Device and method for parallelizing calculation tasks to improve carrying efficiency of mechanical arm
By parallelizing computational tasks, the problem of low handling efficiency of robotic arms was solved, enabling parallel processing of computational tasks during the movement of the robotic arm and improving overall handling efficiency.
Patent Information
- Application Number
- CN202511040826.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-28
- Publication Date
- 2025-11-14
AI Technical Summary
The current robotic arm processes computational and execution tasks sequentially, resulting in low handling efficiency and a significant amount of time spent on computation, failing to fully utilize the idle time during the robotic arm's movement.
The computational task is parallelized by using a processor to perform parallel calculations of gripping points, placement points, and path planning during the robotic arm's task execution. The handling task is subdivided into sub-tasks at different stages, and the gripping points and placement points are calculated in parallel to reduce the overall time consumption.
By parallelizing the computation tasks, the overall time consumption of the handling process is reduced, the handling efficiency of the robotic arm is improved, and the idle time during the movement of the robotic arm is fully utilized.
Smart Images
Figure CN120941376A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the technical field of robotic arm control methods, and in particular to a device and method for parallelizing computational tasks to improve the handling efficiency of robotic arms. Background Technology
[0002] In the field of industrial automation, robotic arms are widely used in various material handling tasks, such as picking, placing, and transferring. However, existing material handling processes have some significant drawbacks. First, traditional robotic arms rely on high-precision 3D industrial cameras for high-resolution imaging when calculating picking and placing points, followed by complex algorithm processing, a process that takes approximately 1.5 to 3 seconds. Adding the processing time for picking and stacking algorithms, these computational tasks consume a large proportion of the material handling time, severely impacting overall handling efficiency.
[0003] Secondly, in existing technologies, computational and execution tasks are processed sequentially, failing to fully utilize the idle time during the robotic arm's movement. This means that while the robotic arm is performing actions such as moving, grasping, and placing, computational tasks must wait for the execution tasks to complete before they can proceed. This sequential processing not only prolongs the overall handling time but also results in the ineffective utilization of the robotic arm's idle time resources during movement, further reducing resource utilization.
[0004] Therefore, optimizing the processing methods for computational and execution tasks, improving efficiency, and making full use of the idle time during robotic arm movement have become urgent problems to be solved. Currently, there is a lack of solutions that can effectively improve the efficiency of material handling tasks and fully and rationally utilize resources. Summary of the Invention
[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a device and method for improving the handling efficiency of a robotic arm by parallelizing computational tasks, which can reduce the time spent in the handling process and improve handling efficiency.
[0006] To achieve the above objectives, the solution of the present invention is: A device for parallelizing computational tasks to improve the handling efficiency of a robotic arm includes a robotic arm, a control module, a gripping area, and a stacking area. The robotic arm is installed between the gripping area and the stacking area. Cameras are installed in both the gripping area and the stacking area. The control module has a processor, which is connected to the robotic arm and the cameras to complete the handling task. The handling task includes a computational task and an execution task. The computational task is performed by the processor, and the execution task is completed by the robotic arm. The computational task includes calculating the gripping point, calculating the placement point, planning the handling path, and planning the movement path. The execution task includes moving to the gripping point, moving vertically to approach the item, gripping the item, retrieving the item, moving to the placement point, moving vertically to place the item, placing the item, and returning to the starting point. During the execution of the task by the robotic arm, the processor performs parallel computation of the task.
[0007] Furthermore, this invention subdivides the handling task into sub-tasks at different stages. The robotic arm is located at the starting point. When an item enters the grasping area, the camera in the grasping area is triggered to take a picture, obtaining 2D and 3D images of the grasping area. The images of the grasping area are then sent to the processor. The processor calculates the grasping point based on the obtained image information and plans the movement path from the starting point to the grasping point. When there is an item to be grasped in the grasping area, the camera in the stacking area is triggered to take a picture, obtaining 2D and 3D images of the stacking area. The images of the stacking area are then sent to the processor. The processor calculates the placement point based on the obtained image information of the stacking area and the size of the item. After obtaining the grasping point and the placement point, the processor plans the handling path of the handling task based on the grasping point and the placement point. The robotic arm executes the task according to the results of the processor's calculation, including moving from the starting point to the grasping point, moving vertically to approach the item, grasping the item, retrieving the item, moving to the placement point, moving vertically to place the item, placing the item, and returning to the starting point.
[0008] Furthermore, when the robotic arm moves to the placement point, the processor calculates the next gripping point and plans the movement path from the starting point to the gripping point; when the robotic arm returns to the starting point, the processor calculates the placement point and plans the transport path.
[0009] This invention can also be implemented using the following technical solutions: A method for improving the handling efficiency of a robotic arm by parallelizing computational tasks includes the following steps: Step S1, Initial Preparation: The robotic arm is positioned at the starting point; Step S2, Move to the gripping point: The robotic arm moves from the starting point to the gripping point; Step S3, Item Grabbing: The robotic arm grabs the item at the gripping point; Step S4, Movement: The robotic arm moves the item according to the transport trajectory; Step S5, Reaching the Placement Point: The robotic arm reaches the placement point; it is determined whether the processor is performing parallel computation. If there is an object to be grasped in the grasping area, the processor executes the following two sub-steps in parallel: Step S51: Calculate the new grab point: Calculate the next grab point; Step S52: Path planning: Plan the path from the starting point to the newly calculated grab point; If there is no object to be grabbed in the grabbing area, the processor will not perform calculations; Step S6: Place the item: The robotic arm places the item at the designated placement point in the stacking area; Step S7, Movement: The robotic arm moves from the placement point to the starting point; Step S8, Return to Starting Point: The robotic arm returns to the starting point and determines whether the processor is performing parallel computation. If there is an object to be grasped and it does not obstruct the stacking area, the processor executes the following two sub-steps in parallel: Step S81 Calculate the new placement point: Calculate the next placement point; Step S82: Path planning for transporting goods and services: Plan the transport path from the grab point in step S51 to the placement point in step S81. If there is no object to be grabbed in the grabbing area, the processor will not perform calculations; Step S9, End Judgment: Determine whether all handling tasks have been completed. If completed, end the process; otherwise, return to step S2 to continue execution.
[0010] Furthermore, in step S5, the calculation of the new gripping point is based on the current item distribution in the gripping area, the movement limitations of the robotic arm, and the preset gripping strategy.
[0011] Furthermore, in step S8, the calculation of the new placement point is performed by comprehensively considering the spatial conditions of the stacking area, the placement rules of the items, and the reachability of the robotic arm.
[0012] By adopting the above scheme, the core of this invention's method for improving the efficiency of robotic arm handling by parallelizing computational tasks is to parallelize the calculation of gripping and placement points, allowing the robotic arm to continue performing computational tasks during movement, thereby effectively reducing the overall time consumption of the handling process. Specifically, the robotic arm can initiate parallel computational tasks during movement, such as calculating gripping and placement points and path planning, so that these computational tasks no longer become bottlenecks in the handling process. In this way, computational tasks can be completed ahead of schedule without affecting the movement of the robotic arm, greatly improving operational efficiency. Therefore, by parallelizing the originally time-consuming computational tasks, the robotic arm can perform calculations while moving, thereby reducing the total time consumption of the handling task and improving the overall efficiency of the handling task.
[0013] This invention proposes a method of concurrent processing of computational tasks, which separates computational tasks such as calculating the grasping point, calculating the placement point, and path planning from the handling process. During the movement of the robotic arm, when conditions are met, parallel computational tasks are initiated, thereby reducing the time consumed by the entire handling process and improving handling efficiency. Attached Figure Description
[0014] Figure 1 This is a schematic diagram of the handling system of the present invention.
[0015] Figure 2 This is a flowchart illustrating the material handling process of the present invention. Detailed Implementation
[0016] To further explain the technical solution of the present invention, the present invention will be described in detail below through specific embodiments.
[0017] like Figure 1 As shown, this invention discloses a device for improving the handling efficiency of a robotic arm by parallelizing computational tasks. The device includes a robotic arm, a control module, a gripping area, and a stacking area. The robotic arm is installed between the gripping and stacking areas. Cameras are installed in both the gripping and stacking areas. The control module has a processor, which can be a CPU or a GPU. The processor is connected to the robotic arm and cameras to complete the handling task. The handling task includes computational tasks and execution tasks. The computational tasks are performed by the processor, and the execution tasks are completed by the robotic arm. The computational tasks include calculating the gripping point, calculating the placement point, planning the handling path, and planning the movement path. The execution tasks include moving to the gripping point, moving vertically towards the item, gripping the item, retrieving the item, moving to the placement point, moving vertically to place the item, placing the item, and returning to the starting point. During the robotic arm's task execution, the processor initiates parallel computational tasks, thereby reducing the overall handling process time and improving handling efficiency.
[0018] This invention subdivides the handling task into different stages of sub-tasks. The robotic arm is located at the starting point. When an item enters the grasping area, the camera in the grasping area is triggered to take a picture, obtaining 2D and 3D images of the grasping area, and sending the images to the processor. The processor calculates the grasping point based on the obtained image information and plans the movement path from the starting point to the grasping point. When there is an item to be grasped in the grasping area, the camera in the stacking area is triggered to take a picture, obtaining 2D and 3D images of the stacking area, and sending the stacking area image to the processor. The processor calculates the placement point based on the obtained stacking area image information and the size of the item. After obtaining the grasping point and the placement point, the processor plans the handling path of the handling task based on the grasping point and the placement point. The robotic arm executes the task according to the result of the processor's calculation, including moving from the starting point to the grasping point, moving vertically to approach the item, grasping the item, retrieving the item, moving to the placement point, moving vertically to place the item, placing the item, and returning to the starting point.
[0019] like Figure 2 As shown, the present invention provides a method for improving the handling efficiency of a robotic arm by parallelizing computational tasks, specifically including the following steps: Step S1, Initial Preparation: The robotic arm is positioned at the starting point; Step S2, Move to the gripping point: The robotic arm moves from the starting point to the gripping point; Step S3, Item Grabbing: The robotic arm grabs the item at the gripping point; Step S4, Movement: The robotic arm moves the item according to the transport trajectory; Step S5, Reaching the Placement Point: The robotic arm reaches the placement point; it is determined whether the processor is performing parallel computation. If there is an object to be grasped in the grasping area, the processor executes the following two sub-steps in parallel: Step S51: Calculate the new grab point: Calculate the next grab point; Step S52 Path Planning: Plan the movement path from the starting point to the newly calculated grab point; If there is no object to be grabbed in the grabbing area, the processor will not perform calculations; Step S6: Place the item: The robotic arm places the item at the designated placement point in the stacking area; Step S7, Movement: The robotic arm moves from the placement point to the starting point; Step S8, Return to the starting point: Determine whether the processor is performing parallel computation. If there is an object to be grabbed and it does not obstruct the stacking area, the processor executes the following two sub-steps in parallel: Step S81 Calculate the new placement point: Calculate the next placement point; Step S82: Path planning for transporting goods and services: Plan the transport path from the grab point in step S51 to the placement point in step S81. Termination judgment: Determine whether all transport tasks have been completed. If completed, terminate; otherwise, return to step S2 to continue execution.
[0020] In step S5, the calculation of the new gripping point is based on the current distribution of items in the gripping area, the movement limitations of the robotic arm, and the preset gripping strategy.
[0021] In step S8, the calculation of the new placement point is performed by comprehensively considering the spatial conditions of the stacking area, the placement rules of the items, and the reachability of the robotic arm.
[0022] The above embodiments and figures are not intended to limit the product form and style of the present invention. Any appropriate changes or modifications made by those skilled in the art should be considered as not departing from the patent scope of the present invention.
Claims
1. A device for parallelizing computational tasks to improve the handling efficiency of a robotic arm, characterized in that: The system includes a robotic arm, a control module, a gripping area, and a stacking area. The robotic arm is installed between the gripping and stacking areas. Cameras are installed in both the gripping and stacking areas. The control module has a CPU, which is connected to the robotic arm and cameras to complete the handling task. The handling task includes calculation tasks and execution tasks. The calculation tasks are performed by the CPU, and the execution tasks are completed by the robotic arm. The calculation tasks include calculating the gripping point, calculating the placement point, planning the handling path, and planning the movement path. The execution tasks include moving to the gripping point, moving vertically to approach the item, gripping the item, retrieving the item, moving to the placement point, moving vertically to place the item, placing the item, and returning to the starting point. During the robotic arm's execution of the task, the CPU performs parallel calculations.
2. The device for parallelizing computational tasks to improve the handling efficiency of a robotic arm as described in claim 1, characterized in that: The robotic arm is located at the starting point. When an item enters the grasping area, the camera in the grasping area is triggered to take a picture, obtaining 2D and 3D images of the grasping area. The images are then sent to the CPU. The CPU calculates the grasping point based on the image information and plans the movement path from the starting point to the grasping point. When there is an item to be grasped in the grasping area, the camera in the stacking area is triggered to take a picture, obtaining 2D and 3D images of the stacking area. The images are then sent to the CPU. The CPU calculates the placement point based on the image information of the stacking area and the size of the item. After obtaining the grasping point and the placement point, the CPU plans the transportation path for the handling task. The robotic arm executes the task based on the results of the CPU's calculations, including moving from the starting point to the grasping point, moving vertically to approach the item, grasping the item, retrieving the item, moving to the placement point, moving vertically to place the item, placing the item, and returning to the starting point.
3. The device for parallelizing computational tasks to improve the handling efficiency of a robotic arm as described in claim 1, characterized in that: When the robotic arm moves to the placement point, the CPU calculates the next gripping point and plans the movement path from the starting point to the gripping point; when the robotic arm returns to the starting point, the CPU calculates the placement point and plans the transport path.
4. A method for improving the handling efficiency of a robotic arm by parallelizing computational tasks, characterized in that, Specifically, the following steps are included: Step S1, Initial Preparation: The robotic arm is positioned at the starting point; Step S2, Move to the gripping point: The robotic arm moves from the starting point to the gripping point; Step S3, Item Grabbing: The robotic arm grabs the item at the gripping point; Step S4, Movement: The robotic arm moves the item according to the transport trajectory; Step S5, Reaching the Placement Point: The robotic arm reaches the placement point; it is determined whether the CPU is performing parallel computation. If there is an object to be grasped in the grasping area, the CPU executes the following two sub-steps in parallel: Step S51: Calculate the new grab point: Calculate the next grab point; Step S52: Path planning: Plan the path from the starting point to the newly calculated grab point; If there is no object to be grasped in the grasping area, the CPU will not perform calculations. Step S6: Place the item: The robotic arm places the item at the designated placement point in the stacking area; Step S7, Movement: The robotic arm moves from the placement point to the starting point; Step S8, Return to Starting Point: The robotic arm returns to the starting point. It checks whether the CPU is performing parallel computation. If there is an object to be grasped or placed, the CPU executes the following two sub-steps in parallel: Step S81 Calculate the new placement point: Calculate the next placement point; Step S82: Path planning for transporting goods and services: Plan the transport path from the grab point in step S51 to the placement point in step S81. If there are no items to be grabbed or placed in the grabbing area, the CPU will not perform calculations. Step S9, End Judgment: Determine whether all transport tasks have been completed. If completed, return to the starting point and end; otherwise, return to step S2 to continue execution.
5. The method for improving the handling efficiency of a robotic arm by parallelizing computational tasks as described in claim 4, characterized in that: In step S5, the calculation of the new gripping point is based on the current distribution of items in the gripping area, the movement limitations of the robotic arm, and the preset gripping strategy.
6. The method for improving the handling efficiency of a robotic arm by parallelizing computational tasks as described in claim 4, characterized in that: In step S8, the calculation of the new placement point is performed by comprehensively considering the spatial conditions of the stacking area, the placement rules of the items, and the reachability of the robotic arm.