Method for navigation of a mobile body in an industrial environment, arrangement for implementing the method, and computer program

Abstract

The present invention relates to a method for navigating a mobile body 5 in an industrial environment having stations, wherein transportation tasks are assigned to the mobile body 5, wherein in a planning step 100, an industrial layout 1 corresponding to the industrial environment is formed having station nodes 3 for the stations and vacant spaces 4, wherein in a generation step 200, a node-edge network 2 having path point nodes 6 and having edges 7 between the station nodes 3 and the path point nodes 6 is automatically generated based on the industrial layout 1 and the transportation tasks, wherein in a use step 300, the mobile body 5 moves in the industrial environment corresponding to the edges 7 of the node-edge network 2.

Description

Technical Field

[0001] The present invention relates to a method for navigating a mobile body in an industrial environment, an arrangement for implementing the method, and a computer program. Background Technology

[0002] In industrial production systems, vehicles are frequently used, which are either self-driving or centrally controlled. In both cases, it is necessary to first learn the driving route used for navigation, a process typically performed by experts.

[0003] Publication DE 10 2016 216 206 A1 discloses a manufacturing apparatus comprising a travel path, at least one evaluation unit, and at least one robot vehicle. The travel path comprises a plurality of modular travel path elements, wherein at least two of the travel path elements form a travel path segment. The travel path has optical markers that include position information. The at least one robot vehicle is arranged on the travel path in a manner capable of active movement. The robot vehicle has an optical sensor unit for detecting at least one optical marker as position data. The at least one evaluation unit is configured to determine the position and / or orientation of the at least one robot vehicle on the travel path and / or within the manufacturing apparatus based on the position data. Summary of the Invention

[0004] The subject of this invention is a method for navigating a moving body having the features of claim 1, an arrangement for implementing the method having the features of claim 11, and a computer program having the features of claim 12. Preferred or advantageous embodiments of the invention are derived from the dependent claims, the following description, and the accompanying drawings.

[0005] The subject of this invention is a method for navigating mobile bodies in an industrial environment. A mobile body can be understood as a ground-based vehicle, such as a vehicle unconstrained by a driving trajectory, particularly a vehicle with wheels, rollers, etc. However, "mobile body" can also be understood as a flying or hovering mobile body, which can fly or hover, for example, by magnetic force, rotors (e.g., drones), etc. In particular, the mobile body is constructed as an unmanned transport system (FTS) or as an AGV (Automated Guided Vehicle). Specifically, the mobile body is constructed as an unmanned transport vehicle used in industry and logistics for automated material handling. The mobile body can be independently oriented and / or positioned in an industrial environment using magnetic strips, lasers, cameras, or GPS technology or other markers.

[0006] Navigation specifically involves planning and executing one or more routes of movement for a mobile body. Industrial environments are typically formed through production systems or production facilities, or alternatively, through logistics facilities. Industrial environments have stations, which can be formed through manufacturing units, storage units, parking positions, etc. These stations specifically form the starting point, ending point, or intermediate point in a movement route.

[0007] A transport task can be defined by defining a starting point, an ending point, and / or intermediate points. Optionally, a transport task may also include the type or kind of moving body. A transport task can be defined by moving a moving body, either without a load or with a load.

[0008] In the planning phase, the industrial environment is transformed into an industrial layout with station nodes and vacant spaces. Here, the industrial environment can be realized first, and the industrial layout derived from it, or the industrial layout can be formed first, and the industrial environment realized based on that layout. The industrial layout is constructed, for example, as a 2-D model or 2-D plan of the industrial environment. Station nodes for the stations are included in the industrial layout. Station nodes are constructed, particularly in a point-like manner. Furthermore, vacant spaces are included, which can be utilized by mobile vehicles for transportation tasks. Areas within the vacant spaces can, for example, be reserved for the station's site requirements.

[0009] In the generation step, based on the industrial layout and transportation task, a node-edge network with path nodes and edges between station nodes and path nodes is automatically, and particularly with computer assistance, generated. Initialization corresponds to the initial creation of the industrial layout. Iteration corresponds to the subsequent creation of an improved or matched industrial layout.

[0010] A node-edge network is a graphical representation consisting of nodes (points) and edges (lines connecting the nodes). In the case of navigation of a moving object, an edge corresponds to the movement path of the moving object. A node-edge network specifically defines all allowed movement lines or paths for a moving object.

[0011] In the usage step, the mobile body moves correspondingly in an industrial environment, particularly along the edges of a node-edge network, especially for the purpose of performing a transportation task. Specifically, the edges form virtual movement routes and / or paths for the mobile body. Alternatively or additionally, in the usage step, control commands for the movement path of the mobile body are generated based on the generated node-edge network.

[0012] Here, the present invention is based on the idea of ​​not manually performing the layout-specific generation of nodes and edges that form the driving route for vehicle navigation, as this requires expert knowledge and a lot of time, which in turn means high economic costs.

[0013] By leveraging the automatic generation of node-edge networks, this node-edge network can be created more simply, at a lower cost, and without the need for experts.

[0014] The automatic and adaptive generation of nodes and edges enables the rapid and flexible matching of moving body paths to variable (production) layouts. No expert knowledge is required, and the matching can be performed during runtime. This makes traveling to temporary stations and manufacturing small quantities of parts economically feasible from a transportation technology perspective.

[0015] Particularly preferred is the creation of node-edge networks in an optimized, especially IT-optimized, manner. Preferably, at least one optimization routine and / or at least one optimization algorithm are run on a digital data processing device to optimize the creation of the node-edge network. Particularly preferred is the optimization of the node-edge network in the generation step regarding the full utilization of vacant space. This ensures and advantageously utilizes vacant space in a manner that maximizes its use for the node-edge network, thereby avoiding or at least reducing collisions and / or congestion of moving objects.

[0016] Preferably, node-edge networks are generated with IT assistance and / or computer assistance. Geometric analysis, random distribution, optimization algorithms, or artificial intelligence methods, and possible combinations thereof, can be used. Node-edge network generation is a common problem in graph theory, with a wide variety of solutions. In the simplest case, path nodes can be distributed randomly, and then the path nodes can be varied according to random principles, with the quality of the resulting node-edge network evaluated by an evaluation function.

[0017] In one possible improvement, at least a portion, preferably all, of the edges are configured as unidirectional edges, on which the moving body travels only in a pre-defined direction. In other words, the node-edge network is at least partially or completely configured as a one-way network for the moving body. Therefore, collisions are avoided, at least in the case of unidirectional edges. Alternatively, the edges are at least partially bidirectional, and thus can be used more flexibly for the navigation of the moving body.

[0018] In a preferred embodiment of the invention, the node-edge network is delivered to the dominant control device of the mobile body. This dominant control device is configured to create individual motion paths based on the node-edge network and the corresponding transportation tasks, and to assign these motion paths to one of the mobile bodies. In this case, the mobile body is specifically configured as an AGV (Automated Guided Vehicle). Alternatively, the node-edge network is delivered to the mobile body, and the mobile body autonomously performs the planning and implementation of the motion paths. In this case, the mobile body is specifically configured as an AMR (Autonomous Mobile Robot).

[0019] Preferably, the matching steps for matching node-edge networks are performed during operation and during the journey. The matching steps can be performed regularly or event-triggered. An example of event-triggered matching is described below.

[0020] In manually established routes, the rapid matching of movement routes for mobile vehicles, or the dynamic response to high local traffic volumes and congestion, as well as numerous other dynamic events or matching, required in adaptable production environments, is either impossible or prohibitively expensive. Static networks of nodes and edges significantly limit the flexibility and efficient navigation of unmanned transport vehicles. On the one hand, their potential for use in adaptable (production) layouts is largely lost; on the other hand, temporary traffic conditions may not be taken into account. While vehicles capable of autonomously planning routes and navigating freely around obstacles do exist, these vehicles are expensive due to significantly more complex requirements, and the use of node and edge networks is not absolutely necessary for navigation.

[0021] Dynamic matching, and particularly optimization, of node-edge networks enables rapid and flexible changes to the movement paths of mobile vehicles based on variable conditions. This requires no expert knowledge, and matching can be performed during runtime. Node-edge networks can be optimized during runtime based on traffic data, route layout, and / or transportation tasks. For example, the load on the node-edge network, the potential waiting time of mobile vehicles, the duration of task implementation, and future transportation tasks can be used as inputs for optimization. Matching nodes and edges during runtime allows mobile vehicles to navigate according to defined virtual routes in highly variable (production) layouts. New stations can be added or removed during runtime, and obstacles can be dynamically considered and avoided.

[0022] In one possible design scenario, a transportation matching step is performed, where the node-edge network is matched during operation for the modified transportation task. For cases where the origin, intermediate points, and / or destination change during a transportation task, the node-edge network can be optimized accordingly to the modified transportation task.

[0023] Alternatively or supplementarily, a traffic matching step can be performed, in which traffic data about the moving body is matched against the node-edge network during operation. If, for example, it is found that a particular edge is used too frequently by the moving body, then parallel edges can be created, for example, through matching, and thus parallel motion paths can be created.

[0024] Alternatively or supplementarily, a layout matching step can be performed, in which the node-edge network is matched against the modified industrial layout during operation. This is particularly relevant when the location of stations is changed and / or when the size of vacant land is altered, as industrial layouts may change.

[0025] Alternatively or supplementarily, an obstacle matching step is performed, in which the node-edge network is matched based on obstacles during runtime. Obstacles may arise due to external factors, such as a disruptor being placed in an empty space. However, it is also possible that one of the moving objects becomes immobile and thus acts as an obstacle. Obstacles can be constructed, in particular, as permanent or temporary obstacles. In both cases, the node-edge network can be matched based on obstacles during runtime, causing changes in the edges or points impeded by the obstacles.

[0026] Another subject of the invention is formed by an arrangement for implementing the method as previously described. This arrangement has multiple stations and multiple moving bodies. Furthermore, the arrangement includes a control unit, which is implemented, for example, as a digital data processing device, wherein the control unit is configured to implement planning and generation steps.

[0027] Another subject of the invention is formed by a computer program configured to perform the methods as previously described when executed on the arrangement according to claim 11.

[0028] Alternatively or supplementarily, the present invention relates to software or a method that dynamically matches and optimizes a node-side network for navigation of unmanned transport vehicles as mobile bodies. This software / method includes a regulation loop for optimizing the node-side network, thereby enabling rapid and dynamic matching of the node-side network based on current traffic conditions and predicted, future traffic conditions. The optimization of the node-side network occurs during operation and is synchronized with the dominant control unit (as long as it is present) after changes. This method or software enables the operation of unmanned transport systems (with low-sensor technology) as mobile bodies with greater flexibility and efficiency, and contributes to the adaptability of production systems. Preferably, the node-side network for navigation of mobile bodies, particularly AGVs (Automated Guided Vehicles), is no longer considered a static concept (Konstrukt) but rather a dynamic network that is continuously optimized using existing data (typically collected by a flottenmanager). Here, the node-side network is considered as the output of the regulation loop, which is matched by the aforementioned regulation parameters. Therefore, it is possible to map the entire process from the initial generation of the node-edge network to continuous optimization during the runtime of the system.

[0029] The input to the software tool or method is a (production) layout consisting of stations, including travel trajectories, available vacant spaces, the system's transport tasks, and current traffic conditions. The software tool or method optimizes the node-edge network based on the input parameters. For this purpose, rule-based methods, optimization algorithms, or artificial intelligence methods can be used. The optimization of the node-edge network involves dynamically matching the system's redundancy to the required specifications and dynamically defining the direction of edges to enable efficient formation management. Furthermore, it is possible to optimize the location of nodes to connect stations more directly to each other. Node and edge optimization can be performed at defined time intervals or based on occurring events. Examples include the arrival of new transport tasks or the failure of individual vehicles. After optimization, the node-edge network is transmitted to the master control unit and / or the moving body, thus enabling it to react to matching. Attached Figure Description

[0030] Further features, advantages, and effects of the invention will become apparent from the following description of preferred embodiments of the invention and from the accompanying drawings. The drawings show: Figure 1 A schematic view of an industrial layout for an embodiment of the method is shown; Figure 2 The first stage of a method for navigation of a moving body, as an embodiment of the present invention, is shown. Figure 3 The second stage of a method for navigating a moving body, as an embodiment of the present invention, is shown. Figure 4 An optimized embodiment for the method is shown. Figure 1 A schematic view of the industrial layout; Figure 5 The arrangement used to implement this method is shown. Detailed Implementation

[0031] Figure 1 An industrial layout 1 is illustrated in schematic form as a 2-D plan view, corresponding to a real industrial environment (not shown). The industrial environment has stations, which can be constructed, for example, as manufacturing stations, warehousing stations, transportation stations, etc. These stations in the industrial environment are mapped as station nodes 3 in a node-edge network 2.

[0032] Furthermore, an inverted T-shaped idle space 4 is introduced into the industrial layout 1, which serves as a driving area for the mobile vehicle 5. The mobile vehicle 5 is specifically constructed as an FTS or AGV.

[0033] In addition, path nodes 6 are introduced into node-edge network 2, where path nodes 6 are connected to each other and to station nodes 3 via edges 7. Edges 7 are, in particular, straight lines. Optionally, buffer nodes 8 can be provided, which are also connected in node-edge network 2 via edges 7, and these buffer nodes can be used as temporary parking spots for the moving body 5. Thus, station node 3, path nodes 6, and buffer nodes 8 form the nodes in node-edge network 2.

[0034] During operation, the mobile body 5 travels along edge 7, which thus forms a virtual travel path for the mobile body 5. The mobile body 5 is moved to perform necessary transportation tasks in an industrial environment. These transportation tasks may specifically have a starting point (such as a storage station), intermediate points (such as parking spaces), and a destination (such as a station) for the mobile body 5.

[0035] This is mapped to a movement path or route, which is formed by the sequential connection of edges 7, such that edges 7 form path segments. In addition to station node 3, stations in a real industrial environment are considered through station sites 9, which represent restricted areas (Sperrfläche) in industrial layout 1.

[0036] Figure 2 A schematic flowchart illustrating a method for navigating mobile body 5 is shown. In this method, the locations of station 11, vacant space 12, and transport task 13, as well as additional relevant information for mobile body 5 in the industrial environment, are provided as input information 10.

[0037] The input information is sent to software tool 14, where in planning step 100, software tool 14 transforms the industrial environment into industrial layout 1, where station nodes 3 are recorded as stations and vacant spaces 4 are recorded as vacant spaces.

[0038] In generation step 200, a node-edge network 2 is generated based on the industrial layout 1 and the transportation task. This node-edge network has path point nodes 6 and edges 7, which connect the path point nodes 6 to each other and to station nodes 3. Buffer nodes 8 are also generated if necessary. Edges 7 can be partially or completely constructed as unidirectional or directed edges.

[0039] The output from software tool 14 is node-edge network 2, which is selectively delivered to mobile body 5 or the dominant control device of mobile body 5 for use in step 300. The mobile body 5 or the dominant control device of mobile body 5 then pre-determines the motion path of mobile body 5, wherein in use step 300, mobile body 5 travels in an industrial environment corresponding to edge 7 of node-edge network 2.

[0040] In other words, the input to software tool 14 is the (production) layout, which consists of the stations to be reached, available vacant spaces, and additional relevant information, such as a transport matrix including transport assignments, if necessary. When the input parameters change, nodes 6, 8, and edges 7 are regenerated (initially) or matched (during operation). Changes are either queried by software tool 14 or notified by external software. Nodes 6, 8, and edges 7 can be defined, for example, using geometric analysis, random distribution, optimization algorithms, or artificial intelligence methods and possible combinations thereof. Furthermore, optimization algorithms can be used to generate directed traffic flows using unidirectional edges 7. The output from software tool 14 is a node-edge network 2 that connects stations 3 and efficiently utilizes vacant spaces 4, taking into account large vehicle formations. Node-edge network 2 is transmitted to the dominant control unit and / or the moving body 5, thus enabling it to respond to matching.

[0041] During operation, matching requirements for navigation can be selectively derived systematically or based on events. In this case, a control loop or feedback step 400 can be used to adjust the system according to... Figure 2 Method extensions, such as in Figure 3 As shown in the diagram. In feedback step 400, it is checked whether a pre-given time has elapsed or whether an event has occurred. If neither of these conditions is met, no action is taken. If both conditions are met, the change caused by the event is added to input data 10.

[0042] New or updated input data 10 may in particular relate to changes in transport tasks, current traffic data 15, changes or information regarding altered industrial layout 1, and / or updates to obstacles in the industrial environment, particularly regarding new obstacles.

[0043] In software module 14, during operation, a possible transport matching step 110 is performed for the modified transport task 13 in the node-edge network 2. In the possible layout matching step 120, during operation, a matching is performed on the node-edge network 2 for the modified industrial layout 1, particularly regarding the modified station 12. In the possible traffic matching step 210, during operation, a matching is performed on the node-edge network 2 based on current traffic data 15. In this case, congestion and other delays are specifically considered. In the possible obstacle matching step 220, during operation, a matching is performed on the node-edge network 2 based on new or updated obstacles.

[0044] Figure 4 With Figure 2The same illustration shows an industrial layout 1, in which obstacles 15 are shown, which are constructed, for example, as immobile moving bodies 5. These obstacles 15 are particularly temporary. However, obstacles 15 can also be constructed as other interfering objects. Initially, obstacles 15 are surrounded in a face-like form by extensions 16. In generation step 200, in obstacle matching step 22, the node-edge network 2 is matched according to the new obstacle 15, such that affected edges 7 and / or path points 6 are eliminated or displaced. A malfunctioning moving body 5 causes a change in the node-edge network 2 by removing or displacing the involved nodes 3 and edges 7.

[0045] This approach enables the node-edge network 2 to be iteratively modified and optimized during operation based on changes in the industrial environment and / or functionality.

[0046] Figure 5 An industrial environment with arrangement 18 is illustrated schematically, wherein arrangement 18 has multiple stations 16 and multiple mobile bodies 5. Furthermore, arrangement 18 includes a control unit 17, wherein control unit 17 is configured to implement planning step 100 and generation step 200.

Claims

1. A method for navigating a mobile body (5) in an industrial environment, wherein the industrial environment has stations, and wherein transportation tasks are assigned to the mobile body (5). In the planning step (100), an industrial layout (1) is formed corresponding to the industrial environment, having station nodes (3) for the station and vacant space (4). In the generation step (200), a node-edge network (2) with path point nodes (6) and an edge (7) between the station node (3) and the path point node (6) is automatically generated based on the industrial layout (1) and the transportation task. In the use step (300), the moving body (5) moves in the industrial environment corresponding to the edge (7) of the node-edge network (2), and / or in the use step (300), control commands for the movement path of the moving body (5) are generated based on the generated node-edge network (2).

2. The method according to claim 1, characterized in that, In the generation step (200), the node-edge network (2) is optimized by making full use of the vacant space (4).

3. The method according to claim 1 or 2, characterized in that, The node-edge network is defined by means of geometric analysis, random distribution, optimization algorithms or artificial intelligence methods and possible combinations thereof (2).

4. The method according to any one of the preceding claims, characterized in that, At least a portion of the edge (7) is constructed as a unidirectional edge, on which the moving body (5) is only allowed to travel in one direction.

5. The method according to any one of the preceding claims, characterized in that, The node-edge network (2) is transmitted to the dominant control device of the mobile body (5) and / or to the mobile body (5).

6. The method according to any one of the preceding claims, characterized in that, The node-edge network (2) is matched during operation.

7. The method according to any one of the preceding claims, characterized in that... Transportation matching step (110), wherein the node-edge network is matched in operation with respect to the modified transportation task.

8. The method according to any one of the preceding claims, characterized in that... Layout matching step (120), wherein the node-edge network (2) is matched in operation for the modified industrial layout (1).

9. The method according to any one of the preceding claims, characterized in that... Traffic matching step (210), wherein traffic data about the mobile body (5) during operation is matched against the node-edge network (2).

10. The method according to any one of the preceding claims, characterized in that... Obstacle matching step (220), wherein the node-edge network (2) is matched according to obstacles (15) during operation.

11. An arrangement (18) for implementing the method according to any one of the preceding claims, the arrangement having a plurality of stations (16), a plurality of mobile bodies (5) and a control unit (17), wherein the control unit (17) is configured to implement the planning step (100) and the generation step (200).

12. A computer program, wherein the computer program is configured to implement the method according to any one of claims 1 to 10 when the computer program is executed on the arrangement (18) according to claim 11.

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