Co-evolution evaluation system
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Filing Date
- 2025-02-21
- Publication Date
- 2026-08-13
Smart Images
Figure JP2025006027_13082026_PF_FP_ABST
Abstract
Description
Co - evolution Evaluation System
[0001] The present invention relates to a co - evolution evaluation system for evaluating the work efficiency and safety that evolve through the interaction between a human and a robot in a task performed by their cooperation.
[0002] There is known an evaluation system that can determine an operation suitable for a task by evaluating the work efficiency and safety of a task through the cooperation between an operator and a work device. As this evaluation system, the operations of an operator and a work device in an area where the task is performed are simulated by a computer, and the work efficiency and safety are evaluated based on this simulation.
[0003] As such an evaluation system, for example, in Patent Document 1, an airport control support system has been proposed. This system can formulate the travel routes of aircraft and vehicles running at an airport and can formulate an optimal route for efficiently operating the aircraft and the vehicle.
[0004] Japanese Patent Application Laid - Open No. 2002 - 197600
[0005] In the above - mentioned conventional evaluation system, by inputting preset conditions (such as environmental information, operator's ability information, and work device performance information, etc.), an evaluation corresponding to these conditions is performed. That is, the evaluation was performed based on fixed operation conditions. Thus, the conventional evaluation system only performed an evaluation at the time (current situation) when it matched the input conditions. And when using this evaluation to operate a task, the work flow (such as a business plan) was formulated according to the evaluation results of the conventional evaluation system.
[0006] Incidentally, in work where workers and work equipment work together, the work equipment operates under pre-set conditions, while the worker's abilities evolve through experience. For this reason, it is desirable that the aforementioned business plans and the like be formulated taking into account the worker's evolution. However, the conventional evaluation system mentioned above only provides an evaluation at a single point in time (the current situation), and therefore, this evaluation alone makes it difficult to formulate a future plan (vision) for the work. Furthermore, if work is carried out solely based on evaluations from the conventional evaluation system, the worker's evolution cannot be utilized in the work, resulting in a problem of poor work efficiency (e.g., productivity). In particular, even if a person's individual abilities improve, they may adjust their work to match the work equipment they are working with, and in this case, the aforementioned evolution is not easily utilized in the work.
[0007] Furthermore, while the system described in Patent Document 1 above performs evaluations appropriate to congestion levels and weather conditions, it can only formulate the optimal route for each environment (current situation) and does not perform evaluations that take into account the improvement (evolution) of skills that arise as operators of aircraft and vehicles gain experience.
[0008] This invention proposes a co-evolutionary evaluation system that can evaluate work performed collaboratively by a worker and a work machine, including the evolution of the worker.
[0009] The present invention is a co-evolution evaluation system comprising: an information input processing means for inputting environmental information of a work area in which a worker and work equipment perform a predetermined job, basic ability information of the worker, and basic performance information of the work equipment; a simulation processing means for deriving a simulation of the work performed by the worker and the work equipment based on the environmental information, basic ability information, and basic performance information input by the information input processing means; and a work evaluation processing means for quantitatively evaluating the work efficiency and safety of the job based on the simulation derived by the simulation processing means, wherein the information input processing means includes processing content for inputting evolutionary ability information of the worker, which is changed from the basic ability information, and evolutionary performance information of the work equipment, which is changed from the basic performance information; the simulation processing means includes processing content for deriving an evolutionary motion simulation of the job based on the environmental information, the evolutionary ability information, and the evolutionary performance information; and the work evaluation processing means includes processing content for quantitatively evaluating the work efficiency and safety of the job based on the evolutionary motion simulation.
[0010] In this configuration, an evaluation including the evolution of both the worker and the work equipment (hereinafter referred to as "co-evolution evaluation") can be performed based on evolutionary capability information and evolutionary performance information. Therefore, in addition to the evaluation based on basic capability information and basic performance information, the evolved future co-evolution evaluation can be obtained. Furthermore, in this configuration, since work efficiency and safety are evaluated based on work motion simulation and evolutionary motion simulation, an evaluation that appropriately balances these (including the co-evolution evaluation) can be obtained. Accordingly, according to the configuration of the present invention, it is possible to manage future changes in the entire work due to the co-evolution of the worker and the work equipment, and to accurately formulate a business plan that makes use of this co-evolution.
[0011] In the co-evolution evaluation system of the present invention described above, a configuration is proposed in which the safety indicator in the work evaluation processing means includes at least the number of collisions in which a worker collides with other workers and / or work equipment in the motion simulation and the evolutionary motion simulation, and the number of predicted collisions in which a worker has a possibility of colliding with other workers and / or work equipment in the motion simulation and the evolutionary motion simulation. Here, the predicted collision count indicates the number of times a collision is possible. For example, the number of times the movement path of a moving worker heading to their destination intersects with the movement path of another moving worker can be set as the predicted collision count.
[0012] In this configuration, since the safety indicator includes not only the number of collisions but also the number of predicted collisions, the true value of the safety evaluation results can be enhanced. This co-evolutionary evaluation, which includes safety, can make unknown risks that may arise in the future materialize, and business plans and other measures that take high safety into consideration can be formulated.
[0013] In the co-evolution evaluation system of the present invention described above, the work evaluation processing means includes a process in which, in the motion simulation and the evolutionary motion simulation, if the time difference in the times when at least one worker and other workers and / or work equipment reach the same or nearby position is below a predetermined threshold, the time difference is defined as the collision risk time, and the safety indicator in the work evaluation processing means includes a collision risk state time which is the sum of the collision risk times generated in the motion simulation and the evolutionary motion simulation.
[0014] In this configuration, the collision risk state time, based on the time difference in reaching the same or nearby position, is included as an indicator of safety, and the possibility of collision on the time axis is indicated by this collision risk state time. This co-evolution evaluation, which includes this collision risk state time, can make unknown risks even more apparent, and business plans and the like can be formulated with a high level of safety in mind.
[0015] The co-evolution evaluation system of the present invention can perform evaluations that include the co-evolution between workers and work equipment, thereby enabling the management of future changes in work and the accurate formulation of business plans that utilize this co-evolution.
[0016] This is a block diagram of the co-evolution evaluation system 1 of this embodiment. This is a flowchart showing the co-evolution evaluation process by the co-evolution evaluation system 1. This is an explanatory diagram showing the logistics area 31 where the work to be evaluated is performed, and an explanatory diagram showing input information and output information. This is an explanatory diagram showing (A) a list display mode of the evaluation results and (B) a detailed display mode of each evaluation result. This is an explanatory diagram showing the number of collision predictions. This is a flowchart showing the evolution information update process. This is an explanatory diagram showing the list display mode of the evaluation results by co-evolution evaluation.
[0017] Embodiments of the present invention will be described with reference to the attached drawings. The co-evolution evaluation system 1 of this embodiment is for evaluating the work efficiency and safety of work performed collaboratively by a worker and a robot, and includes a management server (not shown) managed by an administrator. This management server has general server functions and is composed of one or more computers equipped with a central control unit (CPU), storage devices (RAM, ROM), and communication devices, etc.
[0018] In this embodiment, a data input / output terminal (not shown) is connected to the management server via a network, and input data transmitted from the terminal is input to the management server, while output data output from the management server is received by the terminal. This terminal may be a personal computer, tablet, or smartphone with communication capabilities, and is managed by an ID and password.
[0019] In this embodiment, the work to be evaluated by the co-evolution evaluation system 1 is exemplified by the loading and unloading of goods in a logistics warehouse. As shown in Figure 3, this loading and unloading work is performed collaboratively by multiple workers 61a to 61e and multiple robots 62a to 62e in a logistics area 31 that constitutes a logistics warehouse. The logistics area 31 is equipped with multiple loading and unloading areas 32 for loading and unloading goods and multiple shelves 33 in which goods are stored, and the space between the loading and unloading areas 32 and the shelves 33 is a passageway for the workers 61a to 61e and the robots 62a to 62e. Each shelf 33 is provided with multiple storage spaces (not shown) for storing each item. The management server described above has the function of managing the number of each item stored in the logistics area 31 and the loading and unloading of each item, as well as the function of managing the loading and unloading work performed by the workers 61a to 61e and the robots 62a to 62e. In other words, the management server, in addition to being the co-evolution evaluation system 1 of this embodiment, also has the function of managing the inbound and outbound of goods and managing the inbound and outbound operations.
[0020] In this logistics area 31, workers 61a to 61e perform the tasks of loading and unloading goods into containers in the storage space of shelves 33 and the loading / unloading area 32, and moving the containers. On the other hand, the robots 62a to 62e in this embodiment are equipped with the function of loading and unloading goods in the storage space of shelves 33 and the loading / unloading area 32, and the function of moving the containers.
[0021] As shown in Figure 1, the co-evolution evaluation system 1 comprises an information input processing means 2, a simulation processing means 3, a work evaluation processing means 4, a data storage means 5, and an evaluation output means 6. The information input processing means 2 processes input data received from the terminal and input data entered by the administrator on the management server, and includes environmental information input processing, basic information input processing, evolution condition input processing, and evolution information input processing. The simulation processing means 3 performs calculation processing based on the input data entered by the information input processing means 2, and includes data integration processing, analysis processing, and simulation processing. The work evaluation processing means 4 evaluates work efficiency and safety based on the simulation results derived by the simulation processing means 3, and includes work evaluation processing and optimization estimation processing. The data storage means 5 stores the input data entered by the information input processing means 2 and the simulation results derived by the simulation processing means 3, and the evaluation output means 6 outputs the evaluation results obtained by the work evaluation processing means 4.
[0022] The co-evolution evaluation system 1 performs a co-evolution evaluation process to evaluate work in the logistics area 31. In the co-evolution evaluation process, as shown in Figure 2, the information input processing means 2 performs an information input process (S10). In this information input process, the environmental information input process, basic information input process, evolution condition input process, and evolution information input process are performed, and as shown in Figure 4, environmental information, worker information, and robot information are input.
[0023] The aforementioned environmental information includes layout information, obstacle information, and area weather information. Here, the layout information includes location information of the loading / unloading area 32 and shelves 33 in the logistics area 31, and location information of the storage space of each shelf 33. The obstacle information includes location information of obstacles placed in the logistics area 31. The area weather information includes brightness, temperature, and humidity of the logistics area 31. The process of inputting this environmental information is the environmental information input process.
[0024] The worker information includes location information, cost information, movement speed information, work capacity information, task information, evolution conditions, evolution candidate information, and evolution upper limit information. This worker information is set for each worker 61a to 61e engaged in the work in the logistics area 31. Here, location information is information indicating the position of workers 61a to 61e in the logistics area 31, and for example, location information indicated by X-Y coordinates that define the plane of the logistics area 31 can be applied. Cost information is the cost required for workers 61a to 61e to perform the work, for example, the cost per unit time. Movement speed information indicates the speed at which workers 61a to 61e move the container in the aisles of the logistics area 31. Work capacity information indicates the time required for workers 61a to 61e to load and unload goods at the loading / unloading area 32 and shelves 33. Task information indicates the content of the work performed by workers 61a to 61e, for example, information that sets the order of movement and the amount of loading and unloading work in chronological order. The evolution conditions indicate the conditions under which the capabilities of workers 61a to 61e change, for example, the number of times or the duration of work performed by workers 61a to 61e in the logistics area 31. The evolution candidate information indicates the magnitude (percentage) of change in the capabilities of workers 61a to 61e (the cost information, the movement speed information, and the work capability information), and the percentage at which the information is updated to that magnitude. The evolution upper limit information indicates the limit to which the capabilities of workers 61a to 61e can change.
[0025] The robot information includes location information, cost information, movement speed information, work performance information, task information, evolution conditions, evolution candidate information, and performance upper limit information. This robot information is set for each robot 62a to 62e that performs the aforementioned work in the logistics area 31. Here, location information indicates the position of robots 62a to 62e in the logistics area 31, and location information expressed in X-Y coordinates can be applied, similar to the worker information. Cost information is the cost required to operate robots 62a to 62e, for example, the cost per unit time. Movement speed information indicates the speed at which robots 62a to 62e move in the aisles of the logistics area 31. Work performance information indicates the time required for robots 62a to 62e to load and unload goods at the loading / unloading area 32 and shelves 33. Task information indicates the operation details of robots 62a to 62e, for example, information such as the order of movement and the amount of loading and unloading set in chronological order. The evolution conditions indicate the conditions for changing the performance of robots 62a to 62e, and can be set, for example, to a change in the capabilities of workers 61a to 61e by a predetermined amount. The evolution candidate information indicates the range of change in the performance of robots 62a to 62e (the cost information, the movement speed information, and the work performance information). The evolution upper limit information indicates the limit to which the performance of robots 62a to 62e can be changed.
[0026] The process of inputting cost information, movement speed information, work capacity information, work performance information, and task information from this worker information and robot information is the basic information input process. The process of inputting evolution conditions is the evolution condition input process, and the process of inputting evolution candidate information, evolution upper limit information, and performance upper limit information is the evolution information input process.
[0027] As shown in Figure 2, data integration processing (S20) is executed after the information input processing (S10). The data integration processing links the information input in the information input processing to each worker 61a to 61e and each robot 62a to 62e. In addition, when using data input from cameras, sensors, etc., placed in the logistics area 31, the processing also includes converting this data into a data format that is unified with the information input in the information input processing.
[0028] Following the data integration process, an analysis process (S30) is performed. The analysis process defines the range in which workers 61a to 61e and robots 62a to 62e can move, based on the layout information, the obstacle information, the task information of the worker information, and the task information of the robot information.
[0029] Following the analysis process, a simulation process (S40) is executed. The simulation process derives an action simulation in which workers 61a to 61e and robots 62a to 62e perform their respective tasks in the virtual space defined in the analysis process, and the information input in the information input process is used to derive the action simulation. In this embodiment, by executing the simulation process for multiple combinations in which the number of workers 61a to 61e and the number of robots 62a to 62e differ, an action simulation for each combination can be derived.
[0030] Following the simulation process, an evaluation process (S50) is performed. The evaluation process obtains information indicating safety and information indicating work efficiency by performing predetermined calculations based on the motion simulation derived in the simulation process. Furthermore, optimization estimation information is calculated from this safety information and work efficiency information. Here, if the simulation process has derived multiple motion simulations corresponding to various combinations of the number of workers and the number of robots, the calculations are performed for each motion simulation to obtain the safety information, the work efficiency information, and the optimization estimation information, respectively. The process of obtaining this safety information and work efficiency information is the work evaluation process, and the process of obtaining the optimization estimation information is the optimization estimation process.
[0031] The safety information obtained in the evaluation process, as shown in Figure 4, includes the number of robot collisions, the number of predicted robot collisions, the number of worker collisions, the number of predicted worker collisions, and the collision risk state time. Here, the number of robot collisions represents the total number of times each robot 62a to 62e collides with other robots 62a to 62e and the number of times it collides with workers 61a to 61e in the motion simulation. The number of predicted robot collisions represents the total number of times each robot 62a to 62e has the potential to collide with other robots 62a to 62e and the number of times it has the potential to collide with workers 61a to 61e in the motion simulation. The number of worker collisions represents the total number of times each worker 61a to 61e collides with other workers 61a to 61e and the number of times it collides with robots 62a to 62e in the motion simulation. The predicted number of worker collisions represents the total number of times each worker 61a to 61e has a possibility of colliding with other workers 61a to 61e in the motion simulation, plus the total number of times they have a possibility of colliding with robots 62a to 62e. The collision risk state time is the total collision risk time during which the time difference between workers 61a to 61e and robots 62a to 62e reaching the same position is less than or equal to a predetermined threshold. The predicted number of robot collisions, the predicted number of worker collisions, and the collision risk state time will be described in detail later.
[0032] The aforementioned work efficiency information includes the average travel time ratio for workers, the average work time ratio for workers, the average waiting time ratio for workers, the average travel time ratio for robots, the average work time ratio for robots, the average waiting time ratio for robots, the total time required for all tasks, and the total cost of all tasks. Here, the average travel time ratio for workers, the average work time ratio for workers, and the average waiting time ratio for workers are the average values obtained by averaging the travel time (time required for travel), work time (time required for loading and unloading), and waiting time ratios for each worker 61a to 61e in the aforementioned motion simulation. Similarly, the average travel time ratio for robots, the average work time ratio for robots, and the average waiting time ratio for robots are the average values obtained by averaging the travel time, work time, and waiting time ratios for each robot 62a to 62e in the aforementioned motion simulation. The total time required for all tasks is the time required for all workers 61a to 61e and all robots 62a to 62e to complete all tasks. The total cost of all tasks is the cost required to execute all of the aforementioned tasks.
[0033] The aforementioned optimization estimation information is the sum of normalized values of the number of robot collisions and worker collisions, the number of predicted robot collisions and worker collisions, the average travel time ratio of the worker and robot, the average work time ratio of the worker and robot, the average waiting time ratio of the worker and robot, the total time taken for all tasks, and the total cost taken for all tasks. A smaller value in this optimization estimation information indicates a better balance between safety and work efficiency.
[0034] As shown in Figure 2, after the evaluation process (S50) is completed, a decision is made (S60) as to whether or not to perform the co-evolution process. This decision may be made by the administrator of the co-evolution evaluation system 1, or it may be made automatically according to pre-set conditions. If the decision is made not to perform the co-evolution process, the process proceeds to the display process (S70); if the co-evolution process is to be performed, the process proceeds to the evolution information update process (S80).
[0035] In the display process (S60), the safety information, work efficiency information, and optimization estimation information are output, and the information is made available for display on a monitor or terminal connected to the management server. This allows the information to be viewed on the monitor or terminal. On the display screen of the monitor or terminal, as shown in Figure 5(A), a list of the optimization estimation information corresponding to the combination of the number of workers and the number of robots is displayed, and this list is displayed in order of ranking according to the numerical value of the optimization estimation information. By using the numerical value of this optimization estimation information, it is possible to confirm the combination of the number of workers and the number of robots that provides a good balance between safety and work efficiency. Furthermore, by clicking on each list (rank), detailed information of the clicked list is displayed, as shown in Figure 5(B).
[0036] On the other hand, the evolution information update process (S80) shown in Figure 2 performs a process to update the operator information and the robot information using the evolution conditions, evolution candidate information, and evolution upper limit information input in the information input process (S10) described above.
[0037] Here, the worker evolution conditions are set to be conditions under which the capabilities of workers 61a to 61e change, as described above. The worker evolution candidate information includes multiple speed candidate information and multiple capability candidate information, as well as the selection ratio of the speed candidate information and the selection ratio of the capability candidate information. Here, the speed candidate information is information for updating the movement speed information of the worker information, and the capability candidate information is information for updating the work capability information of the worker information. The worker evolution upper limit information includes the upper limit number of times the worker's movement speed information and work capability information can be evolved, and the respective upper limits of the movement speed information and work capability information. On the other hand, the robot evolution conditions are set to improve the worker's capabilities. In other words, worker evolution is essential for robot evolution. Robot evolution candidate information includes multiple speed candidate information and multiple performance candidate information. Here, the speed candidate information is information for updating the movement speed information of the robot information, and the performance candidate information is information for updating the work performance information of the robot information. The robot's evolution limit information includes the maximum number of times the robot's movement speed information and work performance information can be evolved, and the respective upper limits of the movement speed information and work performance information.
[0038] Furthermore, the aforementioned candidate worker speed information may include not only information that improves the worker's movement speed information, but also information that reduces said movement speed information. Similarly, the candidate ability information may include not only information that improves the worker's work ability information, but also information that reduces said work ability information. Likewise, the aforementioned candidate robot speed information and candidate robot performance information may include not only information that improves the robot's movement speed information and work performance information, respectively, but also information that reduces them, respectively. In other words, evolution (co-evolution) in this embodiment also includes so-called degeneration.
[0039] In the evolution information update process (S80), as shown in Figure 7, the evolution condition update process (S110) is executed. In the evolution condition update process, the number of times (cumulative number) that workers 61a to 61e are evolved is updated. In the next S120, it is determined whether the currently set movement speed information of workers 61a to 61e is at the upper limit. If the result is positive (Yes), the process proceeds to the display process (S60); if the result is negative (No), the process proceeds to S130. In S130, it is determined whether the currently set work capacity information of workers 61a to 61e is at the upper limit. If the result is positive (Yes), the process proceeds to the display process (S60); if the result is negative (No), the process proceeds to S140. In S140, it is determined whether the number of evolutions (cumulative number) for workers 61a to 61e has reached the upper limit. If the result is positive (Yes), the process proceeds to the display process (S60); if the result is negative (No), the process proceeds to the information update process (S150).
[0040] In the information update process (S150), a random number is obtained, and the obtained random number is compared with the selection ratio of the capability candidate information to select speed candidate information and capability candidate information. Then, the worker's movement speed information is updated according to the selected speed candidate information, and the worker's work capability information is updated according to the selected capability candidate information. This process is performed for each worker 61a to 61e, thereby evolving the movement speed information and work capability information of each worker 61a to 61e.
[0041] Furthermore, the information update process (S150) updates the movement speed information and work performance information of the robots 62a to 62e. This process is executed only when the movement speed information and work performance information of the robots have not reached the upper limit and the number of evolution iterations has not reached the upper limit. In this process, candidate robot speed information is selected according to the updated worker movement speed information, and candidate robot performance information is selected according to the updated worker work ability information. Then, the movement speed information of the robots is updated according to the selected candidate speed information, and the work performance information of the robots is updated according to the selected candidate performance information. This process is performed for each of the robots 62a to 62e, and the movement speed information and work performance information of each robot 62a to 62e are evolved.
[0042] Upon completion of the information update process, the process proceeds to the simulation process (S40). In this simulation process, the worker's movement speed information and work ability information updated in the information update process, and the robot's movement speed information and work performance information updated in the same information update process, are used to derive a motion simulation of the worker and robot's evolution (hereinafter referred to as the evolutionary motion simulation). This simulation process is executed in the same manner as the process for deriving the motion simulation using the movement speed information, etc., before evolution.
[0043] After this simulation process, the evaluation process (S50) is executed. In this evaluation process, safety information, work efficiency information, and optimization estimation information are obtained based on the evolutionary motion simulation. The process of obtaining this information is performed in the same way as the process using the motion simulation before evolution. The safety information, work efficiency information, and optimization estimation information obtained based on the evolutionary motion simulation correspond to the co-evolution evaluation.
[0044] Then, when the evaluation process ends, S60 is executed to determine whether to execute the co-evolution process as described above. In the case of an affirmative determination (Yes), the evolution information update process (S80) is executed, while in the case of a negative determination (No), the display process (S70) is executed. Here, when the evolution information update process is executed, as described above, a process of evolving the operator's movement speed information and work ability information, and the robot's movement speed information and work performance information is executed, and the simulation process and the evaluation process are executed using the information updated according to this evolution.
[0045] The display process (S70) performs a process of outputting the evaluation results (safety information, work efficiency information, and optimization estimation information) obtained in the evaluation process before the co-evolution process and the results of the co-evolution evaluation (safety information, work efficiency information, and optimization estimation information) obtained in the co-evolution process when the co-evolution process (a series of processes from the evolution information update process through the simulation process to the evaluation process) is being executed. As a result, on the display screen of the monitor or the terminal, the evaluation results before the co-evolution process and the results of the co-evolution evaluation can be selectively displayed. The results of the co-evolution evaluation are displayed in the same display mode as before the co-evolution process (see FIG. 5). For example, as shown in FIG. 8, a list of the optimization estimation information corresponding to the number of operators and the number of robots is displayed. Since this list is the information obtained in the co-evolution process, compared with the information before co-evolution (see FIG. 5(A)), excellent optimization estimation information is displayed. By clicking on each list, detailed information is displayed (see FIG. 5(B)).
[0046] Next, the worker collision prediction count and robot collision prediction count mentioned above will be explained. In this embodiment, the worker collision prediction count indicates the number of times in the motion simulation when the movement path of workers 61a to 61e that have started moving intersects with the movement paths of other workers 61a to 61e that are moving and robots 62a to 62e that are moving. Similarly, the robot collision prediction count indicates the number of times in the motion simulation when the movement path of robots 62a to 62e that have started moving intersects with the movement paths of other robots 62a to 62e that are moving and workers 61a to 61e that are moving. For example, as shown in Figure 6(A), in the motion simulation, when a stationary robot 62a starts moving, if the movement path of robot 62a (the path to the next destination) intersects with the movement path of worker 61a that is already moving, the robot collision prediction count is counted. Here, the number of predicted collisions is counted by counting the intersection of movement paths, so even if the robot 62a and the worker 61a do not collide in the motion simulation (see Figure 6(B)), the number of predicted robot collisions is counted. Also, as shown in Figure 6(B), if robot 62c starts moving while robot 62a is moving, and the movement path of robot 62c (the path to the next destination) intersects with the movement path of robot 62a, the number of predicted robot collisions is counted. Note that even if another robot 62b starts moving, if its movement path does not come into contact with other movement paths, the number of predicted robot collisions is not counted. The number of predicted robot collisions counted in this way is accumulated in the motion simulation. Similarly, the number of predicted robot collisions is also obtained for the evolutionary motion simulation derived through the co-evolution process described above, and the number of predicted robot collisions is obtained for both the motion simulation and each evolutionary motion simulation. The number of predicted worker collisions is also obtained in the same way as the number of predicted robot collisions described above.
[0047] Next, the collision risk state time described above will be explained. The collision risk state time in this embodiment is calculated in the evaluation process (S50) as described above. In this evaluation process, on the operation simulation, the positions where the workers 61a to 61e and the robots 62a to 62e reach are predicted based on their respective movement speed information. When the time difference between the times when they reach the same position is less than or equal to a predetermined threshold, this time difference is taken as the collision risk time. Then, by summing up all the collision risk times predicted in the operation simulation, the collision risk state time is calculated. For example, if the time difference between the times when the worker 61a and the robot 62a reach the same position in the operation simulation is less than or equal to the threshold, this time difference is taken as the collision risk time. On the other hand, if it is greater than the threshold, this time difference is not taken as the collision risk time. Here, the threshold can be set to, for example, 2 seconds or 4 seconds. Incidentally, such collision risk times and collision risk state times are similarly calculated for the evolutionary operation simulation derived through the above-described co-evolution process, and are calculated separately for the operation simulation and each evolutionary operation simulation.
[0048] Thus, in this embodiment, the safety information obtained in the evaluation process includes the number of collisions indicated by the operation simulation and the evolutionary operation simulation, the predicted number of collisions obtained from the movement paths of the workers and robots that have started moving, and the collision risk state time obtained from the movement speeds of the workers and robots. Thereby, safety can be evaluated from a plurality of different viewpoints.
[0049] In the co-evolution evaluation system 1 of this embodiment, the work efficiency and safety of the work in the logistics area 31 can be evaluated, and the optimization estimation information obtained from these evaluations can provide an evaluation result that appropriately balances work efficiency and safety. Furthermore, this evaluation includes not only the evaluation at the time the motion simulation was derived, but also a co-evolution evaluation using the evolutionary motion simulation in which the worker and robot co-evolve. In particular, in this embodiment, the optimization estimation information provides the requirements (the required number of workers and robots to engage in the work) that best balance work efficiency and safety. Furthermore, since this optimization estimation information is obtained from both the motion simulation and the evolutionary motion simulation, future changes due to co-evolution can be clearly predicted. Thus, with the configuration of this embodiment, it is possible to know the current evaluation and the co-evolution evaluation, making it easier to manage future changes in the work and enabling the accurate formulation of business plans that utilize the co-evolution of workers and robots.
[0050] Furthermore, in this embodiment, safety, work efficiency, and optimization estimation information are each quantitatively evaluated, and these evaluation results (quantitative values) are displayed, making the evaluation results clear and easy to understand. These evaluation results can also be easily used in formulating the business plan.
[0051] Furthermore, in the configuration of this embodiment, safety is evaluated based on the number of collisions between the worker and the robot, the number of predicted collisions between the worker and the robot, and the duration of the collision risk state, thereby enhancing the true value of the evaluation results. By evaluating this safety using the evolutionary motion simulation in which the worker and the robot co-evolve, unknown risks that may arise in the future can be made apparent, and business plans that take high safety into consideration throughout the entire work can be formulated.
[0052] Furthermore, in the configuration of this embodiment, since the evaluation of work efficiency is performed using the average travel time ratio of the worker and robot, the average work time ratio of the worker and robot, the average waiting time ratio of the worker and robot, the total time required for all tasks, and the cost required for all tasks, the evaluation using the evolutionary motion simulation makes it easier to predict the future prospects of the work and to formulate business plans.
[0053] In this embodiment, the logistics area 31 corresponds to the work area according to the present invention. Robots 62a to 62e correspond to the work equipment according to the present invention. Worker location information, cost information, movement speed information, and work capacity information correspond to the basic capacity information according to the present invention, and robot location information, cost information, movement speed information, and work performance information correspond to the basic performance information according to the present invention. Worker evolution candidate information and evolution upper limit information correspond to worker evolution capacity information according to the present invention, and robot evolution candidate information and performance upper limit information correspond to work equipment evolution performance information according to the present invention.
[0054] The present invention is not limited to the embodiments described above, and can be modified as appropriate without departing from the spirit of the invention. For example, the number of workers and robots evaluated by the co-evolution evaluation system 1 can be changed as appropriate.
[0055] In the embodiment, the collision risk time is treated as the time difference between the time when the worker and the robot reach the same position. However, the embodiment is not limited to this, and the collision risk time may be defined as the time difference between the time when the worker and the robot reach close positions, provided that this time difference is less than or equal to the threshold. In this case as well, the same effects and advantages as in the embodiment described above can be achieved.
[0056] In this embodiment, the co-evolution process may include selecting a reduction in worker capabilities and a reduction in robot performance. However, it is not limited to this, and it is also possible to select only an improvement in worker capabilities and an improvement in robot performance.
[0057] In this embodiment, the co-evolution evaluation process is configured to execute a simulation process via data integration and analysis processes after the information input process. However, the process is not limited to this configuration. Before the simulation process, a result estimation process may be performed to estimate the evaluation results of work efficiency and safety based on existing data (information) stored in the data storage means. This result estimation process estimates the evaluation results based on previously evaluated results and newly input information in the information input process. By displaying these estimated evaluation results before the execution of the simulation process, the administrator can choose whether or not to proceed with the simulation process.
[0058] In this embodiment, the co-evolution evaluation process derives motion simulations and evolutionary motion simulations using information input by the information input processing means. However, the process is not limited to this, and data obtained from cameras, sensors, etc., installed in the logistics area (work area) can also be used to derive motion simulations, etc. For example, the worker's movement speed may be calculated from the worker's behavior detected by cameras, sensors, etc., and motion simulations may be derived or candidate evolutionary information for the worker may be determined based on the improvement in the movement speed.
[0059] In the embodiments, work in a logistics area was used as an example of the evaluation target, but the system is not limited to this, and other types of work can be evaluated. For example, work in a business area equipped with multiple manufacturing facilities and receiving / shipping facilities can be evaluated using the co-evolutionary evaluation system of the present invention. In this case, it is preferable to perform an operation simulation (co-evolutionary simulation) that includes not only work vehicles and robots moving between the manufacturing facilities and receiving / shipping facilities in the business area, but also information such as the manufacturing capacity and storage capacity of the manufacturing facilities, and information such as the receiving / shipping capacity and storage capacity of the receiving / shipping facilities. This can achieve the same effects as in the embodiments described above. Furthermore, it is also possible to evaluate work involving transporting goods by truck or the like to multiple delivery locations using the co-evolutionary evaluation system of the present invention.
[0060] 1. Co-evolutionary evaluation system 2. Information input processing means 3. Simulation processing means 4. Work evaluation processing means 31. Logistics area (work area) 61a-61e. Workers 62a-62e. Robots (work equipment)
Claims
1. A co-evolution evaluation system comprising: an information input processing means for inputting environmental information of a work area in which a worker and work equipment perform a predetermined job, basic ability information of the worker, and basic performance information of the work equipment; a simulation processing means for deriving a simulation of the work performed by the worker and the work equipment based on the environmental information, basic ability information, and basic performance information input by the information input processing means; and a work evaluation processing means for quantitatively evaluating the work efficiency and safety of the job based on the simulation derived by the simulation processing means, wherein the information input processing means includes processing content for inputting evolutionary ability information of the worker, which is changed from the basic ability information, and evolutionary performance information of the work equipment, which is changed from the basic performance information; the simulation processing means includes processing content for deriving an evolutionary motion simulation of the job based on the environmental information, the evolutionary ability information, and the evolutionary performance information; and the work evaluation processing means includes processing content for quantitatively evaluating the work efficiency and safety of the job based on the evolutionary motion simulation.
2. The co-evolutionary evaluation system according to claim 1, characterized in that the safety indicators in the work evaluation processing means include at least the number of collisions in which a worker collides with other workers and / or work equipment in the motion simulation and the evolutionary motion simulation, and the number of predicted collisions in which a worker has the potential to collide with other workers and / or work equipment in the motion simulation and the evolutionary motion simulation.
3. The co-evolution evaluation system according to claim 1 or 2, wherein the work evaluation processing means includes a process in which, in the motion simulation and the evolutionary motion simulation, if the time difference in the time when at least the worker and other workers and / or work equipment reach the same position or a nearby position is less than or equal to a predetermined threshold, the time difference is set to a collision risk time, and the safety indicator in the work evaluation processing means includes a collision risk state time which is the sum of the collision risk times generated in the motion simulation and the evolutionary motion simulation.