Method and apparatus for assigning pick-and-place tasks to robots

Abstract

Embodiments of the present disclosure relate to a method and apparatus for assigning pick-and-place tasks to robots, the method comprising: obtaining positions of items to be picked and placed; determining available robots for each item based on a condition of each robot and the obtained position of each item; determining an optimal robot for each item to be picked and placed from the available robots; assigning a pick-and-place task of a corresponding item to the optimal robot.

Description

Technical Field

[0001] This invention relates to robotics, and more specifically, to a method and apparatus for assigning pick-and-place tasks to a robot. Background Technology

[0002] Robots are widely used in industry for picking up and placing items. Typically, distributing or assigning items requires a distribution strategy, which can be referred to as the method of picking up and placing items. The quality of the distribution strategy has a significant impact on the picking and placing of items.

[0003] Typically, robots use two allocation strategies: load balancing (LB) and adaptive task completion (ATC).

[0004] LB is a distribution strategy that distributes items on the conveyor belt equally to all robots in the station, ensuring that each robot has the same load; while ATC is a strategy that distributes items according to the order of the robots, so that the robots at the front pick up as many items as possible, while the robots at the back pick up the remaining items. Summary of the Invention

[0005] This invention is defined by the claims.

[0006] According to one aspect of this disclosure, a method for assigning pick-and-place tasks to robots is provided, the method comprising: obtaining the location of an item to be picked up or placed; determining an available robot for each item based on the status of each robot and the obtained location of each item; determining the optimal robot from the available robots for each item to be picked up or placed; and assigning the pick-and-place task of the corresponding item to the optimal robot.

[0007] Using the above method, those skilled in the art will understand that this method provides an improved allocation strategy that can be adapted to any combination of the following: the number and location of items, the robot's real-time status, load capacity, speed, and operating range (or reachability), as well as other practical conditions. This can greatly improve the efficiency of item pickup and placement, reduce the frequency of robot malfunctions, extend the robot's lifespan, and reduce the operator's workload.

[0008] In some embodiments, determining the optimal robot from the available robots for each item to be picked up and placed may include: estimating the pick-up and placement energy consumption of each available robot for each item; comparing the pick-up and placement energy consumption of all available robots; and determining the optimal robot based on the comparison of pick-up and placement energy consumption.

[0009] In some embodiments, estimating the pick-and-place energy consumption for each available robot may include: calculating the pick-and-place path for each available robot for each item; and representing the pick-and-place energy consumption using the calculated pick-and-place path.

[0010] In some embodiments, the pick-and-place path is measured by the path taken by the end effector of an available robot from the placement point of a previous item to the pick-up point of the target item, and then to the placement point of the target item.

[0011] In some embodiments, determining the optimal robot from the available robots for each item to be picked up and placed may include: estimating the current load of each available robot for each item; comparing the current loads among all available robots; and determining the optimal robot based on the comparison of the current loads.

[0012] In some embodiments, determining the optimal robot from the available robots for each item to be picked up and placed may include: estimating the pick-up and placement energy consumption of each available robot for each item; estimating the current load of each available robot; calculating the sum of the pick-up and placement energy consumption and the current load of each available robot; comparing the sum of all available robots; and determining the optimal robot based on the comparison of the sums.

[0013] In some embodiments, the current load of each available robot is measured by total energy consumption or the number of assigned items that have been allocated to the queue of available robots but have not yet been picked up.

[0014] In some embodiments, the determination of the optimal robot may also be based on one or more other factors selected from the group consisting of: the conveyor speed of the conveyor on which items are to be picked up or placed; the rated load capacity of each available robot; the operating speed of each available robot; and the work area of ​​each available robot.

[0015] In some embodiments, the location of the item to be picked up is obtained via an image capture device.

[0016] In some embodiments, the status of each robot includes the state of each robot and the operating range of each robot.

[0017] In some embodiments, items are picked up and placed between two conveyors.

[0018] According to another aspect of this disclosure, an apparatus for assigning pick-and-place tasks to robots is provided, comprising: a processor coupled to a plurality of robots and configured to implement the method described above.

[0019] According to another aspect of this disclosure, a pick-and-place system is provided, comprising: a plurality of robots, each configured to perform pick-and-place tasks of a plurality of items; and a processor coupled to the plurality of robots and configured to implement the method described above.

[0020] In some embodiments, the pick-and-place system may further include: at least one image capture device coupled to the processor and configured to capture at least one image of the item to be picked up; wherein the processor is configured to obtain the position of the item to be picked up based on the captured at least one image.

[0021] In some embodiments, the pick-and-place system may further include: a first conveyor configured to convey an item to be picked up; and a second conveyor configured to receive an item picked up from the first conveyor.

[0022] According to another aspect of this disclosure, a computer-readable medium having a computer program stored thereon is provided, which, when executed by a processor, implements the method described above. Attached Figure Description

[0023] In the accompanying drawings, similar / identical reference numerals in different views generally indicate similar / identical parts. The drawings are not necessarily to scale. Rather, the focus is on illustrating the principles of the invention. In these drawings:

[0024] Figure 1 An exemplary pick-and-place system is shown that applies a method for assigning pick-and-place tasks to a robot according to an embodiment of the present disclosure;

[0025] Figure 2 A flowchart is shown for a method of assigning pick-and-place tasks to a robot according to an embodiment of the present disclosure;

[0026] Figure 3 A schematic diagram of two exemplary pick-and-place paths, each used by two different available robots, is shown; and

[0027] Figure 4 A schematic diagram is shown for two queues with their respective assigned items for two different available robots. Detailed Implementation

[0028] Embodiments of this disclosure will be described in more detail with reference to the accompanying drawings. Although the drawings illustrate some embodiments of this disclosure, it should be understood that this disclosure can be implemented in various ways and should not be construed as limited to the embodiments described herein. Rather, embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0029] In the description of embodiments of this disclosure, the term "comprising" and variations thereof shall be interpreted as open-ended terms meaning "including but not limited to". The term "based on" shall be understood as "at least partially based on". The terms "an embodiment" and "the embodiment" shall be understood as "at least one embodiment". The following text may also include other explicit and implicit definitions.

[0030] As described in the background section, the quality of the allocation strategy has a critical impact on the picking and placing of items, and two commonly used allocation strategies for robots exist: load balancing (LB) and adaptive task completion (ATC). However, both of these allocation strategies have been found to have their own drawbacks.

[0031] More specifically, the LB strategy has the following drawbacks: Items are not allocated based on the actual characteristics and performance of the robots, which may vary between different robots. In this case, LB allocation (i.e., average allocation) may result in some robots with poor performance being assigned too many items to pick up and drop, while some robots with excellent performance are assigned too few items. Furthermore, LB allocation does not fully consider the actual location of the items and / or the operating range (or reachability) of each robot, so that items beyond the robot's reach may be assigned to it, leading to malfunctioning pick-ups (or exceeding the robot's limits). Additionally, since the LB allocation strategy is usually pre-set, if one of the robots malfunctions, the system may not be able to dynamically adjust the allocation strategy, potentially resulting in missed pick-ups.

[0032] The drawback of the ATC (Automatic Pick-and-Place) strategy is that the preceding robots may be overloaded, while the following robots may be underloaded. In such cases, the preceding robots are more prone to damage or require more maintenance. Furthermore, like the LB (Load-Binding) strategy, the ATC strategy does not fully consider the actual location of the items and the operating range (or reachability) of each robot, allowing items beyond the robot's reach to be assigned to it, leading to malfunctions (or exceeding the robot's limits). In the event of malfunctions or exceeding limits, not only is maintenance and / or replacement required, but production efficiency is also severely impacted.

[0033] To overcome or mitigate the problems or drawbacks of the two common allocation strategies mentioned above, this disclosure proposes an improved allocation strategy, or improved method, for assigning pick-and-place tasks to robots. This method may include: acquiring the location of items to be picked up; determining the available robot for each item based on the status of each robot and the acquired location of each item; determining the optimal robot from the available robots for each item to be picked up; and assigning the pick-and-place task for the corresponding item to the optimal robot. Those skilled in the art will understand that, using the improved allocation strategy or method of this disclosure, the location of the items to be picked up and the performance or parameters of the robots can be considered when assigning pick-and-place tasks. Furthermore, an optimal robot can be determined for each item. In this case, the pick-and-place task for each item can be assigned to the optimal robot and can be dynamically adjusted among all available robots, thereby improving productivity.

[0034] To better understand this disclosure, Figure 1 An exemplary pick-and-place system is shown that employs a method for assigning pick-and-place tasks to a robot according to an embodiment of the present disclosure.

[0035] like Figure 1 As shown, the exemplary pick-and-place system 10 may include a plurality of robots 20 and a processor 30 coupled to the plurality of robots 20.

[0036] Multiple robots 20 are each configured to pick up and place items, for example, picking up an item from one location and placing it at another. Typically, the robots 20 are industrial robots, each equipped with an end effector for picking up and placing items.

[0037] In some embodiments, each robot 20 may be a robot with a fixed base. However, this is not a limitation, and in some embodiments, it is also possible for each robot 20 to have a movable base.

[0038] Regarding the picking and placing of items, those skilled in the art will understand that items can be organized in a desired manner. For example, items can be picked up and then placed in a packaging box.

[0039] To facilitate the pick-and-place process, in some embodiments, the pick-and-place system 10 may also include one or more conveyors 40 for transporting items to be picked up or placed. In this case, in some embodiments, multiple robots 20 may be arranged alongside these conveyors 40. Although the one or more conveyors 40 are provided herein, it should be understood that this is not a limitation, and in some embodiments, a pick-and-place system 10 without any conveyors is also possible.

[0040] For example only, such as Figure 1As shown, items can be picked up and placed between two conveyors, such as a first conveyor 41 for conveying items to be picked up (e.g., 1, 2, 3, 4) and a second conveyor 42 for conveying packaging boxes 50, and the picked-up items can be placed or organized in packaging boxes 50.

[0041] The pick-and-place system 10 may also be equipped with an allocation strategy that allows items to be allocated among the robots. Typically, the allocation strategy can be embodied as an allocation algorithm in the form of a computer program, which can be stored in and retrieved from memory, and then implemented by the processor 30 to generate item allocation information for each robot 20 (including, for example, a first available robot 21 and a second available robot 22). Typically, the item allocation information may include the pick-and-place task to be assigned to each available robot, the location of the item to be picked up, etc.

[0042] In this disclosure, in order to overcome or mitigate the problems or drawbacks of the two common allocation strategies described above, one or more factors, including information or parameters such as the number of items, item location, robot status, robot load, robot speed, robot operating range (or reachable range), and conveyor speed, will be considered for the allocation strategy, as will be described in detail later.

[0043] To collect the aforementioned information or parameters, in some embodiments, one or more sensors may be deployed around or within the robot's work area / environment. For example, one or more sensors may be used to detect the position or status of each robot. One or more sensors may be used to detect the speed of the conveyor. One or more image capture devices 60 may be used to capture images of the items to be picked up and placed, and then the images may be used to determine the position or quantity of the items. Furthermore, parameters of the conveyor or robot—such as the width or length of the conveyor, the operating range (or reachable range) of each robot—may be provided (inputted to or transmitted to) the processor 30.

[0044] Based on the generated item allocation information, each robot 20 can then perform the pick-up and drop-off tasks accordingly.

[0045] To facilitate understanding of the methods disclosed herein, Figure 2 A flowchart of a method for assigning pick-and-place tasks to a robot according to an embodiment of the present disclosure is shown.

[0046] It should be understood that the method for assigning pick-and-place tasks to the robot can be implemented using the processor or pick-and-place system described above. Furthermore, this method can be implemented in real time.

[0047] like Figure 2 As shown, method 200 can begin at box 210, that is, obtaining the position of the item to be picked up and placed.

[0048] In some embodiments, the item to be picked up may be placed on a conveyor (e.g., 41, 42). In some embodiments, an image capturing device (e.g., 60) may be positioned above the item to capture at least one image of the item, which can then be used to determine the item's position. In this case, the position of the item to be picked up can be obtained. Those skilled in the art will understand that in some embodiments, it is also possible to use sensors other than the image capturing device to detect the position of the item.

[0049] In box 220, the available robot for each item is determined based on the status of each robot and the location of each item obtained.

[0050] Note that the status of each robot may include, but is not limited to, the state of each robot and the operating range (or reachable range) of each robot.

[0051] Those skilled in the art will understand that the location of the item to be picked up and the condition of the robot can differ from each other. For this reason, it should be understood that in practice, not all robots are suitable or usable for every item to be picked up.

[0052] As an example only, some items may be located outside the robot's operating range (or reachability), in which case the robot may not be available for those items. As another example, some robots may sometimes malfunction or be undergoing maintenance, and then those robots may not be available for all items at that time.

[0053] By using the knowledge of the location of the items to be picked up and the status of the robots, the available robots for each item can then be determined.

[0054] It's important to note that different items can have different available robots, and the available robots for the same item can change over time. Additionally, an item can have more than one available robot.

[0055] Utilizing the robots available above, another objective of this disclosure is to determine the optimal robot. Those skilled in the art will understand that in this manner, allocation strategies can be significantly optimized.

[0056] Therefore, method 200 can proceed to box 230, that is, to determine the best robot from the available robots for each item to be picked up and placed.

[0057] In some embodiments, block 230 may include: estimating the pick-and-place energy consumption of each available robot for each item; comparing the pick-and-place energy consumption of all available robots; and determining the optimal robot based on the comparison.

[0058] To simplify the above estimation, in some embodiments, the pick-and-place energy consumption for each item can be represented by the pick-and-place path for each item. In these embodiments, estimating the pick-and-place energy consumption for each available robot may include: calculating the pick-and-place path for each available robot for each item; and using the calculated pick-and-place path to represent the pick-and-place energy consumption.

[0059] For simplicity, in some embodiments, the pick-up and drop path can be measured by the path taken by the end effector of an available robot from the placement point of the previous item to the pick-up point of the target item, and then to the placement point of the target item.

[0060] To facilitate understanding of the metric or definition of the pick-and-place path as described above, Figure 3 The diagram illustrates two exemplary pick-and-place paths used by two different available robots.

[0061] like Figure 3 As shown, assume that two robots 21 and 22 can be used to pick up and place the target item k. It should be understood that the pick-up and place-down paths can be different for the two available robots 21 and 22.

[0062] For example, the first available robot 21 can use a pick-and-place path Smk (represented by a solid line) to pick up and place a target item k, wherein the pick-and-place path Smk can be measured by the path of the end effector of the first available robot 21 from the placement point A of the previous item m to the pick-up point B of the target item k, and then to the placement point C of the target item k.

[0063] In contrast, the second available robot 22 can use a pick-and-place path Snk (represented by a solid line) to pick up and place a target item k, wherein the pick-and-place path Snk can be measured by the path of the end effector of the second available robot 22 from the placement point A' of the previous item n to the pick-up point B' of the target item k, and then to the placement point C' of the target item k.

[0064] Given the potentially different pick-and-place paths, it's understandable that the relevant pick-and-place energy consumption may differ between different available robots. In these cases, the pick-and-place path can be used to represent the pick-and-place energy consumption.

[0065] It should be noted that although the pick-and-place path has been measured or defined above, in some embodiments, the pick-and-place path may be measured or defined in different ways. For example, in some embodiments, the pick-and-place path may be measured or defined as the path by which the end effector of a robot moves from a pick-up point A or A' of the target item to a placement point B or B' of the target item.

[0066] Furthermore, it should be noted that, although in Figure 3Two available robots 21 and 22 were used to estimate the pick-up and drop-off energy consumption for each item, but in reality, there may be more than two available robots 21 and 22 for each item. In this case, the pick-up and drop-off energy consumption of all available robots will be estimated separately.

[0067] Once the pick-and-place energy consumption of each available robot has been measured or estimated, a comparison of pick-and-place energy consumption can be made among all available robots. Through this comparison, in some embodiments, the available robot with the lowest pick-and-place energy consumption can then be determined as the optimal robot.

[0068] Typically, in addition to the energy consumption for picking up and placing each item, one or more other factors may be considered to determine the optimal robot. These other factors may include, for example, but are not limited to: the current load of each available robot, the conveyor speed of the conveyor on which items are picked up or placed, the rated load capacity of each available robot, the operating speed of each available robot, and the working area of ​​each available robot.

[0069] Taking only the current load of each available robot as an example, in some embodiments, block 230 may include: for each item, calculating the current load of each available robot; comparing the current loads among all available robots; and determining the optimal robot based on the comparison of the current loads.

[0070] In these embodiments, the current load of each available robot can be defined or measured by total energy consumption or the number of assigned items in the available robot queue that have not yet been picked up. Those skilled in the art will understand that it is also possible for the current load of each available robot to be defined in a different way.

[0071] To facilitate understanding of the current load as described above, Figure 4 A schematic diagram is shown for two queues with their respective assigned items for two different available robots.

[0072] like Figure 4 As shown, assume that the first available robot 21 has an associated current queue 23 with items allocated from i to m, and the second available robot 22 has an associated current queue 24 with items allocated from j to n.

[0073] In the above case, the current load of the first available robot 21 can then be calculated by summing all pick-up and drop-off energy consumption from item i to item m, and the current load of the second available robot 22 can be calculated by summing all pick-up and drop-off energy consumption from item j to item n.

[0074] By comparing the current loads of all available robots, the available robot with the lowest current load can then be identified as the optimal robot.

[0075] In particular, in some embodiments, the determination of the optimal robot may be based on a combination of the estimated pick-up and drop energy consumption for each item and the estimated current load for each available robot.

[0076] In these embodiments, block 230 may include: estimating the pick-and-place energy consumption of each available robot for each item; estimating the current load of each available robot; and calculating the sum of the pick-and-place energy consumption of each available robot and the current load; comparing the sum of all available robots; and determining the optimal robot based on the comparison of the sum.

[0077] For example only, please refer to the reference. Figure 4 Suppose we must decide whether a new item k should be assigned to the first available robot 21 (e.g., added to queue 23) or the second available robot 22 (e.g., added to queue 24).

[0078] In this example, for the new item k, the pick-up and drop-off energy consumption of the first available robot 21 and the second available robot 22 can be estimated first (e.g., Smk or Snk). Then, the current load of the first available robot 21 and the second available robot 22 can be estimated (e.g., Sim or Sjn). Next, the sum of the pick-up and drop-off energy consumption and the current load of the first available robot 21 and the second available robot 22 can be calculated (e.g., S1 = Sim + Smk, or S2 = Sjn + Snk). Afterward, the sum can be compared between the first available robot 21 and the second available robot 22. By comparison, the available robot with the smallest sum can be determined as the optimal robot.

[0079] In the above embodiments, the determination of the optimal robot can be further based on any combination of the following factors: the conveying speed of the conveyor on which items will be picked up or placed, the rated load capacity of each available robot, the operating speed of each available robot, and the working area of ​​each available robot.

[0080] For example, in Figure 4 In the above embodiments, the determination of the optimal robot can also be based on the rated load capacity of each available robot.

[0081] In such an embodiment, determining the optimal robot from the available robots for each item to be picked up and placed may include comparing the calculated sum of the pick-up and placement energy consumption with the current load (e.g., S1 = Sim + Smk, or S2 = Sjn + Snk) to the corresponding rated load capacity of each available robot. If the calculated sum of an available robot is greater than its corresponding rated load capacity, that available robot may be excluded from the possible candidate optimal robots. This means that subsequent comparisons of the calculated sums between that available robot and other available robots will not be necessary.

[0082] Once the optimal robot is determined, method 200 can proceed to box 240, whereby the pick-up and drop task for the corresponding item is assigned to the optimal robot. In this box, the corresponding item can be added to the optimal robot's queue as the assigned item.

[0083] The above describes various embodiments of methods or allocation strategies for assigning pick-and-place tasks to robots. Those skilled in the art will understand that such methods or allocation strategies can be implemented in real time and are adaptable to any combination of the following: the number and location of items, the robot's real-time status, load capacity, speed, and operating range (or reachability), and other practical conditions. This can significantly improve the efficiency of item pick-and-place, reduce the frequency of robot malfunctions, extend the robot's service life, and reduce the operator's workload.

[0084] Furthermore, because this method or allocation strategy can consider any combination of real-time item quantity and location, robot real-time status, load capacity, speed and reachability, and other practical conditions, items can be assigned to the most suitable robot. Simultaneously, it avoids the problem of robots exceeding their limits. Moreover, since items can be allocated based on robot load capacity, speed, and other factors, each robot can operate within its load capacity. This can extend the robot's service life and reduce the frequency of robot failures. Even in the event of robot failure, items can be automatically redistributed to minimize potential errors in picking and placing items.

[0085] Furthermore, those skilled in the art will understand that this disclosure relates not only to the methods or allocation strategies described above, but also to means for allocating pick-and-place tasks to robots, which may include a processor coupled to a plurality of robots and configured to implement the methods described above. Additionally, this disclosure may also relate to a pick-and-place system comprising: a plurality of robots, each configured to perform pick-and-place tasks on a plurality of items; and a processor coupled to the plurality of robots and configured to implement the methods described above. In some embodiments, the pick-and-place system may further include: one or more conveyors, such as a first conveyor configured to convey items to be picked up; and a second conveyor configured to receive items picked up from the first conveyor. Furthermore, this disclosure may also relate to a computer-readable medium having a computer program stored thereon, which, when executed by a processor, can implement the methods described above.

[0086] Although the above method is described in sequential steps, it should be noted that the order of steps in the method can be appropriately changed, reordered, combined, omitted, or modified.

[0087] By studying the accompanying drawings, the disclosure, and the appended claims, those skilled in the art can understand and implement other variations of the disclosed embodiments in practicing the claimed invention. In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite articles "a" or "an" do not exclude a plurality. The fact that certain measures are recited in mutually different dependent claims does not imply that combinations of these measures cannot be advantageously used. Any reference numerals in the claims should not be construed as limiting the scope.

Claims

1. A method for assigning pick-and-place tasks to a robot, comprising: Get the location of the item to be picked up and placed; The available robot for each item is determined based on the status of each robot and the location of each item obtained; Determine the optimal robot for each item to be picked up from the available robots; and The task of picking up and placing the corresponding items is assigned to the optimal robot.

2. The method of claim 1, wherein determining the optimal robot from the available robots for each item to be picked up and placed comprises: For each item, Estimate the pick-and-place energy consumption for each available robot; Compare the pick-and-place energy consumption of all available robots; as well as The optimal robot is determined based on the comparison of the energy consumption for picking up and placing.

3. The method of claim 2, wherein estimating the pick-and-place energy consumption for each available robot comprises: For each item, Calculate the pick-and-place path for each available robot; as well as The calculated pickup and drop path is used to represent the pickup and drop energy consumption.

4. The method of claim 3, wherein the pick-up and drop path is measured by the following path of the end effector of the available robot, the path moving from the placement point of the previous item to the pick-up point of the target item and then to the placement point of the target item.

5. The method of claim 1, wherein determining the optimal robot from the available robots for each item to be picked up and placed comprises: For each item, Estimate the current load of each available robot; Compare the current load of all the available robots; as well as The optimal robot is determined based on the comparison of the current load.

6. The method of claim 1, wherein determining the optimal robot from the available robots for each item to be picked up and placed comprises: For each item, Estimate the pick-and-place energy consumption for each available robot; Estimate the current load of each available robot; as well as Calculate the sum of the pick-and-place energy consumption and the current load for each available robot; Compare the sum of all the available robots; as well as The optimal robot is determined based on the comparison of the sums.

7. The method of claim 5 or 6, wherein the current load of each available robot is measured by total energy consumption or the number of assigned items that have been allocated to the queue of available robots but have not yet been picked up.

8. The method according to any one of claims 2, 5, and 6, wherein the determination of the optimal robot is further based on one or more other factors selected from the group consisting of: The conveyor speed of the conveyor on which items are picked up or placed; Rated load capacity of each available robot; The operating speed of each available robot; and Work area for each available robot.

9. The method according to any one of the preceding claims, wherein the position of the item to be picked up and placed is acquired via an image capture device.

10. The method according to any one of the preceding claims, wherein the state of each robot includes the state of each robot and the operating range of each robot.

11. The method according to any one of the preceding claims, wherein the articles are picked up and placed between two conveyors.

12. An apparatus for assigning pick-and-place tasks to a robot, comprising: A processor, coupled to multiple robots and configured to implement the method according to any one of claims 1 to 11.

13. A pick-and-place system, comprising: Multiple robots, each configured to perform multiple item pick-up and drop-off tasks; as well as A processor, coupled to multiple robots and configured to implement the method according to any one of claims 1 to 11.

14. The pick-and-place system according to claim 13, further comprising: At least one image capture device is coupled to the processor and configured to capture at least one image of an object to be picked up and placed. The processor is configured to obtain the location of the item to be picked up based on the captured at least one image.

15. The pick-and-place system according to claim 13, further comprising: A first conveyor is configured to transport the item to be picked up; as well as The second conveyor is configured to receive items picked up from the first conveyor.

16. A computer-readable medium having a computer program stored thereon, the computer program implementing the method according to any one of claims 1 to 11 when executed by a processor.

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