Human-computer interaction method, robot and computer readable storage medium

Abstract

The invention discloses a man-machine interaction method, a robot and a computer readable storage medium. The man-machine interaction method is used for the robot, and a first corresponding relation among reference time for completing a task, points of an operator and first bonus is pre-stored; the man-machine interaction method comprises the steps of obtaining a target task; obtaining personal information of a current operator; prompting the current operator to execute the target task; determining the completion time used by the current operator to complete the target task; determining an integral change value and a bonus change value according to the completion time, the current integral and the first corresponding relation; according to the integral change value and the bonus change value, incentive information is determined; and outputting the excitation information to the current operator. According to the man-machine interaction method, the integral change value and the bonus change value of the target task are determined according to the completion time and the grade of the current operator, and the incentive information is determined and output to the current operator, so that the current operator is incentive to improve the picking efficiency, and meanwhile, the man-machine adaptability is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of robots, and more particularly, to a human - machine interaction method, a robot, and a computer - readable storage medium. Background Art

[0002] In modern warehousing and logistics management, it is crucial to improve the picking efficiency. At present, there are already some automation technologies, such as automated navigation robots and automated picking systems, used to improve the picking efficiency. In the related art, automation technologies are mostly used to mechanically perform repetitive tasks, with low human - machine cooperation and low human - machine collaborative picking efficiency. Summary of the Invention

[0003] Embodiments of the present invention provide a human - machine interaction method, a robot, and a computer - readable storage medium.

[0004] Embodiments of the present invention provide a human - machine interaction method for a robot, which pre - stores a first correspondence relationship among a reference time for completing a task, the points of an operator, and a first bonus, where the shorter the reference time, the higher the corresponding points and the higher the corresponding first bonus; the human - machine interaction method includes: obtaining a target task; obtaining personal information of a current operator, where the personal information includes the current points of the operator; prompting the current operator to execute the target task; after the current operator completes the target task, determining a completion time taken by the current operator to complete the target task; determining a points change value and a bonus change value obtained by the current operator for completing the target task according to the completion time, the current points of the current operator, and the first correspondence relationship; determining incentive information for the current operator according to the points change value and the bonus change value; and outputting the incentive information to the current operator.

[0005] In this way, by displaying the target task to prompt the content of the target task for the current operator to execute, and by counting the completion time of the current operator for completing the target task, determining the points change value and the bonus change value of the current target task according to the completion time, the points of the current operator, and the first correspondence relationship, so as to determine the incentive information and output the incentive information to the current operator, to motivate the current operator to improve the picking efficiency and at the same time improve the human - machine cooperation degree.

[0006] In some embodiments, the robot further includes a scanning module. The obtaining of the personal information of the current operator includes controlling the scanning module to scan the work permit of the current operator to obtain the personal information of the current operator. The determining of the completion time taken by the current operator to complete the target task includes: receiving a completion signal input by the current operator indicating the completion of the target task; and taking the time from scanning the work permit of the current operator to receiving the completion signal as the completion time.

[0007] In this way, according to the time from scanning the work permit of the current operator to receiving the completion signal, the completion time for completing the target task can be determined.

[0008] In some embodiments, the determining of the integral change value obtained by the current operator for completing the target task according to the completion time, the current integral of the current operator, and the first corresponding relationship includes: determining the reference time corresponding to the current integral of the current operator according to the first corresponding relationship; and determining the integral change value according to the completion time and the reference time corresponding to the current integral of the current operator. Wherein, when the completion time is less than or equal to the reference time corresponding to the current integral of the current operator, the integral change value is a positive number; when the completion time is greater than the reference time corresponding to the current integral of the current operator, the integral change value is a negative number.

[0009] In this way, by setting up a reward and punishment system, the picking enthusiasm of the operator can be motivated through human-computer interaction, thereby improving the picking efficiency.

[0010] In some embodiments, the method further includes: pre-storing a second corresponding relationship between the level of the operator and the points of the operator, wherein the higher the level, the higher the corresponding points of the operator; the determining the integral change value according to the completion time and the reference time corresponding to the current integral of the current operator includes: determining whether the completion time is less than or equal to the reference time corresponding to the current integral of the current operator, and if so, determining the integral change value as a first preset value, the first preset value being a positive number; if not, performing: determining a reference reference time corresponding to the completion time, the reference reference time being the smallest one among the reference times larger than the completion time in the first corresponding relationship; determining the operator points corresponding to the reference reference time according to the first corresponding relationship; determining the actual level corresponding to the operator points corresponding to the reference reference time according to the second corresponding relationship; determining the current level corresponding to the current integral of the current operator according to the second corresponding relationship; determining the level gap between the current level and the actual level; and determining the integral change value according to the level gap, the integral change value being a negative number, and the larger the level gap, the smaller the integral change value.

[0011] In this way, by determining the integral change value and the bonus change value of the current operator according to the comparison result of the completion time and the reference time, and setting up a reward and punishment system, the operator is further motivated to improve work efficiency.

[0012] In some embodiments, the determining the bonus change value obtained by the current operator for completing the target task according to the completion time, the current integral of the current operator, and the first corresponding relationship includes: determining the reference time and the corresponding bonus corresponding to the current integral of the current operator according to the first corresponding relationship; determining whether the completion time is less than or equal to the reference time corresponding to the current integral of the current operator, and if so, determining the bonus change value as the bonus corresponding to the current integral of the current operator, otherwise, determining the bonus change value as zero or a negative number.

[0013] In this way, according to the first corresponding relationship, the bonus change value obtained by the current operator for completing the target task is determined, and when the current operator completes the task overtime, the bonus change value is 0 or a negative value to warn the current operator, thereby motivating the current operator to improve the picking efficiency.

[0014] In some embodiments, the personal information includes the current integral and the current bonus of the operator; the determining the incentive information of the current operator according to the integral change value and the bonus change value includes: updating the current integral and the current bonus of the current operator according to the integral change value and the bonus change value, and the incentive information includes the current integral and the current bonus of the current operator.

[0015] In this way, according to the integral change value and the bonus change value, the current integral and the current bonus of the current operator are updated, realizing the dynamic update of the current integral and the current bonus, and making the incentive information include the current integral and the current bonus of the current operator, so that the current operator can know the current integral and the current bonus from the robot, thereby improving the work efficiency of the current operator.

[0016] In some embodiments, after updating the current integral and the current bonus of the current operator according to the integral change value and the bonus change value, it further includes: sending the current integral of the current operator to the server, so that the server ranks the current integrals of each operator in descending order, and displays the ranking result and the corresponding second bonus on the public display screen. The more the current integral, the higher the corresponding ranking, and the more the corresponding second bonus.

[0017] In this way, by ranking the integrals to obtain the ranking result and displaying it on the public display screen, the work enthusiasm of the operator can be stimulated; by setting the second bonus, the operator can be further motivated to improve his own integral and ranking to obtain more bonuses.

[0018] In some embodiments, a plurality of the target tasks form a target total task, and the human-computer interaction method further includes: after the target total task is completed and the task result is obtained, reviewing the task result; if the task result is incorrect, determining the errant operator who caused the error; determining the integral deduction value and the bonus deduction value for the errant operator; and updating the current integral and the current bonus of the errant operator according to the integral deduction value and the bonus deduction value of the errant operator.

[0019] In this way, by reviewing the task result, it can be determined whether the task result is incorrect, and when there is an error, a certain punishment can be imposed on the operator, and the integral deduction amount and the bonus deduction amount are determined according to the level of the operator, so as to further motivate the operator to improve the picking accuracy and efficiency.

[0020] An embodiment of the present invention provides a robot, which includes one or more processors and a memory. The memory stores a computer program, and when the computer program is executed by the processor, the steps of the human-computer interaction method in any of the above embodiments are implemented.

[0021] In this way, by displaying the target task to prompt the current operator to execute the content of the target task, and by counting the completion time of the current operator for completing the target task, the integral change value and the bonus change value of the current target task are determined according to the completion time, the integral of the current operator, and the first corresponding relationship, so as to determine the incentive information, and the incentive information is output to the current operator to encourage the current operator to improve the picking efficiency and at the same time improve the human-machine cooperation degree.

[0022] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the human-computer interaction method in any of the above embodiments are implemented.

[0023] In this way, by displaying the target task to prompt the current operator to execute the content of the target task, and by counting the completion time of the current operator for completing the target task, the integral change value and the bonus change value of the current target task are determined according to the completion time, the integral of the current operator, and the first corresponding relationship, so as to determine the incentive information, and the incentive information is output to the current operator to encourage the current operator to improve the picking efficiency and at the same time improve the human-machine cooperation degree.

[0024] The additional aspects and advantages of the present invention will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The above and / or additional aspects and advantages of the present invention will become obvious and easy to understand from the description of the embodiments in conjunction with the following drawings, where:

[0026] Figure 1 is a schematic flow chart of the interaction method according to an embodiment of the present invention;

[0027] Figure 2 is a schematic diagram of the interaction device according to an embodiment of the present invention;

[0028] Figure 3 is a schematic flow chart of the interaction method according to an embodiment of the present invention;

[0029] Figure 4 is a schematic diagram of the first determination module according to an embodiment of the present invention;

[0030] Figure 5 is a schematic flow chart of the interaction method according to an embodiment of the present invention;

[0031] Figure 6 is a schematic diagram of the statistics module according to an embodiment of the present invention;

[0032] Figure 7 is a schematic flow chart of the interaction method according to an embodiment of the present invention;

[0033] Figure 8 It is a schematic diagram of the interaction device according to an embodiment of the present invention;

[0034] Figure 9 It is a flowchart of the interaction method according to an embodiment of the present invention;

[0035] Figure 10 It is a schematic diagram of the interaction device according to an embodiment of the present invention;

[0036] Figure 11 It is a flowchart of the interaction method according to an embodiment of the present invention;

[0037] Figure 12 It is a schematic diagram of the interaction device according to an embodiment of the present invention;

[0038] Figure 13 It is a flowchart of the interaction method according to an embodiment of the present invention;

[0039] Figure 14 It is a schematic diagram of the interaction device according to an embodiment of the present invention;

[0040] Figure 15 It is a flowchart of the interaction method according to an embodiment of the present invention;

[0041] Figure 16 It is a schematic diagram of the interaction device according to an embodiment of the present invention. Detailed Embodiments

[0042] The following details the embodiments of the present invention. The embodiments are illustrated in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0043] In modern warehousing and logistics management, improving the picking efficiency is crucial. However, in the warehousing picking scenario, how to effectively motivate the operators to improve their work efficiency and accuracy is a major challenge. Operators play an indispensable role in the entire warehousing system. Although robotic technologies have been applied to optimize warehouse management, the key factor of human is often overlooked. Operators need to perform various tasks in the complex warehouse environment, including picking, verification, and packing. There are already some automation technologies, such as automated navigation robots and automated picking systems, used to improve the picking efficiency. However, automation technologies are mostly used to mechanically perform repetitive tasks, with low human-machine cooperation and low human-machine collaborative picking efficiency; at the same time, the subjective factors of operators, such as enthusiasm, motivation, and job satisfaction, are ignored.

[0044] In the related art, there is a lack of methods and systems for improving the motivation of operators. These methods and systems should take into account the psychological factors and incentive mechanisms of operators to ensure that they show higher efficiency and lower error rates in their work. Traditional salary systems are often insufficient to stimulate the motivation of operators because they need to perform repetitive and boring work, which easily makes them feel tired and lose motivation. Therefore, there is an urgent need for a new method and system to improve the motivation of operators by combining robotics, data analysis, and human-computer interaction technologies, thereby improving the efficiency of human-robot collaborative picking.

[0045] Please refer to Figure 1 , an embodiment of the present invention provides a human-computer interaction method for a robot, which pre-stores the first correspondence relationship between the benchmark time for completing a task, the points of an operator, and the first bonus, where the shorter the benchmark time, the higher the corresponding points, and the higher the corresponding first bonus; the human-computer interaction method includes:

[0046] 01: Obtain a target task;

[0047] 02: Obtain the personal information of the current operator, where the personal information includes the current points of the operator;

[0048] 03: Prompt the current operator to perform the target task;

[0049] 04: After the current operator completes the target task, determine the completion time used by the current operator to complete the target task;

[0050] 05: According to the completion time, the current points of the current operator, and the first correspondence relationship, determine the point change value and bonus change value obtained by the current operator for completing the target task;

[0051] 06: Determine the incentive information of the current operator according to the point change value and bonus change value;

[0052] 07: Output the incentive information to the current operator.

[0053] Specifically, please refer to Figure 2, the human-computer interaction method according to the embodiments of the present invention can be implemented by the human-computer interaction device 100 according to the embodiments of the present invention. The human-computer interaction device 100 includes a first acquisition module 10, a second acquisition module 20, a prompt module 30, a first determination module 40, a second determination module 50, a third determination module 60, and an output module 70. Among them, the first acquisition module 10 can be used to acquire a target task; the second acquisition module 20 can be used to acquire the personal information of the current operator, and the personal information includes the current points of the operator; the prompt module 30 can be used to prompt the current operator to execute the target task; the first determination module 40 can be used to determine the completion time used by the current operator to complete the target task after the target operator completes the target task; the second determination module 50 can be used to determine the integral change value and bonus change value obtained by the current operator for completing the target task according to the completion time, the current points of the current operator, and the first corresponding relationship; the third determination module 60 can be used to determine the incentive information of the current operator according to the integral change value and bonus change value; the output module 70 can be used to output the incentive information to the current operator.

[0054] Among them, the target task can be a picking task. Each picking task corresponds to a Stock Keeping Unit (SKU). The operator includes a picker. Before the current operator performs the picking task, the robot acquires the personal information of the current operator, that is, confirms the name, level, current points, and current bonus of the current operator, and displays the details of this picking task on the display screen, showing the SKU information that needs to be picked to prompt the current operator to perform the picking task for picking, and waits for the current operator to operate. The SKU information can include the shelf position where the SKU is located, the type of the SKU, and image information, etc.; the current operator picks the required goods on the corresponding shelf according to the SKU information displayed on the screen, places the goods at the set position required by the robot, such as on the storage tray, and clicks the confirmation button on the display screen to complete this picking task; the robot counts the completion time used by the current operator to complete the picking task, and determines whether the completion time is within the time required by the level corresponding to the points according to the points of the current operator, determines the integral change value and bonus change value obtained for completing this picking task, determines the incentive information, and outputs the incentive information. The output method can be to display the integral change value, bonus change value, total points, and total bonus on the screen to prompt the current operator of the points and bonus obtained from this picking. By rewarding the excellent performance of the current operator, the enthusiasm is stimulated. This measure makes the picking work more attractive and challenging, effectively reduces the phenomena of laziness and loafing, thereby motivating the operator to improve the picking efficiency. In addition, the real-time data monitoring and automatic evaluation of the operator's work by the robot weaken the subjectivity of the manual evaluation, ensure the fairness and accuracy of the evaluation, and make the work performance of the operator based on objective data, rather than simply relying on the traditional time or piecework system.

[0055] In this way, by displaying the target task to prompt the current operator to execute the content of the target task, and by counting the completion time of the current operator for completing the target task, the integral change value and bonus change value of the current target task are determined according to the completion time, the integral of the current operator, and the first corresponding relationship, so as to determine the incentive information, and the incentive information is output to the current operator to encourage the current operator to improve the picking efficiency and improve the human-machine cooperation degree at the same time.

[0056] Please refer to Figure 3 , in some embodiments, the robot further includes a scanning module to obtain the personal information of the current operator, including controlling the scanning module to scan the work card of the current operator to obtain the personal information of the current operator; step 04 (determining the completion time used by the current operator to complete the target task) includes:

[0057] 0401: Receive the completion signal input by the current operator to confirm the completion of the target task;

[0058] 0402: Use the time from scanning the work card of the current operator to receiving the completion signal as the completion time.

[0059] Specifically, please refer to Figure 4 , step 0401 can be implemented by the receiving sub-module 41 of the first determination module 40, and step 0402 can be implemented by the first determination sub-module 42 of the first determination module 40, that is, the receiving sub-module 41 can be used to receive the completion signal input by the current operator to confirm the completion of the target task; the first determination sub-module 42 can be used to use the time from scanning the work card of the current operator to receiving the completion signal as the completion time.

[0060] Among them, the scanning module can include a barcode scanner. When the current operator arrives near the robot, the robot can control the display screen to display a scanning reminder to remind the current operator to use the barcode scanner to scan the work card of the current operator, so that the robot can determine the personal information of the current operator and display the personal information of the operator on the display screen for the operator to determine whether the personal information obtained by the robot's scanning is correct. After the current operator places the picked SKU in the set position to complete the picking, the current operator clicks the OK button on the display screen to send a completion signal to the robot, informing the robot that the picking task is completed; after receiving the completion information, the robot determines that the current operator has completed the picking task, counts the time from scanning the work card to determine the identity information to clicking the OK button by the current operator as the completion time, and determines the integral change value and bonus change value of the current operator for completing this picking task according to the integral of the operator.

[0061] Thus, according to the time from scanning the operator's work card to receiving the completion signal, the completion time of the target task can be determined.

[0062] Please refer to Figure 5 , in some embodiments, step 05 (determining the integral change value obtained by the current operator for completing the target task according to the completion time, the current integral of the current operator, and the first correspondence) includes:

[0063] 0501: According to the first correspondence, determine the reference time corresponding to the current integral of the current operator;

[0064] 0502: According to the completion time and the reference time corresponding to the current integral of the current operator, determine the integral change value; wherein, when the completion time is less than or equal to the reference time corresponding to the current integral of the current operator, the integral change value is positive; when the completion time is greater than the reference time corresponding to the current integral of the current operator, the integral change value is negative.

[0065] Specifically, please refer to Figure 6 , step 0501 can be implemented by the second determination sub-module 51 of the second determination module 50, and step 0502 can be implemented by the third determination sub-module 52 of the second determination module 50. That is to say, the second determination sub-module 51 can be used to determine the reference time corresponding to the current integral of the current operator according to the first correspondence; the third determination sub-module 52 can be used to determine the integral change value according to the completion time and the reference time corresponding to the current integral of the current operator; wherein, when the completion time is less than or equal to the reference time corresponding to the current integral of the current operator, the integral change value is positive; when the completion time is greater than the reference time corresponding to the current integral of the current operator, the integral change value is negative.

[0066] Among them, the standard time TS, achievement levels, etc. are preset. The standard time is the time required for a junior operator to complete one SKU. The unit of the standard time TS is seconds. The achievement levels include junior operator, intermediate operator, senior operator, picking expert, and picking master. After reaching the promotion points required for the corresponding level, one can become an operator of that level. The first correspondence is shown in Table 1:

[0067] Achievement Level Points Required for Promotion Benchmark Time First Prize Junior Operator 0 TS Bonus Intermediate Operator 100 0.9 * TS 1.1 * Bonus Senior Operator 200 0.8 * TS 1.2 * Bonus Picking Expert 500 0.7 * TS 1.5 * Bonus Picking Master 1000 0.5 * TS 2 * Bonus

[0068] Table 1

[0069] As can be seen from Table 1, the higher the score of an operator, the shorter the benchmark time required to complete the current task. The benchmark time is the longest time required for an operator to complete one SKU. If the completion time of the current operator for the picking task is greater than the benchmark time required for the level corresponding to the current score of the current operator, the score change value is negative; if the completion time of the current operator for the picking task is not greater than the benchmark time required for the level corresponding to the current score of the current operator, the score change value is positive.

[0070] In one embodiment, the current score of the current operator is 480, then the benchmark time of the current operator is 0.8TS; the completion time of the current operator for the picking task is 0.75TS. Since 0.75TS is less than 0.8TS, the score obtained by the current operator is positive.

[0071] In another embodiment, the current score of the current operator is 520, then the benchmark time of the current operator is 0.7TS; the completion time of the current operator for the picking task is 0.75TS. Since 0.75TS is greater than 0.7TS, the score obtained by the current operator is negative.

[0072] In this way, by setting up a reward and punishment system, the picking enthusiasm of operators can be stimulated through human-computer interaction, thereby improving the picking efficiency.

[0073] Please refer to Figure 7 , in some embodiments, the method further includes:

[0074] 08: Pre-store the second corresponding relationship between the level of the operator and the score of the operator, where the higher the level, the higher the corresponding score of the operator;

[0075] Step 0502 (determine the score change value according to the completion time and the benchmark time corresponding to the current score of the current operator) includes:

[0076] 05021: Determine whether the completion time is less than or equal to the benchmark time corresponding to the current score of the current operator,

[0077] If so, then:

[0078] 05022: Determine that the score change value is the first preset value, and the first preset value is a positive number;

[0079] If not, then execute:

[0080] 05023: Determine the reference benchmark time corresponding to the completion time, and the reference benchmark time is the smallest one among the benchmark times greater than the completion time in the first corresponding relationship;

[0081] 05024: Determine the operator score corresponding to the reference benchmark time according to the first corresponding relationship.

[0082] 05025: Determine the actual level corresponding to the operator's points at the reference base time according to the second correspondence relationship.

[0083] 05026: Determine the current level corresponding to the current points of the current operator according to the second correspondence relationship.

[0084] 05027: Determine the level gap between the current level and the actual level.

[0085] 05028: Determine the points change value according to the level gap. The points change value is negative, and the larger the level gap, the smaller the points change value.

[0086] Specifically, please refer to Figure 8 , step 08 can be implemented by the pre-storage module 80 of the human-machine interaction device 100, step 05021 can be implemented by the judgment unit 521 of the third determination sub-module 52, step 05022 can be implemented by the first determination unit 522 of the third determination sub-module 52, step 05023 can be implemented by the second determination unit 523 of the third determination sub-module 52, step 05024 can be implemented by the third determination unit 524 of the third determination sub-module 52, step 05025 can be implemented by the fourth determination unit 525 of the third determination sub-module 52, step 05026 can be implemented by the fifth determination unit 526 of the third determination sub-module 52, step 05027 can be implemented by the sixth determination unit 527 of the third determination sub-module 52, step 05028 can be implemented by the sixth determination unit 528 of the third determination sub-module 52. That is to say, the pre-storage module 80 can be used to pre-store the second correspondence relationship between the level of the operator and the points of the operator, where the higher the level, the higher the corresponding points of the operator; the judgment unit 521 can be used to judge whether the completion time is less than or equal to the reference time corresponding to the current points of the current operator; the first determination unit 522 can be used to determine that the points change value is the first preset value, and the first preset value is a positive number; the second determination unit 523 can be used to determine the reference base time corresponding to the completion time, and the reference base time is the smallest one among the base times larger than the completion time in the first correspondence relationship; the third determination unit 524 can be used to determine the operator points corresponding to the reference base time according to the first correspondence relationship; the fourth determination unit 525 can be used to determine the actual level corresponding to the operator points corresponding to the reference base time according to the second correspondence relationship; the sixth determination unit 527 can be used to determine the current level corresponding to the current points of the current operator according to the second correspondence relationship; the fifth determination unit 526 can be used to determine the level gap between the current level and the actual level; the sixth determination unit 528 can be used to determine the points change value according to the level gap. The points change value is negative, and the larger the level gap, the smaller the points change value.

[0087] Among them, the second corresponding relationship can be the corresponding relationship between the integral and the achievement level as shown in Table 1, and the second corresponding relationship is pre-stored in the robot. The first preset value can be 1, that is, when the completion time used by the operator to complete the current picking task is lower than the reference time corresponding to the operator's level, the integral change value is 1, that is, the operator obtains 1 integral; when it is determined that the completion time exceeds the reference time, the integral is deducted according to the difference between the level corresponding to the completion time and the operator's level, that is, the integral change value is negative. The robot determines the reference reference time corresponding to the completion time, and the reference reference time is the reference time that is greater than the completion time and closest to the completion time; determines the actual level corresponding to the reference reference time, and the actual level is the level corresponding to the completion time; and determines the current level corresponding to the current integral of the current operator according to the second corresponding relationship, and the current level is the level of the current operator, and the integral deduction value can be determined according to the difference between the actual level and the current level.

[0088] In one embodiment, the reference time TS is 100s, and the operator's level is a picking expert. Then the minimum picking time requirement for the operator is 70s, and the picking time for the operator to complete the current picking task is 98s, corresponding to the level of a junior operator. The difference between the actual level and the current level is -2. Then the integral change value of the operator this time is -2, that is, 2 integral are deducted, the bonus change value is 0, and at the same time the display screen shows a negative picture, stimulating the operator to improve work efficiency in addition to prompting the integral deducted this time.

[0089] In this way, by determining the integral change value and the bonus change value of the current operator according to the comparison result between the completion time and the reference time, and setting up a reward and punishment system, the operator is further motivated to improve work efficiency.

[0090] Please refer to Figure 9 , in some embodiments, step 05 (determining the bonus change value obtained by the current operator for completing the target task according to the completion time, the current integral of the current operator, and the first corresponding relationship) includes:

[0091] 0503: According to the first corresponding relationship, determine the reference time and the corresponding bonus corresponding to the current integral of the current operator;

[0092] 0504: Determine whether the completion time is less than or equal to the reference time corresponding to the current integral of the current operator. If so, determine that the bonus change value is the bonus corresponding to the current integral of the current operator; otherwise, determine that the bonus change value is zero or a negative number.

[0093] Specifically, please refer to Figure 10, step 0503 can be implemented by the fourth determination sub-module 53 of the second determination module 50, and step 0504 can be implemented by the judgment sub-module 54 of the second determination module 50. That is to say, the fourth determination sub-module 53 can be used to determine the reference time and the corresponding bonus corresponding to the current points of the current operator according to the first correspondence relationship; the judgment sub-module 54 can be used to judge whether the completion time is less than or equal to the reference time corresponding to the current points of the current operator. If so, it is determined that the bonus change value is the bonus corresponding to the current points of the current operator; otherwise, it is determined that the bonus change value is zero or a negative number.

[0094] Among them, the basic bonus (Bonus) of the first bonus is preset. The basic bonus is the bonus obtained by a junior operator for completing one SKU, and the unit of the basic bonus is yuan. For example, please refer to Table 1. If the bonus obtained by a junior operator for completing one SKU is 10 yuan, then the bonus obtained by a picking expert for completing one SKU is 15 yuan. Judge whether the completion time is less than or equal to the reference time corresponding to the current points of the current operator. When the completion time is not greater than the reference time, the bonus change value is the bonus corresponding to the current level, and the higher the level of the current operator, the higher the bonus change value obtained; when the completion time is greater than the reference time, the bonus change value is zero or a negative value to give a certain warning to the current operator.

[0095] In this way, according to the first correspondence relationship, the bonus change value obtained by the current operator for completing the target task is determined, and when the current operator completes the task overtime, the bonus change value is 0 or a negative value to give a warning to the current operator, so as to motivate the current operator to improve the picking efficiency.

[0096] Please refer to Figure 11 , in some embodiments, the personal information includes the current points and the current bonus of the operator; step 06 (determining the incentive information of the current operator according to the points change value and the bonus change value) includes:

[0097] 0601: Update the current points and the current bonus of the current operator according to the points change value and the bonus change value. The incentive information includes the current points and the current bonus of the current operator.

[0098] Specifically, please refer to Figure 12 , step 0601 can be implemented by the update sub-module 61 of the third determination module 60. That is to say, the update sub-module 61 can be used to update the current points and the current bonus of the current operator according to the points change value and the bonus change value. The incentive information includes the current points and the current bonus of the current operator.

[0099] Among them, according to the integral change value and the bonus change value, the current integral and the current bonus of the current operator can be updated, so as to dynamically update the current integral and the current bonus of the operator after the current operator completes the target task. When the current operator completes the target task next time, the robot can obtain the updated current integral and current bonus of the operator. The robot can output the incentive information including the updated current integral and current bonus to the current robot. For example, it can be displayed on the display screen of the robot to encourage the current operator to improve work efficiency.

[0100] In this way, according to the integral change value and the bonus change value, the current integral and the current bonus of the current operator are updated, realizing the dynamic update of the current integral and the current bonus, and making the incentive information include the current integral and the current bonus of the current operator, so that the current operator can know the current integral and the current bonus from the robot, thereby improving the work efficiency of the current operator.

[0101] Please refer to Figure 13 , in some embodiments, after updating the current integral and the current bonus of the current operator according to the integral change value and the bonus change value, it further includes:

[0102] 09: Send the current integral of the current operator to the server, so that the server ranks the current integrals of each operator in descending order, and displays the ranking result and the corresponding second bonus on the public display screen. The more the current integral, the higher the corresponding ranking, and the more the corresponding second bonus.

[0103] Specifically, please refer to Figure 14 , step 09 can be implemented by the sending module 90 of the human-machine interaction device 100. That is to say, the sending module 90 can be used to send the current integral of the current operator to the server, so that the server ranks the current integrals of each operator in descending order, and displays the ranking result and the corresponding second bonus on the public display screen. The more the current integral, the higher the corresponding ranking, and the more the corresponding second bonus.

[0104] Among them, a second bonus pool and the distribution rules of the second bonus pool are preset. The current scores of all operators are ranked from high to low to obtain a ranking result, and the ranking result is displayed on a public display screen in real time, so that all operators can determine their own rankings, thereby motivating the work enthusiasm of the operators; and the second bonus of the second bonus pool is distributed according to the ranking result after the end of a day's work. The distribution rules of the second bonus of the second bonus pool are shown in Table 2. In one embodiment, the second bonus of the second bonus pool is 1000 yuan. Then, the operator ranked first in the daily score can obtain 300 yuan of the second bonus, and the 4th to 10th ranked operators can respectively obtain 40 yuan of the second bonus. The reward policy not only considers the individual work efficiency, but also provides additional rewards for outstanding employees in the group, and also punishes mistakes in work. This helps to mobilize the enthusiasm of all employees and improve work efficiency.

[0105] Ranking Results Second Prize First Place 30％ Second Place 20％ Third Place 10％ 4th - 10th Place Split the remaining 40%

[0106] Table 2

[0107] In this way, by ranking the scores to obtain a ranking result and displaying it on a public display screen, the work enthusiasm of the operators can be stimulated; by setting the second bonus, the operators can be further motivated to improve their own scores and rankings to obtain more bonuses.

[0108] Please refer to Figure 15 , in some embodiments, a plurality of target tasks form a target total task, and the human-computer interaction method further includes:

[0109] 011: After the target total task is completed and the task result is obtained, review the task result;

[0110] 012: If there is an error in the task result, determine the operator who made the mistake causing the error;

[0111] 013: Determine the score deduction value and bonus deduction value for the operator who made the mistake;

[0112] 014: According to the score deduction value and bonus deduction value of the operator who made the mistake, update the current score and current bonus of the said operator who made the mistake.

[0113] Specifically, please refer to Figure 16, Step 011 can be implemented by the review module 110 of the human-machine interaction device 100, step 012 can be implemented by the fourth determination module 120 of the human-machine interaction device 100, step 013 can be implemented by the fifth determination module 130 of the human-machine interaction device 100, and step 014 can be implemented by the update module 140 of the human-machine interaction device 100. That is to say, the review module 110 can be used to review the task result after the target total task is completed and the task result is obtained; the fourth determination module 120 can be used to determine the errant operator who caused the error if the task result is incorrect; the fifth determination module 130 can be used to determine the integral deduction value and bonus deduction value for the errant operator; and the update module 140 can be used to update the current integral and current bonus of the errant operator according to the integral deduction value and bonus deduction value of the errant operator.

[0114] Among them, a packing review area is provided in the warehouse, and the goods that have completed picking are reviewed and packed in the packing review area. The task result is the goods picked by the operator according to the picking task. The robot can go to the packing review area with the task result obtained from completing the total picking task after the operator has completed all picking tasks, and review the task result in the packing review area to determine whether there are errors such as wrong picking or missing picking. If it is determined that the task result is incorrect, the integral deduction value and bonus deduction value are determined according to the level of the operator who completed the picking task corresponding to the error. The integral deduction value can be twice the integral obtained by the level for completing one SKU, and the bonus deduction value can be twice the bonus obtained by the level for completing one SKU for punishment. At the same time, the robot updates the current integral according to the integral change value and updates the current bonus according to the bonus change value.

[0115] In addition, after the end of a day's work, the total bonus obtained by the operator is the result obtained by adding the first bonus and the second bonus obtained from completing the picking task and then subtracting the bonus deduction value. The first bonus is the sum of the bonus change values obtained each time the picking task is completed, the second bonus is the bonus allocated according to the ranking in the ranking bonus pool, and the bonus deduction value is the sum of the bonus deduction values at each review. In one embodiment, the levels, integrals, and bonuses of the operators are cleared every day to ensure that all operators start from the same starting point on a new day, and all operators start the day's work as junior operators for promotion.

[0116] In this way, by reviewing the task result, it can be determined whether there is an error in the task result, and when there is an error, the operator is punished to a certain extent, and the integral deduction amount and bonus deduction amount are determined according to the level of the operator to further encourage the operator to improve the picking accuracy rate and efficiency.

[0117] An embodiment of the present invention provides a robot system, which includes multiple robots, a server, and a public display screen. Each robot includes a display screen. The server stores the current scores and current bonuses of all operators. The robot is configured to: obtain a target task; obtain the personal information of the current operator, where the personal information includes the current score of the operator; prompt the current operator to execute the target task; after the target operator completes the target task, determine the completion time taken by the current operator to complete the target task; according to the completion time, the current score of the current operator, and a first corresponding relationship, determine the score change value and bonus change value obtained by the current operator for completing the target task; according to the score change value and bonus change value, determine the incentive information for the current operator; output the incentive information to the current operator; and send the score change value and bonus change value to the server. The server is configured to: determine the current score and current bonus according to the score change value and bonus change value; rank the current scores of all target operators to obtain a ranking result; transmit the ranking result, the current score, and the current bonus to the public display screen; and the public display screen is configured to display the ranking result, the total score, and the total bonus of each target operator.

[0118] Specifically, the robot can obtain the personal information of the current operator from the server, or send the current score and current bonus to the server and the public display screen to display the updated personal information on the public display screen, and display the score deduction value and bonus deduction value to publicize the score information, further urging the operator to pick goods correctly and improving the accuracy of picking goods. The server can rank the current scores of all operators to obtain a ranking result and send the ranking result to the public display screen for publicity.

[0119] In this way, through the cooperation of the robot, the server, and the public display screen, the current score and current bonus of the robot can be updated in real time, and the ranking result can be obtained by ranking according to the current score. The current score, current bonus, and ranking result are displayed on the public display screen so that all operators can obtain the score information and ranking information to stimulate the work enthusiasm of the operators.

[0120] An embodiment of the present invention provides a robot, which includes one or more processors and a memory. The memory stores a computer program. When the computer program is executed by the processor, the steps of the human-machine interaction method in any of the above embodiments are implemented.

[0121] Specifically, the robot can be a warehousing robot, which can be used to cooperate with an operator in the warehouse to complete the picking task. The warehousing robot includes a display screen and a scanning module.

[0122] In this way, by prompting the current operator to complete the content of the target task, and counting the completion time of the current operator for completing the target task, the integral change value and bonus change value of this target task are determined according to the completion time and the level of the current operator, and the incentive information is determined according to the integral change value and bonus change value and output to the current operator to motivate the current operator to improve the picking efficiency and at the same time improve the human-machine cooperation degree.

[0123] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the steps of the human-computer interaction method in any of the above embodiments are implemented. In this way, by prompting the current operator to complete the content of the target task, and counting the completion time of the current operator for completing the target task, the integral change value and bonus change value of this target task are determined according to the completion time and the level of the current operator, and the incentive information is determined according to the integral change value and bonus change value and output to the current operator to motivate the current operator to improve the picking efficiency and at the same time improve the human-machine cooperation degree.

[0124] In this way, by prompting the current operator to complete the content of the target task, and counting the completion time of the current operator for completing the target task, the integral change value and bonus change value of this target task are determined according to the completion time and the level of the current operator, and the incentive information is determined according to the integral change value and bonus change value and output to the current operator to motivate the current operator to improve the picking efficiency and at the same time improve the human-machine cooperation degree.

[0125] In the description of this specification, the descriptions with reference to terms such as "one embodiment", "some embodiments", "schematic embodiments", "examples", "specific examples" or "some examples" etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. In addition, without conflict, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0126] In addition, the term "connection" should be understood in a broad sense. For example, it may include fixed connection, may also include detachable connection, or integral connection; it may include direct connection, may also be indirectly connected through an intermediate medium, and may also include the communication inside two elements. For those of ordinary skill in the art, the specific meaning of the above terms in the present invention can be understood in specific situations.

[0127] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the quantity of the technical features indicated. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0128] Any process or method description shown in a flowchart or described otherwise herein may be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of the present invention includes additional implementations in which functions may be executed not in the order shown or discussed, including substantially concurrently or in reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0129] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A human-computer interaction method for a robot, characterized in that, Pre-store the first correspondence relationship among the benchmark time for completing a task, the points of the operator, and the first bonus, where the shorter the benchmark time, the higher the corresponding points, and the higher the corresponding first bonus; The human-computer interaction method includes: Obtain a target task; Obtain the personal information of the current operator, where the personal information includes the current points of the operator; Prompt the current operator to execute the target task; After the current operator completes the target task, determine the completion time used by the current operator to complete the target task; According to the completion time, the current points of the current operator, and the first correspondence relationship, determine the points change value and the bonus change value obtained by the current operator for completing the target task; According to the points change value and the bonus change value, determine the incentive information of the current operator; Output the incentive information to the current operator.

2. The human-computer interaction method according to claim 1, wherein The robot further includes a scanning module, and obtaining the personal information of the current operator includes: Control the scanning module to scan the work permit of the current operator to obtain the personal information of the current operator; Determining the completion time used by the current operator to complete the target task includes: Receive the completion signal input by the current operator to confirm the completion of the target task; Take the time from scanning the work permit of the current operator to receiving the completion signal as the completion time.

3. The human-computer interaction method according to claim 1, characterized in that, The determining the points change value obtained by the current operator for completing the target task according to the completion time, the current points of the current operator, and the first correspondence relationship includes: According to the first correspondence relationship, determine the benchmark time corresponding to the current points of the current operator; According to the completion time and the benchmark time corresponding to the current points of the current operator, determine the points change value; Wherein, when the completion time is less than or equal to the benchmark time corresponding to the current points of the current operator, the points change value is a positive number; When the completion time is greater than the benchmark time corresponding to the current points of the current operator, the points change value is a negative number.

4. The human-computer interaction method according to claim 3, wherein, The method further includes: pre-storing the second correspondence relationship between the level of the operator and the points of the operator, where the higher the level, the higher the corresponding points of the operator; The determining the points change value according to the completion time and the benchmark time corresponding to the current points of the current operator includes: Judge whether the completion time is less than or equal to the benchmark time corresponding to the current points of the current operator. If so, determine that the points change value is the first preset value, and the first preset value is a positive number; If not, execute: Determine the reference benchmark time corresponding to the completion time, and the reference benchmark time is the smallest one among the benchmark times larger than the completion time in the first correspondence relationship; According to the first correspondence relationship, determine the operator points corresponding to the reference benchmark time; According to the second correspondence relationship, determine the actual level corresponding to the operator points corresponding to the reference benchmark time; Determine the current level corresponding to the current points of the current operator according to the second corresponding relationship; Determine the level gap between the current level and the actual level; Determine the points change value according to the level gap, and this points change value is negative. The greater the level gap, the smaller the points change value.

5. The human-computer interaction method according to claim 1, wherein The determining the bonus change value obtained by the current operator for completing the target task according to the completion time, the current points of the current operator, and the first corresponding relationship includes: Determine the reference time and corresponding bonus corresponding to the current points of the current operator according to the first corresponding relationship; Judge whether the completion time is less than or equal to the reference time corresponding to the current points of the current operator. If so, determine that the bonus change value is the bonus corresponding to the current points of the current operator. Otherwise, determine that the bonus change value is zero or negative.

6. The human-computer interaction method according to claim 1, wherein The personal information includes the current points and current bonus of the operator; The determining the incentive information of the current operator according to the points change value and the bonus change value includes: Update the current points and current bonus of the current operator according to the points change value and the bonus change value. The incentive information includes the current points and current bonus of the current operator.

7. The human-computer interaction method according to claim 6, wherein After updating the current points and current bonus of the current operator according to the points change value and the bonus change value, it further includes: Send the current points of the current operator to the server, so that the server ranks the current points of each operator in descending order, and displays the ranking result and the corresponding second bonus on the public display screen. The more the current points, the higher the corresponding ranking, and the more the corresponding second bonus.

8. The human-computer interaction method according to claim 1, wherein A plurality of the target tasks form a target total task, and the human-computer interaction method further includes: After the target total task is completed and the task result is obtained, review the task result; If there is an error in the task result, determine the operator who made the mistake causing the error; Determine the points deduction value and bonus deduction value for the operator who made the mistake; Update the current points and current bonus of the operator who made the mistake according to the points deduction value and bonus deduction value of the operator who made the mistake.

9. A robot, characterized in that, The robot includes one or more processors and a memory. When the computer program stored in the memory is executed by the processor, the steps of the human-computer interaction method according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, the steps of the human-computer interaction method according to any one of claims 1 to 8 are implemented.

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