Method and system for locating a mobile device and mobile device

Abstract

Method for locating a mobile device (10, 20), in particular a vehicle, in an environment using a map (11) representing the environment by means of simultaneous positioning and mapping (SLAM), wherein the mobile device (10, 20) has an environment detection device (12) and a computing device (Sys1), and the method comprises the following steps: - detecting environmental data (SD) of the environment of the mobile device (10, 20) by means of the environmental detection device (12), - Localizing the mobile device (10, 20) by processing the acquired environmental data (SD) by - in a tracking (T) at least one environmental feature of the environment is determined from the recorded environmental data (SD), - in a mapping (M) the map (11) is provided with map data describing the environmental features of the environment represented by the map, and - in a loop closing (LC), a position of the mobile device (10, 20) in the environment is determined by comparing the acquired environmental data (SD) with the map data to compare the respective environmental features, - Provision of an additional computing device (Sys2), - providing a communication connection (13, 14, 15) between the computing device (Sys1) of the mobile device (10, 20) and the further computing device (Sys2), - determining an available bandwidth of the communication connection (13, 14, 15), - determining an available computing capacity of the computing device (Sys1) of the mobile device (10, 20), - determining an available computing capacity of the further computing device (Sys2) via the communication connection (13, 14, 15), - dividing the tracking (T), mappings (M) and / or loop closings (LC) between the computing device (Sys1) of the mobile device (10, 20) and the further computing device (Sys2) depending on the available bandwidth, the available computing capacity of the computing device (Sys1) of the mobile device (10, 20) and the available computing capacity of the further computing device (Sys2) according to a predetermined allocation rule (70) and - Transmission of processing data relating to the tracking (T), mapping (M) and / or loop closing (LC) assigned to the further computing device (Sys2) to the further computing device (Sys2), wherein an information content of the acquired environmental data (SD) is reduced by the computing device (Sys1) before the tracking (T) by means of a filter function (A) depending on the available bandwidth of the communication connection (13, 14, 15) and an information content of the processing data transmitted to the further computing device (Sys2) by the further computing device (Sys2) is reduced by means of a further filter function (B) depending on the available computing capacity of the further computing device (Sys2) before the assigned tracking (T), mapping (M) and / or loop closing (LC) is carried out.

Description

[0001] The invention relates to methods and a system for locating a mobile device in an environment. The invention also relates to a corresponding mobile device. Localization is performed using what is known as simultaneous localization and mapping (SLAM). This means that the SLAM method is used, in which a map of the mobile device's surroundings is created and its spatial location, i.e., its position, within this map or the surroundings is determined.

[0002] Maps enable mobile devices, such as vehicles, to independently locate themselves in an environment and can be used for navigation. Environmental properties are used for this purpose. These maps can be in two- or three-dimensional form.

[0003] With the SLAM method, an existing map can be used or created in parallel. These maps can require a lot of storage space. Outsourcing to a cloud can reduce storage requirements on the mobile device.

[0004] Using the SLAM method, a mobile device, e.g. a vehicle, can create a map of its surroundings and use this to estimate its current relative position in the environment. This allows the mobile device to be localized in the respective environment. To create the map, the mobile device can collect sensor data from the environment. This sensor data can be, for example, depth or RGB images. The sensor data can be evaluated to detect objects or edges of objects. The relative position of the detected objects to the mobile device can be stored in a frame (data structure for representing objects). By continuously recording the environment around the mobile device and detecting objects, classification can be performed and a map of the environment can be created.As the mobile device moves through the environment, the positions of the detected objects change according to the recorded sensor data. Based on this change, a relative position change of the mobile device can be estimated. If a map of the environment has been recorded, the mobile device can also independently determine its position by comparing its current sensor data with the map.

[0005] Overall, a localization method based on the SLAM method can essentially be divided into the following three processes: tracking or object detection (feature extraction), mapping or map creation, and loop closing or the recognition of similarities between the current image and the previously recorded map. The SLAM method accordingly comprises three modules: tracking module, mapping module, and loop closing module. Tracking is responsible for determining properties of the environment. The results are frames in which the environment is represented. Mapping is responsible for creating a map from these frames and / or providing the map. Loop closing is responsible for checking whether the system has already been to the location.

[0006] All three processes can be highly computationally intensive and time-critical, as, for example, the control of the mobile device may also depend on them. To provide the required computing power, the mobile device can be equipped with a processor (central processing unit, or CPU) and a graphics card with high computing capacity. However, such processors and graphics cards are expensive, often oversized, and generally consume a lot of energy. This can lead to shorter device runtimes. Another option is to offload the computing operations and thus the computing load from the mobile device.

[0007] To meet latency requirements, solutions based on edge computing or edge cloud computing can be used. Computationally intensive processes are offloaded to the edge, and the map is also stored there. A local map can remain on the local system, i.e., the mobile device.

[0008] For example, DE 10 2022 100 454 A1 discloses a method for locating an autonomously operated means of transport using a SLAM method. Environmental data acquired by the means of transport's sensors are dynamically outsourced to an external computing device, which can be provided by an edge cloud server.

[0009] Furthermore, DE 10 2021 130 382 A1 discloses a method for downloading sensor data from an autonomous vehicle to a computer external to the vehicle, which can be provided by an edge server. DE 10 2019 207 212 A1 also describes a method for processing sensor data. A digital map is created using acquired sensor data. The scope of the sensor data used for this purpose is adapted, i.e., reduced, to the available bandwidths within a vehicle or a wireless communication connection to an external stationary processing device.

[0010] From DE 2014 220 687 A1 a method is known in which a communication device of a vehicle receives location-related reference data from an external stationary server, a sensor of the communication device detects environmental data of the vehicle, the communication device determines a difference between the detected environmental data and the received reference data and transmits the determined difference to the stationary server.

[0011] US 2022 / 0 351 553 A1 describes data storage and retrieval in a distributed system comprising vehicles equipped with various sensors for automated driving and generating a large amount of sensor data. The sensor data contains information about the mapped physical environment. The sensor data is to be retrieved from the vehicles and made available in a useful manner.

[0012] From US 2016 / 0 358 030 A1 a method is known in which a video stream captured by a camera of a smartphone is transmitted to a stationary server, the stationary server detects and tracks objects contained in the video stream, determines data belonging to the detected and tracked objects and transmits the determined data to the smartphone and the smartphone displays the captured video stream with the transmitted data.

[0013] DE 10 2018 009 906 A1 discloses a method in which a system application, ie, an app, of a mobile terminal is executed in a distributed manner by the mobile terminal, the edge cloud computer and / or the cloud computer depending on determined respective computing capacities of the mobile terminal, an edge cloud computer and / or a cloud computer.

[0014] Cloud computing provides computing and storage services from a centralized location within a communications network. Cloud computing is suitable for applications that are not time-critical. Edge computing provides computing and storage services for applications that operate in real-time or near-real-time. Edge computing pushes computing to the edge of both wired and wireless networks to support mission-critical real-time applications. For example, an edge computing architecture can deploy data centers near cell towers or at regional levels instead of remotely in the cloud.

[0015] Against this background, the object of the invention is to provide methods and devices that realize a reliable and fast localization of a mobile device depending on the situation using the SLAM method.

[0016] This object is achieved by a method having the features of claim 1, by a mobile device having the features of claim 7, and by a system having the features of claim 9. Further, particularly advantageous embodiments of the invention are disclosed in the respective subclaims.

[0017] It should be noted that the features listed individually in the claims can be combined with one another in any technically reasonable manner (even across category boundaries, for example, between methods and devices) and demonstrate further embodiments of the invention. The description further characterizes and specifies the invention, particularly in conjunction with the figures.

[0018] It should also be noted that a conjunction "and / or" used herein between two features and linking them together is always to be interpreted in such a way that in a first embodiment of the subject matter according to the invention only the first feature can be present, in a second embodiment only the second feature can be present and in a third embodiment both the first and the second feature can be present.

[0019] The invention relates to a method for locating a mobile device in an environment using a map representing the environment by means of simultaneous positioning and mapping (referred to herein as SLAM), wherein the mobile device has an environment detection device and a computing device.

[0020] The mobile device can be, for example, a vehicle, in particular an autonomously operated vehicle, a mobile robot, a smartphone or similar.

[0021] The environment detection device may include, for example, radar, ultrasonic, optical sensors such as a camera, etc. The computing device may comprise one or more CPUs (computer processors), GPUs (graphics processors), FPGAs (field programmable gate arrays), or similar devices.

[0022] According to the invention, the method comprises the steps: - Collecting environmental data, in particular sensor data, of the environment of the mobile device by means of the environmental detection device, - Localize the mobile device by processing the collected environmental data by - in a tracking process, at least one environmental feature of the environment is determined from the recorded environmental data, - in a mapping, map data describing the map are provided which contain environmental features of the environment represented by the map, and - in a loop closing, a position of the mobile device in the environment is determined by comparing the recorded environmental data with the map data to compare the respective environmental features, - Providing an additional computing device (e.g. in the form of one or more CPUs, GPUs, FPGAs, etc.), - Providing a communication connection between the computing device of the mobile device and the further computing device, - Determine the available bandwidth of the communication connection, - Determining the available computing capacity of the mobile device’s computing device, - Determining the available computing capacity of the additional computing device via the communication connection, - Distributing the tracking, mapping and / or loop closing between the computing device of the mobile device and the further computing device depending on the available bandwidth of the communication connection, the available computing capacity of the computing device of the mobile device and the available computing capacity of the further computing device according to a predetermined allocation rule and - Transfer of processing data relating to the tracking, mapping and / or loop closing assigned to the further computing device to the further computing device.

[0023] In other words, the environmental data of the mobile device's surroundings are first captured using the environmental detection device. This means that the mobile device can record or capture its surroundings itself. The captured environmental data is then processed or evaluated. The processing of the environmental data is essentially divided into the three processes mentioned above: object detection (tracking), map creation (mapping), and map-image comparison (loop closing).

[0024] For object recognition, at least one environmental feature of the environment is determined from the recorded environmental data. Known methods such as FAST (Features from Accelerated Segment Test), BRIEF (Binary Robust Independent Elementary Features), ORB (Oriented FAST and Rotated BRIEF), etc. can be used for this purpose. The environmental feature can be, for example, a predetermined image feature and / or an object and / or an edge. In this case, the environment describes a detectable area within the vicinity of the mobile device. Depending on the environmental detection device used and the environmental topography, the detectable area can be a few meters to several kilometers. For example, an area with a radius of two to three kilometers around the mobile device can be detected as the environment. The environmental data can map this environment.The environmental data can be provided, for example, by a respective sensor of the environmental detection device as sensor data or measurement data. If the environmental detection device is designed as a camera, for example, the environmental data can be present as image data, such as an RGB image, stereo image, or depth image. Of course, depending on the design of the environmental detection device, other forms of environmental data are also possible. The environmental detection device can, for example, additionally or alternatively be designed as a radar system, lidar system, or ultrasound system. The evaluation of the environmental data to determine the respective environmental feature can be carried out, for example, using known object recognition algorithms or feature detection methods.

[0025] To create a map, map data describing a map of the mobile device's surroundings is provided. The map data includes environmental features of the environment represented by the map. The mobile device can create the map itself, for example, by cyclically recording the environment from the recorded environmental data. Alternatively, the mobile device can load or retrieve the map data from an internal data storage device or an external data server. When using an external data server, the map data can be used by several different mobile devices, for example. For example, a first mobile device can access the map data of a second mobile device.

[0026] Finally, for the map-image comparison, the position of the mobile device in the environment is determined by comparing the captured environmental data with the map data to match the respective environmental features. This means that it is checked whether and where environmental features in the map correspond to the detected environmental features. In other words, similarities between the map and the environmental data are determined.

[0027] In order to be able to outsource the individual processing steps for processing the recorded environmental data, the additional computing device is provided. Several, i.e. two or more, corresponding computing devices can be provided. The respective computing device can be used to carry out the corresponding computing operations for processing the environmental data as needed. For this purpose, the corresponding processing data can be sent between the computing device of the mobile device and the additional computing device. Processing data refers to the data that arises when processing or evaluating the recorded environmental data. This can be data or data packets that are sent to the additional computing device for processing (data to be processed) or data that is sent back from the additional computing device after processing (processed data).

[0028] To transmit the processing data, a communication connection is provided or established between the computing device of the mobile device and the further computing device. The communication connection can be wireless, for example, but is not necessarily limited to this. It can be a radio connection, such as a WLAN connection or a mobile radio connection. To establish the communication connection, the respective computing devices can have a respective communication module with a corresponding radio interface.Wired communication connections can be provided, for example, via network cables in a LAN (Local Area Network), via a communication bus formed on a circuit board on which the respective computing devices can be provided, or via a communication bus of a so-called system-on-a-chip (SoC), in which both the respective computing devices and the communication bus can be provided chip-internally.

[0029] In any event, the invention provides a communication link with a high capacity in terms of possible throughput, which enables a division of bandwidth-intensive applications between at least two computing devices, even if the communication link is a wireless communication link such as a radio link.

[0030] In order to realize a situation-dependent (i.e. dynamic) reliable and fast localization of the mobile device in the environment, the currently available bandwidth of the communication connection, the currently available computing capacity of the computing device of the mobile device and the currently available computing capacity of the other computing device are determined.

[0031] The available bandwidth indicates in particular how quickly or what amount of data can be transmitted at a specific point in time per unit of time via the communication connection between the computing device of the mobile device and the other computing device.

[0032] The available computing capacity of the mobile device's computing device can be determined directly by querying its current utilization. The available computing capacity of the additional computing device, however, is provided to the mobile device via the communication connection and can be determined in this way. The available computing capacity of the additional computing device can be shared with the mobile device, for example, via regularly transmitted synchronization messages, but also irregularly, for example, event-driven when a predetermined capacity threshold is exceeded. This is a preferred option, especially for wireless communication connections.In wired communication connections where both computing devices are deployed on the same circuit board, for example, the current utilization of the additional computing device can be retrieved directly, especially if the additional computing device is deployed, for example, as a container or virtual machine, running the same operating system. If the mobile device's computing device and the additional computing device have different operating systems, messages or so-called signals can be used to exchange available computing capacity.

[0033] Depending on the available bandwidth, the available computing capacity of the mobile device's computing device, and the available computing capacity of the additional computing device, the steps for locating the mobile device—i.e., the steps for processing the environmental data (also referred to herein as processing steps), in particular tracking, mapping, and / or loop closing—are distributed between the mobile device's computing device and the additional computing device according to a predefined allocation rule (dynamic load balancing). This means that all processing steps can be performed by exactly one of the computing devices, or some of the processing steps can be performed by the mobile device's computing device and another part of the processing steps by the additional computing device.For example, object detection (tracking) in the environmental data can be performed using the mobile device, while the analysis of the environmental data for edges (mapping) is performed using the additional computing device. For simplicity, we will refer to the division or allocation of processing steps below. This term also includes the division of processing steps into sub-steps or individual computing operations.

[0034] The dynamic load distribution proposed according to the invention essentially comprises three basic variants of the SLAM method: In the first variant (also referred to herein as "full offload", FO), the three modules of the SLAM method mentioned above, i.e., tracking, mapping, and loop closing, are outsourced to the additional computing device. In the second variant (also referred to herein as "partial offload", PO), only the mapping and loop closing are outsourced to the additional computing device. This allows the use of more powerful systems for the computationally intensive mapping and loop closing. In the third variant, the complete calculation for localizing the mobile device takes place on the mobile device itself (also referred to herein as "on device", OD).

[0035] "Full Offload" requires the least computing power on the mobile device or the computing device provided by it, as sensor data generated by the mobile device is forwarded directly to the additional computing device via a (e.g., wireless) communication connection to determine the properties of its environment. However, this requires a higher bandwidth in the communication channel of the communication connection.

[0036] "Partial offload," on the other hand, requires more computing power on the mobile device or the computing device provided by it, since the tracking remains on the mobile device and is performed by it. However, this is already significantly reduced compared to full on-device computing. The requirements for the communication connection, especially its available bandwidth, are lower with "partial offload."

[0037] By splitting up the processing steps, there is the advantage that complex computing tasks or operations can be distributed between the respective computing devices. If necessary, complex computing operations can be offloaded from the mobile device. Furthermore, the processing of environmental data can be parallelized. This allows performance advantages to be achieved through higher computing capacity. The mobile device can be localized efficiently and reliably. By taking into account the available bandwidth and the available computing capacity of the respective computing devices, a qualified decision can be made as to which computing operations should be outsourced at all. This can ensure, for example, that the processing data is only outsourced if the data transfer can essentially be completed within a specified period of time.This allows the mobile device to be localized as quickly as possible, essentially in real time, depending on the situation. Dynamically outsourcing the processing steps also has the advantage that less or less powerful hardware can be used on the mobile device. This saves costs, making the mobile device less expensive to manufacture. Furthermore, the mobile device is lighter and consumes less energy.

[0038] Furthermore, the invention enables a higher map creation rate, a higher speed of object or map change detection, and improves localization accuracy. Furthermore, the probability of failure (e.g., due to track loss) in localization and mapping is reduced. Furthermore, the invention achieves high flexibility for implementation in different application scenarios.

[0039] Furthermore, in the case of a vehicle, precise and reliable localization of the mobile device can ensure the safe functionality of driving safety functions and enable autonomous driving. Resource consumption on the mobile devices can be adjusted depending on the situation. This allows computing capacity on the mobile device to be made available for other relevant safety functions provided by the mobile device.

[0040] In an advantageous embodiment, a maximum number of environmental features determined from the acquired environmental data during tracking is dynamically adjusted depending on the available computing capacity of the mobile device and / or the available bandwidth of the communication connection and / or a capture rate of the environmental data (e.g., frame rate of a camera) and / or a movement speed of the mobile device according to a predetermined further assignment rule. The more environmental features determined during tracking, the greater the computing effort and the larger the resulting data volume, which may need to be transmitted to the further computing device via the communication connection. In this way, both the computing capacity required for tracking and for the downstream mapping and / or loop closing can be flexibly adapted to the current utilization of the respective computing device.

[0041] Alternatively or additionally, the maximum number of environmental features to be determined can be reduced when the mobile device, e.g., a vehicle, is moving at a high linear speed in order to reduce computational latency. When moving along a curved path, e.g., cornering, the maximum number can be increased to capture more new environmental properties or features, or reduced to achieve lower computational latency. The decision to increase or decrease the number can depend on the speed of movement / curve, a number of existing environmental properties / features, the available computing capacity, and / or the prevailing environmental conditions (e.g., lighting, fog, etc.). The speed of movement can be recorded by sensors on the mobile device (e.g., vehicle sensors) or by visual odometry (in the tracking module).

[0042] Furthermore, according to the invention, the information content of the acquired environmental data is reduced prior to tracking depending on the available bandwidth of the communication connection. For example, a provided filter function can be used to reduce a camera's frame rate and / or reduce or remove image quality such as resolution and colors. The filter function is preferably applied to the data stream generated by the environmental detection device. If the computing device and / or the communication connection is under high load, the data stream can be reduced. The reduction can be determined by a function of the available bandwidth of the communication connection and a capture rate of the environmental data (e.g., incoming frame rate).

[0043] Furthermore, according to the invention, an information content of the processing data transmitted to the further computing device is reduced by the further computing device before executing the assigned tracking, mapping, and / or loop closing, depending on the available computing capacity of the further computing device. For example, by means of a provided further filter function, a frame rate of a camera whose images are contained in the transmitted processing data can be reduced and / or an image quality such as resolution and colors can be reduced or removed. The further filter function can be applied by the further computing device to the received data stream of the processing data. If the further computing device is under high load, the data stream can be reduced.

[0044] Still further advantageous embodiments provide for the processing data to be compressed before being transmitted to the additional computing device and decompressed after being transmitted from the additional computing device before executing the assigned tracking, mapping, and / or loop closing. Compression can be performed either losslessly or with lossy compression. Lossy compression allows for greater compression of the processing data.

[0045] In other advantageous embodiments, the additional computing device is provided by the mobile device or externally by means of another mobile device, a cloud server, or an edge cloud server. In the first case, the two computing devices of the mobile device can be provided as hardware on a system-on-a-chip. Alternatively or additionally, the additional computing device of the same mobile device can also be provided virtually, i.e., in software terms, in a virtual environment of the control software (e.g., operating system) of the mobile device.

[0046] The communication connection can be provided as a wired connection or a wireless radio connection. The radio connection is preferably designed according to the 5G mobile communications standard or the WLAN standard IEEE 802.11ax, but is not necessarily limited to these. The aforementioned radio standards can ensure that, in particular, the latency and reliability of the communication connection for transmitting the processing data are known.

[0047] The additional mobile device can, for example, be another vehicle. Accordingly, the communication connection can be direct vehicle-to-vehicle (V2V) communication. In addition to the processing data, information about the previously determined / already known topology of the environment can be transmitted to the additional mobile device. In this way, if there is insufficient computing capacity available on the mobile device (e.g., a vehicle), the computing capacity of another mobile device (e.g., another vehicle) can be used to perform tracking, mapping, and / or loop closing. This allows the map calculated on one mobile device to also be used on the other mobile device. Furthermore, map details can also be distributed to other mobile devices (e.g., other vehicles in the area).

[0048] Providing the additional computing device via a cloud server or edge cloud server offers the advantage that the SLAM process steps can be carried out in a particularly efficient, decentralized manner. In this case, an edge cloud server refers to a server device whose computing capacity is located as close as possible to the end device generating the data, in this case, the mobile device (e.g., a vehicle). This avoids communication bottlenecks, as direct physical communication connections or robust wireless communication connections are feasible. Furthermore, the edge devices can concentrate computing resources on a smaller set of data, thus avoiding the extensive use of computing resources in a cloud.

[0049] The term "edge" describes the data processing taking place at the edge of a shared network. This means that the external computing device and the mobile device can be part of a local or closed computer network, such as a corporate network at a location. This avoids the time delays of data transmission within the network, i.e., over the communication connection. In contrast, a cloud server refers to an external server facility, i.e., outside of a local computer network. Processing using an edge cloud server also has the advantage that the map data, i.e., the map, is available in a central computing facility.

[0050] There it can, for example, be used or improved by other mobile devices.

[0051] Furthermore, the invention relates to a mobile device, in particular a vehicle, which is designed to carry out a localization in an environment of the mobile device using a map representing the environment by means of simultaneous positioning and mapping (SLAM), comprising: - an environment detection device designed to detect environmental data of the environment, - a computing device designed and configured to locate the mobile device by processing the acquired environmental data, - to determine at least one environmental feature of the environment from the recorded environmental data in a tracking process, - to capture map data describing the map in a mapping, which contain environmental features of the environment represented by the map, and - to determine a position of the mobile device in the environment in a loop closing by comparing the recorded environmental data with the map data to compare the respective environmental features, - a communication module for providing a communication connection between the computing device of the mobile device and another computing device, and - a control device which is designed - to determine the available bandwidth of the communication connection, - to determine the available computing capacity of the mobile device’s computing device and - to determine the available computing capacity of the additional computing device via the communication connection, and - to distribute the tracking, mapping and / or loop closing between the computing device of the mobile device and the further computing device depending on the available bandwidth, the available computing capacity of the computing device of the mobile device and the available computing capacity of the further computing device according to a predetermined allocation rule and - to control the communication module for transmitting processing data relating to the tracking, mapping and / or loop closing assigned to the further computing device to the further computing device.

[0052] It should be understood that with regard to device-related definitions of terms as well as the effects and advantages of device-related features, the disclosure of corresponding definitions, effects, and advantages of the method according to the invention can be fully relied upon, and vice versa. Repetition of explanations of similar features, their effects, and advantages can thus be omitted in favor of a more concise description, without such omissions being interpreted as a limitation of any of the disclosed subject matter of the invention.

[0053] In advantageous embodiments, the mobile device is designed as a vehicle, in particular as an autonomously operable vehicle, mobile robot or smartphone.

[0054] A further subject matter of the invention is a system for locating a mobile device, in particular a vehicle, comprising the mobile device according to one of the embodiments disclosed herein and a further computing device which is designed to carry out the tracking, mapping and / or loop closing assigned to it according to an embodiment of the method according to the invention disclosed herein.

[0055] In advantageous embodiments, the further computing device is provided by means of the mobile device or externally by means of another mobile device, in particular another vehicle, a cloud server or an edge cloud server.

[0056] Further features and advantages of the invention will become apparent from the following description of non-limiting embodiments of the invention, which are explained in more detail below with reference to the drawings. In this drawing, schematically show: Fig. 1 shows in four partial views (a)-(d) a mobile device for performing localization by means of simultaneous positioning and mapping (SLAM) and a related system, each according to different embodiments of the invention; Fig. 2 a functional diagram of localisation using simultaneous positioning and mapping (SLAM); Fig. 3 is a functional diagram for describing a method for locating a mobile device using simultaneous positioning and mapping (SLAM) according to an embodiment of the invention; Fig. 4 is a functional diagram for describing a method for locating a mobile device using simultaneous positioning and mapping (SLAM) according to another embodiment of the invention; Fig. 5 shows a section of four exemplary embodiments of the method from Fig. 3; Fig.6 shows a section of two exemplary embodiments of the method from Fig. 4; Fig. 7 a diagram for the dynamic selection of Fig. 6 states according to a predetermined assignment rule; and Fig. 8 a diagram for the dynamic limitation of a number n F of environmental features to be determined according to a further assignment rule.

[0057] In the different figures, parts that are equivalent in terms of their function are always provided with the same reference symbols, so that they are usually only described once.

[0058] Fig.1 schematically shows in four partial views (a), (b), (c) and (d) a mobile device 10 and 20 for performing localization by means of simultaneous positioning and mapping (SLAM) and a related system 50, 51, 52, 53, each according to different embodiments of the invention.

[0059] In Fig. In Figure 1, mobile devices 10 and 20 are each depicted as vehicles, but are not necessarily limited to these. For example, a mobile device can be a smartphone or a mobile robot.

[0060] Each of the illustrated mobile devices 10 and 20 is configured to perform a localization in an environment of the respective mobile device 10 or 20 using a map 11 representing the environment (cf. Fig. 2) using simultaneous positioning and mapping (SLAM).

[0061] The mobile devices 10, 20 each have an environment detection device 12 (cf. Fig. 2) which are used to collect environmental data SD (cf. Fig. 2) the environment, and a computing device Sys1, which is designed and configured to locate the mobile device 10 or 20 by processing the acquired environmental data SD, - in a tracking T (cf. Fig. 2) to determine at least one environmental feature of the environment from the recorded environmental data SD, - in a mapping M (cf. Fig. 2) to provide map data describing the map 11, which include environmental features of the environment represented by the map 11, and - in a Loop Closing LC (cf. Fig. 2) to determine a position of the mobile device 10 or 20 in the environment by comparing the recorded environmental data with the map data to compare the respective environmental features.

[0062] The mobile devices 10, 20 further comprise a communication module (not shown) for providing a communication connection 13, 14 or 15 between the computing device Sys1 of the mobile device 10, 20 and a further computing device Sys2, as well as a control device (not shown) which is designed to determine an available bandwidth of the communication connection 13, 14, 15, to determine an available computing capacity of the computing device Sys1 of the mobile device 10 or 20 and to determine an available computing capacity of the further computing device Sys2 via the communication connection 13, 14 or 15 and to carry out the tracking T, mapping M and / or loop closing LC between the computing device Sys1 of the mobile device 10 or 20 and the further computing device Sys2 as a function of the available bandwidth, the available computing capacity of the computing device Sys1 of the mobile device 10 or 20.20 and the available computing capacity of the further computing device Sys2 according to a predetermined allocation rule and to control the communication module for transmitting processing data relating to the tracking T, mapping M and / or loop closing LC allocated to the further computing device Sys2 to the further computing device Sys2.

[0063] As in Fig. 1, the communication connection 13 and 15 for transmitting the processing data between the computing device Sys1 of the mobile device 10 and the further computing device Sys2 can be designed wirelessly, for example as a radio connection based on a WLAN or mobile radio standard.

[0064] In Fig.1, the further computing device Sys2 is provided in view (a) as an edge cloud server 60. In view (c), the further computing device Sys2 is provided as a computing device of a further mobile device 30, i.e., the communication connection 15 is a direct vehicle-to-vehicle communication connection (V2V). The direct V2V communication connection enables direct map sharing and cooperative mapping between the two mobile devices 10 and 30. The mobile device 30 can be designed and configured essentially like the mobile device 10, so that in this case the computing device Sys2 can perform essentially the same functions as the computing device Sys1 of the mobile device 10. In particular, the computing device Sys2 can be designed to carry out a method according to the invention according to one of the embodiments disclosed herein. However, the invention is not necessarily limited thereto, i.e.the mobile device 30 including its computing device Sys2 do not necessarily have to be designed to carry out the method according to the invention.

[0065] The edge cloud server 60 may be part of a server system, cloud system, or an edge cloud system or multi-access edge cloud system (MEC).

[0066] In view (b) of the Fig. 1, the communication connection 14 is configured as a wired communication connection, since the two computing devices Sys1 and Sys2 are provided on the same mobile device 20, e.g., in the form of a system-on-a-chip. The division of the two computing devices Sys1 and Sys2 within the same mobile device 20 can include different hardware chips or a single hardware chip with different virtualized systems (e.g., containers, virtual machines).

[0067] View (d) of the Fig.1 shows a wireless communication connection 13 on the one hand between the mobile device 10 and the edge cloud server 60 and a forwarding or distribution of the map 11 to at least one further mobile device 30' (e.g. vehicle) with a further computing device Sys2', which can be designed and configured essentially like the mobile device 10, but without necessarily being limited thereto, ie the mobile device 30' including its computing device Sys2' do not necessarily have to be designed to carry out the method according to the invention.

[0068] Fig. Figure 2 shows a functional diagram of localization using simultaneous positioning and mapping (SLAM). The calculation of the entire SLAM method on a single computing device, e.g., computing device Sys1, is referred to as "On Device" (OD) execution and declared as state S0.

[0069] After the environmental data SD is output from the environmental detection device 12, e.g., a camera (optical, monocular, RGB-D, LIDAR, etc.), the environmental features are extracted and classified in the tracking T. Methods such as ORB, FAST, BRIEF, etc. can be used for this purpose. The number of extracted or determined environmental features is denoted by n. F designated.

[0070] The positions of the determined and recognized environmental features in an image are referred to as a frame. Based on a defined decision criterion, a decision is made as to whether a frame is declared as a keyframe KF. The decision can be based, for example, on a (relative or absolute) number of newly determined / found and classified environmental features. The keyframe KF contains sufficient new information to provide added value for map 11 or localization. When a new keyframe KF is declared, it is forwarded to mapping M. The mobile device can be localized using map 11 created in mapping M. Additionally, loop closing LC is performed.

[0071] Fig.Figure 3 shows a functional diagram for describing a method for locating a mobile device using simultaneous positioning and mapping (SLAM) according to an embodiment of the invention, which is referred to as "Full Offload" (FO). Fig. 3, dashed rectangles indicate optional process steps which, in combination with the other process steps shown, form further embodiments of the process according to the invention.

[0072] The method is used to locate a mobile device, e.g., the mobile devices 10, 20, in an environment using the map 11 representing the environment by means of simultaneous positioning and mapping (SLAM), wherein the mobile device 10, 20 has the environment detection device 12 and the computing device Sys1.

[0073] The environmental data SD of the environment of the mobile device 10, 20 are first acquired by the environmental detection device 12. The mobile device 10, 20 is localized by processing the acquired environmental data SD, in that in tracking T at least one environmental feature of the environment is determined from the acquired environmental data SD, in mapping M map data describing the map 11 are provided, which have environmental features of the environment represented by the map 11, and in loop closing LC a position of the mobile device 10, 20 in the environment is determined by comparing the acquired environmental data with the map data to compare the respective environmental features.

[0074] Tracking T, Mapping M and Loop Closing LC can be found in the in Fig. 3, the execution of the execution takes place on the additional computing device Sys2 provided, which is why the situation shown is also referred to as “Full Offload” FO.

[0075] Furthermore, Fig. 3 that a communication connection, for example a communication connection 13, 14 or 15 as in Fig. 1, is provided between the computing device Sys1 of the mobile device 10, 20 and the further computing device Sys2.

[0076] An available bandwidth of the communication connection 13, 14 or 15, an available computing capacity of the computing device Sys 1 of the mobile device 10, 20 and an available computing capacity of the further computing device Sys2 via the communication connection 13, 14 or 15 are determined. The latter can be provided to the computing device Sys1 from the further computing device Sys2 by means of messages transmitted via the communication connection 13, 14 or 15.

[0077] The tracking T, mapping M, and / or loop closing LC are distributed between the computing device Sys1 of the mobile device 10, 20 and the further computing device Sys2 depending on the available bandwidth, the available computing capacity of the computing device Sys1, and the available computing capacity of the further computing device Sys2 according to a predetermined allocation rule. In the present case, the distribution is carried out, for example, such that the tracking T, mapping M, and loop closing LC are performed by the further computing device Sys2. Accordingly, processing data relating to the allocated tracking T, mapping M, and loop closing LC are transmitted to the further computing device Sys2 via the communication connection 13, 14, or 15, respectively.

[0078] In Fig.Figure 3 further illustrates that the information content of the acquired environmental data SD is reduced prior to tracking T, depending on the available bandwidth of the communication connection 13, 14, or 15, using a correspondingly configured filter function A, as already explained in the general part of this description. The filter function A is provided by the computing device Sys1.

[0079] In addition, the information content of the processing data transmitted to the additional computing device Sys2 is reduced by the additional computing device Sys2 before executing the assigned tracking T, mapping M, and / or loop closing LC, depending on the available computing capacity of the additional computing device Sys2, using a correspondingly configured filter function B, as also explained in the general part of this description. The filter function B is provided by the additional computing device Sys2.

[0080] Alternatively or additionally, the processing data can be compressed by the computing device Sys1 using a compression function C before being transmitted to the further computing device Sys2, and decompressed after being transmitted by the further computing device Sys2 using a decompression function D before executing the assigned tracking T, mapping M, and / or loop closing LC. The compression C can be performed either losslessly or with lossy data, e.g., depending on the currently available bandwidth of the communication connection 13, 14, or 15.

[0081] Fig. Fig. 4 is a functional diagram for describing a method for locating a mobile device, e.g., one of the mobile devices 10, 20 Fig. 1, by means of simultaneous positioning and mapping (SLAM) according to a further embodiment of the invention, which is referred to as “partial offload” (PO).

[0082] The main difference of the Fig. 4 to the procedure described in Fig. 3 shows that the tracking T is carried out on the computing device Sys1 of the mobile device 10 or 20 and the mapping M and loop closing LC on the further computing device Sys2.

[0083] As in the example from Fig. 3 can also be used in the embodiment of the Fig. 4 optionally a filter function A is applied to the data stream of the acquired environmental data SD by the computing device Sys1 and / or a filter function B is applied to the data stream of the processing data transmitted via the communication connection 13, 14 or 15 by the further computing device Sys2.

[0084] If the processing data is compressed by the computing device Sys1 using the compression function C (lossless or lossy) before transmission via the communication connection 13, 14, or 15, the compression function C is applied by the computing device Sys1 to the processing data to be transmitted after tracking T. The further computing device Sys2 applies the decompression function D to the transmitted processing data after reception and feeds the decompressed processing data to the mapping M.

[0085] Since in Fig.4 If tracking T is executed on the computing device Sys1, a local copy of the map 11 containing the map data describing the environment is provided to the computing device Sys1. For this purpose, the map 11 provided, created, and / or updated on the additional computing device Sys2, or parts thereof, can be transmitted to the computing device Sys1 via the communication connection 13, 14, or 15.

[0086] Fig. 5 shows a section of four exemplary embodiments of the method Fig. 3 (“Full Offload”, FO), which are designated by the FO states S1, S2, S3 and S4, where the FO state S3 is further divided into two FO substates S3 l and S3 ll is divided into Fig. 5, the respective section only represents the steps after the acquisition of the environmental data SD (cf. Fig. 3) up to tracking T.

[0087] The first FO state S1 concerns the case that the recorded environmental data SD (cf. Fig. 3) essentially without further processing from the computing device Sys1 as processing data via the communication connection 13, 14 or 15 to the further computing device Sys2, which in Fig. 5 is symbolized by a transfer function S. The reception of this processing data by the further computing device Sys2 is in Fig. 5 symbolized by a receiving function R.

[0088] The second FO state S2 concerns the case that the recorded environmental data SD (cf. Fig. 3) be filtered before transmission to the further computing device Sys2 using the filter function A, as already described in detail elsewhere herein.

[0089] The third FO state S3 concerns the case that the recorded environmental data SD (cf. Fig.3) are compressed by the computing device Sys1 before being transmitted to the further computing device Sys2 using the compression function C. Here, the FO state S3 is divided into the two FO substates S3 l and S3 ll divided, with the first FO substate S3 l a lossy compression is used and the second FO substate S3 ll A lossless compression, which can be used optionally, is used. The additional computing device Sys2 applies the decompression function D to the received processing data.

[0090] The fourth FO state S4 relates to the case that the processing data received from the further computing device Sys2 are filtered by means of the filter function B as described herein before being fed to the tracking T.

[0091] Fig.6 shows a section of two exemplary embodiments of the method Fig. 4 (“Partial Offload”, PO), which are designated by the PO states S5 and S6, where the PO state S6 is further divided into two PO substates S6 l and S6 ll is divided into Fig. 6, the respective section only represents the steps from tracking T of the recorded environmental data SD (cf. Fig. 3) by the computing device Sys1 until after the receipt of the transmitted processing data by the further computing device Sys2.

[0092] The first PO state S5 concerns the case that the recorded environmental data SD (cf. Fig. 3) after the tracking T, the processing data are transferred from the computing device Sys1 to the further computing device Sys2 via the communication connection 13, 14 or 15, which is Fig.6 is symbolized by the transfer function S. The reception of this processing data by the further computing device Sys2 is in Fig. 6 symbolized by the receiving function R.

[0093] The second PO state S6 concerns the case that the recorded environmental data SD (cf. Fig. 3) are compressed by the computing device Sys1 after tracking T before transmission to the further computing device Sys2 using the compression function C. Here, the PO state S6 is divided into the two PO substates S6 l and S6 ll divided, with the first PO substate S6 l a lossy compression is used and the second PO substate S6 ll a lossless compression, which can be selected optionally. The additional computing device Sys2 applies the decompression function D to the received processing data.

[0094] Based on the Fig. 5 and Fig. 6, it is explained below by way of example how the tracking T, mapping M and / or loop closing LC are distributed between the computing device Sys1 of the mobile device 10 or 20 and the further computing device Sys2 depending on the available bandwidth, the available computing capacity of the computing device Sys1 of the mobile device 10 or 20 and the available computing capacity of the further computing device Sys2 according to a predetermined allocation rule.

[0095] The available computing capacity RL v one of the computing devices Sys1 or Sys2 can be determined by the respective computing device Sys1, Sys2 by querying the current relative processor load RL A An index I RLwhich defines the computing capacity of the respective computing device Sys1, Sys2. This allows computing devices with different computing capacities (e.g., different processor hardware) to be compared: RLV=(1−RLA)∗IRL

[0096] The respective states S1-S6 can be set depending on the available computing capacity on Sys1 RL v (Sys1) and on Sys2 RL v (Sys2) and the available bandwidth BW of the communication link 13, 14, 15.

[0097] The required computing capacity RL A the individual states S1-S6 on Sys1 can be ordered as follows: [RLA(S1)=RLA(S4)] <RLA(S2)<RLA(S3l)<RLA(S5)<RLA(S3) <RLA(S6l)<RLA(S6)

[0098] The required bandwidth BW req the communication connection 13, 14, 15 of the individual states on Sys1 can be arranged as follows: BWreq(S6l) <BWreq(S6)<BWreq(S5)<BWreq(S3l)<BWreq(S3) <BWreq(S2)<[BWreq(S1)=BWreq(S4)]

[0099] To select the currently most suitable state, ie, to optimally distribute the processing steps between the computing devices Sys1 and Sys2, a matrix can be used, which is shown below. BW rel High (H) BW rel Low (L) RL V (Sys1) H / Depending on bandwidth, Depending on I RL-BW (Sys2): RL V (Sys2) H falling BW rel : S6 l S1 S6 S3 S5 [rising I RL-BW (Sys2)] Dependence, since here the priorities ity on the processing in the map- ping M and Loop Closing LC is RL V (Sys1) H / S5 S0 RL V (Sys2) L S6 S5 S6 l S6 l S4 [Rising I RL-BW (Sys2)] [Rising I RL-BW (Sys2)] RL V (Sys1) L / S1 S2 RL V (Sys2) H S2 S3 l S4 S3 S3 l [Rising I RL-BW (Sys1)] S3 Here Sys1, because here the limitation [Rising is present I RL-BW (Sys1)] Here Sys1, since here the Li- mitation is present RL V (Sys1) L / S2 S2 RL V (Sys2) L S4 S3 l S1 S5 (if necessary in combination with [Rising fit of n F (cf. Fig. 8)) I RL-BW (Sys2)] [Rising I RL-BW (Sys2)]

[0100] The decision threshold of the states within the matrix fields I RLBW (Sys) is determined by the available computing capacity on the two computing devices Sys1, Sys2 and the available relative bandwidth BW rel given: IRLBW(Sys)=∝∗RLV(Sys)+β∗BWrel

[0101] The relative bandwidth BW rel indicates the available bandwidth of the communication link, e.g. communication link 13, 14, 15, depending on the maximum bandwidth of the communication link.

[0102] A weighting of the available computing capacity is defined with ∝ and the weighting of the available bandwidth with β under the condition: ∝+β=1. Fig. 7 shows an example diagram for the dynamic selection of the Fig. 6 shown states S5, S6 l and S6 ll according to a predetermined assignment rule 70. The case shown applies for β > ∝ and represents the matrix field RL v (Sys1) H / RL y (Sys2)H Λ BW rel L. It is in Fig. 7 shows that depending on the decision threshold I RL BW (Sys2) the respectively displayed states S6 l , S6 ll or S5 can be selected.

[0103] In addition, the number n F the environmental features to be extracted in the tracking T. n Fcan be reduced or increased depending on the available bandwidth of the communication connection, the available computing capacity, or the acquisition rate (e.g., frame rate) of the environmental data. The dependence can be linear, exponential, or logarithmic, for example.

[0104] Fig. 8 shows a diagram for dynamically limiting the number n F of the environmental characteristics to be determined. In Fig. 8 it can be seen that the number of environmental features determined n Fwith an increasing number of acquired environmental data SD (e.g. images from a camera) increases until it reaches a maximum value predetermined by a boundary line 71. The height of the boundary line 71 can be dynamically adjusted depending on the available computing capacity of the computing device Sys1 of the mobile device 10, 20 and / or the available bandwidth of the communication connection 13, 14, 15 and / or a capture rate of the environmental data SD and / or a movement speed of the mobile device 10, 20, which is indicated by the double arrow 72 in Fig. 8 is indicated.

[0105] To set High (H) or Low (L) of BW rel and RL v In the matrix shown above, threshold values ​​can be set depending on the total computing capacity and the available bandwidth of the communication link depending on, for example, a resolution of the environmental data (e.g. camera images), a predetermined value for nF and a sampling rate (e.g., frame rate) of the ambient data. These values ​​can be determined and set application-specifically and / or empirically.

[0106] For example, a threshold for the required bandwidth BW rel for the transmission of processing data according to state S5. This value corresponds to the threshold BW schw . If BW rel > BW schw : then BW applies rel H, otherwise BW rel L.

[0107] Alternatively or additionally, a threshold for carrying out the tracking T and sending the processing data RL A (S5,Sys1). This value corresponds to the processor load on Sys1. If RL v (Sys1) > RL A (S5, Sys1), then RL v (Sys1) H, otherwise RL v (Sys1) L.

[0108] Alternatively or additionally, a value of the processor utilization for receiving the processing data and performing the mapping M and loop closings LC on Sys2 RL A (S5, Sys2). If RL v (Sys2) > RL A (S5, Sys2), then RL v (Sys2) H, otherwise RL v (Sys2) L. LIST OF REFERENCE SYMBOLS: 10 Mobile device 11 map 12 Environmental detection device 13 Communication connection 14 Communication connection 15 Communication connection 20 Mobile Device 30 Mobile Device 30' Mobile Device 50 systems 51 System 52 systems 53 Systems 60 edge cloud servers 70 Allocation rule 71 boundary line 72 Dynamic adjustment of 71 A Filter function A B Filter function B C compression function D Decompression function I RL BW Decision threshold n F Number of environmental features identified n SD Number of environmental data collected R Receive processing data S Send processing data SD Recorded environmental data Sys1 computing device Sys2 Additional computing device Sys2' Additional computing device S0 OD state S1 First FO state S2 Second FO state S3 Third FO state S3 l First FO substate of S3 S3 ll Second FO substate of S3 S4 Fourth PO state S5 First PO state S6 Second PO state S6 l First PO substate of S6 S6 ll Second PO substate of S6 KF Keyframe LC Loop Closing M Mapping SLAM Simultaneous Positioning and Mapping T Tracking

Claims

[1] Method for locating a mobile device (10, 20), in particular a vehicle, in an environment using a map (11) representing the environment by means of simultaneous positioning and mapping (SLAM), wherein the mobile device (10, 20) has an environment detection device (12) and a computing device (Sys1), and the method comprises the following steps: - detecting environmental data (SD) of the environment of the mobile device (10, 20) by means of the environmental detection device (12), - Localizing the mobile device (10, 20) by processing the acquired environmental data (SD) by - in a tracking (T) at least one environmental feature of the environment is determined from the recorded environmental data (SD), - in a mapping (M) the map (11) is provided with map data describing the environmental features of the environment represented by the map, and - in a loop closing (LC), a position of the mobile device (10, 20) in the environment is determined by comparing the acquired environmental data (SD) with the map data to compare the respective environmental features, - Provision of an additional computing device (Sys2), - providing a communication connection (13, 14, 15) between the computing device (Sys1) of the mobile device (10, 20) and the further computing device (Sys2), - determining an available bandwidth of the communication connection (13, 14, 15), - determining an available computing capacity of the computing device (Sys1) of the mobile device (10, 20), - determining an available computing capacity of the further computing device (Sys2) via the communication connection (13, 14, 15), - dividing the tracking (T), mappings (M) and / or loop closings (LC) between the computing device (Sys1) of the mobile device (10, 20) and the further computing device (Sys2) depending on the available bandwidth, the available computing capacity of the computing device (Sys1) of the mobile device (10, 20) and the available computing capacity of the further computing device (Sys2) according to a predetermined allocation rule (70) and - Transmission of processing data relating to the tracking (T), mapping (M) and / or loop closing (LC) assigned to the further computing device (Sys2) to the further computing device (Sys2), wherein an information content of the acquired environmental data (SD) is reduced by the computing device (Sys1) before the tracking (T) by means of a filter function (A) depending on the available bandwidth of the communication connection (13, 14, 15) and an information content of the processing data transmitted to the further computing device (Sys2) by the further computing device (Sys2) is reduced by means of a further filter function (B) depending on the available computing capacity of the further computing device (Sys2) before the assigned tracking (T), mapping (M) and / or loop closing (LC) is carried out. [2] Method according to claim 1, wherein a maximum number (n F) of the environmental features determined from the acquired environmental data (SD) is dynamically adapted as a function of the available computing capacity of the computing device (Sys1) of the mobile device (10, 20) and / or the available bandwidth of the communication connection (13, 14, 15) and / or a capture rate of the environmental data (SD) and / or a movement speed of the mobile device (10, 20) according to a predetermined further assignment rule (72). [3] Method according to one of the preceding claims, in which the processing data are compressed before being transmitted to the further computing device (Sys2) and are decompressed after being transmitted from the further computing device (Sys2) before carrying out the allocated tracking (T), mapping (M) and / or loop closing (LC). [4] Method according to one of the preceding claims, in which the further computing device (Sys2) is provided by means of the mobile device (20) or is provided externally by means of a further mobile device (30), a cloud server or an edge cloud server (60). [5] System (50, 51, 52, 53) for locating a mobile device (10, 20), in particular a vehicle, comprising the mobile device (10, 20) and a further computing device (Sys2), wherein the mobile device (10, 20) is designed to carry out a localization in an environment of the mobile device (10, 20) using a map (11) representing the environment by means of simultaneous positioning and mapping (SLAM) and - an environment detection device (12) which is designed to detect environmental data (SD) of the environment, - a computing device (Sys1) designed and configured to locate the mobile device (10, 20) by processing the acquired environmental data (SD), - to determine at least one environmental feature of the environment from the recorded environmental data (SD) in a tracking (T), - in a mapping (M) to provide the map (11) with map data describing the environmental features of the environment represented by the map, and - to determine a position of the mobile device (10, 20) in the environment in a loop closing (LC) by comparing the recorded environmental data (SD) with the map data to compare the respective environmental features, - a communication module for providing a communication connection (13, 14, 15) between the computing device (Sys1) of the mobile device (10, 20) and the further computing device (Sys2) and - has a control device which is designed - to determine an available bandwidth of the communication connection (13, 14, 15), - to determine an available computing capacity of the computing device (Sys1) of the mobile device (10, 20) and - to determine an available computing capacity of the further computing device (Sys2) via the communication connection (13, 14, 15), and - to divide the tracking (T), mapping (M) and / or loop closing (LC) between the computing device (Sys1) of the mobile device (10, 20) and the further computing device (Sys2) depending on the available bandwidth, the available computing capacity of the computing device (Sys1) of the mobile device (10, 20) and the available computing capacity of the further computing device (Sys2) according to a predetermined allocation rule (70) and - to control the communication module for transmitting processing data relating to the tracking (T), mapping (M) and / or loop closing (LC) assigned to the further computing device (Sys2) to the further computing device (Sys2), wherein an information content of the acquired environmental data (SD) is reduced by the computing device (Sys1) before the tracking (T) by means of a filter function (A) depending on the available bandwidth of the communication connection (13, 14, 15) and an information content of the processing data transmitted to the further computing device (Sys2) by the further computing device (Sys2) is reduced by means of a further filter function (B) depending on the available computing capacity of the further computing device (Sys2) before the assigned tracking (T), mapping (M) and / or loop closing (LC) is carried out. [6] System according to claim 5, wherein the further computing device (Sys2) is provided by means of the mobile device (20) or is provided externally by means of a further mobile device (30), in particular a further vehicle, a cloud server or an edge cloud server (60). [7] System according to claim 5 or 6, wherein the mobile device is designed as a vehicle, in particular an autonomously operable vehicle, a mobile robot or a smartphone.

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