect.

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