WO2023126115A1 - Method and system for navigating mobile logistics robots - Google Patents

Method and system for navigating mobile logistics robots Download PDF

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Publication number
WO2023126115A1
WO2023126115A1 PCT/EP2022/083645 EP2022083645W WO2023126115A1 WO 2023126115 A1 WO2023126115 A1 WO 2023126115A1 EP 2022083645 W EP2022083645 W EP 2022083645W WO 2023126115 A1 WO2023126115 A1 WO 2023126115A1
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Prior art keywords
mobile logistics
logistics robot
map
nodes
topological map
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PCT/EP2022/083645
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German (de)
French (fr)
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Tino Krüger-Basjmeleh
Volker Viereck
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Still Gmbh
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Publication of WO2023126115A1 publication Critical patent/WO2023126115A1/en

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
    • G05D1/0274—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means using mapping information stored in a memory device
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0234—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
    • G05D1/0289—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling with means for avoiding collisions between vehicles

Definitions

  • the invention relates to a method for navigating mobile logistics robots using a map that is created by detecting a working environment of the mobile logistics robot using sensors.
  • the invention also relates to a system for carrying out the method.
  • Mobile robots are increasingly being used in industry and in logistics companies to automate processes in industrial production and for logistical tasks, such as order picking.
  • Mobile robots with arm manipulators, in particular robot arms, are usually used in this case.
  • So-called articulated-arm robots are an example of this.
  • mobile logistics robots in particular autonomous industrial trucks with robot arms for load handling, for example mobile picking robots
  • mobile logistics robots are particularly demanding because logistics robots are to move freely in a logistics area, for example a warehouse.
  • the mobile logistics robots constantly encounter completely new working environments.
  • Localization is a basic requirement for navigating automated vehicles in the intralogistics environment.
  • the basis of the localization is the agreement of an expected value with a sensory perception of the vehicle. If the sensory perception is successfully matched with the expected value, a position of the vehicle can be calculated from this.
  • a distinction is made between relative localization and global localization.
  • a closed or open control circuit calculates suitable target values for driving vehicles on the basis of a target description and the localization and, if necessary, adjusts them.
  • a map containing connection information in the form of obstacles, graphs or routes is often used in addition to the localization. Maps are therefore used to calculate a suitable connection based on connection information in order to connect the current position of the vehicle with the target position.
  • maps Numerous types of maps exist, including, for example, metric, semantic, or topological maps to depict connection information. The effort involved in creating maps varies greatly and requires procedures of varying complexity.
  • metric maps for navigation is now the standard for navigating automatically driving vehicles in the intralogistics environment.
  • the challenge here is that the creation of metric map material either involves high technological risks, such as in the case of self-mapping, or with complex measurements of the movement space, as in particular in the case of third-party mapping.
  • the vehicle With self-mapping, the vehicle creates its own map of the environment through exploration drives.
  • the localization of automatic vehicles indoors is considered to be a challenge, since satellite localization has to be dispensed with for physical reasons.
  • the vehicle In order for the vehicle to create a metric map of its surroundings, it must specifically drive through and map out the unfamiliar areas, such as a warehouse.
  • Sensor inaccuracies, i.e. random errors, and calibration differences, i.e. systematic errors result in different metric maps for each vehicle with integral errors. Vehicles that want to use these maps have to deal with these inaccuracies technologically.
  • Topological maps are a type of map intended to store connection information of movement space.
  • topological maps represent a very simple map type in which the movement space is represented by edges and nodes. The disadvantage of these maps is that they are not suitable for navigation without modifications.
  • metric maps are robot-specific due to odometry errors and deviations in hardware components, e.g. from laser scanners. Providing the robot's own metric map to other mobile robots is difficult because of the resulting differences between the recognized environment and the stored metric map.
  • the present invention is based on the object of designing a method of the type mentioned and a system for carrying out the method in such a way that reliable navigation of the mobile logistics robots is also made possible indoors.
  • this object is achieved according to the invention in that the map is created as an intelligent topological map without using global metric map information, with landmarks in the working environment of the mobile logistics robot, which are uniquely designed via an identification system, being detected by the sensors, by evaluating the Sensor data are recognized as such in a data processing unit and stored as nodes in the topological map.
  • a smart topological map ie an intelligent topological map
  • This smart topological map consists of nodes that describe unique landmarks.
  • Really placed markings are preferably used as landmarks, which are attached to prominent positions in the working environment of the mobile logistics robot, in particular at intersections and/or curves and/or stations and/or elevators and/or gates.
  • the identification system preferably includes numbers and/or letter codes and/or pictograms, which are detected by means of the sensors that are expediently attached to the mobile logistics robot and recognized by evaluating the sensor data in the data processing unit that is expediently also housed in the mobile logistics robot, and for automatic Navigation of the mobile logistics robot can be used in a vehicle control unit.
  • the mobile logistics robot can therefore detect these unique landmarks using sensors, recognize them as such and save them as nodes in the topological map.
  • edges can indicate the direction of movement of the connection of the individual nodes by means of a predecessor/successor principle.
  • these edges which connect the nodes to one another, are stored in the topological map with additional annotations of the edges.
  • edges advantageously contain information about a preferred path between two nodes and/or about a distance between two nodes and/or about a roadway width and/or about roadway obstructions, for example the number of people, oncoming traffic, blockages, and/or about speed limits and/or or about regions with interaction possibilities.
  • the mobile logistics robot navigates along the nodes or the recorded or loaded node network.
  • a possible path for the navigation of the mobile logistics robot is then expediently carried out by determining a valid combination of nodes between a starting point and a destination on the intelligent topological map using the data processing unit.
  • the starting point can be found using vehicle behavior heuristics.
  • a request to the mobile logistics robot can consist of following a route in an obstacle-oriented manner to the next junction.
  • the task of the mobile logistics robot for the movement execution is therefore no longer to navigate a global route, but only to the next junction. All the information required for this is in the annotated edge information of the connection element, i.e. the edge to specific nodes.
  • the navigation of the mobile logistics robot between the nodes is advantageously carried out reactively, with the mobile logistics robot orienting itself to the existing environment by perceiving the environment using the sensors.
  • the mobile logistics robot can derive its driving behavior from the existing environment, be it obstacles, road markings or other features that provide orientation.
  • the mobile logistics robot shares the intelligent topological map that has been created with at least one other mobile logistics robot.
  • the other mobile logistics robot can then compare and supplement the topological map it has received with its own map.
  • an overview of the environment is created in which the connections of the individual landmarks are known.
  • paths and tasks can be planned along these connections of the nodes.
  • the planned paths are then processed along the known landmarks and confirmed by recognizing the landmarks along the way.
  • Local navigation, obstacle detection and avoidance, interaction with objects and stations can be taken over by the on-board sensors and systems and only take place locally.
  • the topological map can be supplemented in an agile manner.
  • other mobile robots are informed directly of the changes and can thus adapt to new situations.
  • At least two mobile logistics robots share information about their planned paths in the intelligent topological map, this information being used in at least one traffic management system to control traffic situations. For example, nodes that will be approached in the future can only be released if they are not occupied by vehicles driving in front.
  • the mobile logistics robot shares the generated intelligent topological map with at least one manually or partially automatically controlled vehicle in order to enable localization of the manually or partially automatically controlled vehicle.
  • the smart topological maps can also be used for manual or semi-automated vehicles and their localization.
  • the invention also relates to a system for carrying out the method with at least one mobile logistics robot with a sensor system for detecting a working environment of the mobile logistics robot and a data processing unit for evaluating the sensor data.
  • the system solves the problem in that landmarks are provided in the working environment of the mobile logistics robot, which are uniquely designed via an identification system and can be detected by the sensors, and the data processing unit is set up to evaluate the sensor data Recognize landmarks as such and save them as nodes in the topological map. 1
  • the identification system expediently includes optical markers, while the sensor system includes at least one optical sensor, in particular a camera, which is preferably attached to the mobile logistics robot and is used for the necessary sensory perception.
  • the identification system includes radio-based transmitters at the landmarks, while the sensor system includes at least one radio-based receiver.
  • the invention enables navigation of automated vehicles without global metric charts.
  • a map of mobile robot workspaces can be shared with other mobile robots. If a mobile robot recognizes changes in the area, other mobile robots learn from it.
  • Multi-storey work areas can be handled easily and without additions using the smart topological map.
  • Automated vehicles are enabled to orient themselves and localize themselves, for example, with elevators in multi-storey warehouses.
  • the localization of mobile robots is no longer dependent on a global or local positioning system such as GPS, Galileo or WLAN.
  • Heuristic algorithms can use the smart topological map to plan paths and tasks.
  • the smart topological map can provide heuristic weighting parameters, such as distance, lane width, frequency of bends, number of people and speed limits. Because the intelligent topological map compactly bundles the nodes and edges, no global, metric occupancy grid maps have to be processed. This leads to a saving in computing time. Through an extended exchange of their planned paths, mobile robots can recognize whether other participants also have a planned path on the edges used and thus recognize upcoming traffic situations and react to them through traffic management.
  • Figure 1 is a landmark in a warehouse from the perspective of a mobile logistics robot
  • FIG. 2 shows the situation from FIG. 1 with the mobile logistics robot from a perspective view from above.
  • FIG. 1 An example of a landmark 2 in a warehouse 5 is shown in FIG. Only one landmark 2 is shown in FIG. 1, but as a rule there are several landmarks 2 in the warehouse 5.
  • the landmarks 2 can vary by an arbitrarily represented unique identifier.
  • the landmarks 2 are actually placed markings that are uniquely designed via an identification system 7, for example numbers, letter codes or pictograms and can be perceived by sensors from the mobile logistics robot 1, which can be seen in the illustration in FIG.
  • the landmark 2 is a sign 6 with unique ArUco markers 3 as machine-readable characters.
  • the landmark 2 also contains a representation 4 for human interaction as a translation of the machine-readable characters.
  • the landmarks 2 are placed in the robot area that can be driven over, ie in the working environment 8 of the mobile logistics robot 1, at prominent positions, for example intersections, curves, stations, elevators, gates.
  • the mobile logistics robot can detect these unique landmarks 2 using its on-board sensors, recognize them as such and save them as nodes in a topological map.
  • a smart topological map ie an intelligent topological map, is used to decouple the global navigation of the mobile logistics robot 1 from the metric environment. This smart topological map consists of nodes formed by the unique landmarks 2 .
  • FIG. 2 shows the situation from FIG. 1 with the mobile logistics robot from a perspective view from above.
  • the mobile logistics robot 1 can also be seen in this representation.
  • several unique landmarks 2 can be seen in the form of signs 6 that are attached to prominent positions in the warehouse 5 .
  • the mobile logistics robot 1 can detect these unique landmarks 2 by sensors, recognize them as such and save them as nodes in the topological map.
  • the navigation of the mobile logistics robot 1 takes place along the nodes that describe the landmarks 2 in the topological map, or the recorded or loaded node network.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Electromagnetism (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

The invention relates to a method for navigating mobile logistics robots (1) by means of a map which is created by detecting a working environment (8) of the mobile logistics robot (1) by means of a sensor system. According to the invention, the map is created as an intelligent topological map without using global metric map information, wherein landmarks (2), which are uniquely designed by an identification system (7), in the working environment (8) of the mobile logistics robot (1) are detected by means of the sensor system, identified as such by analysis of the sensor data in a data processing unit, and stored as nodes in the topological map. The invention also relates to a system for carrying out the method.

Description

Beschreibung Description
Verfahren und System zur Navigation von mobilen Logistik-Robotern Method and system for navigating mobile logistics robots
Die Erfindung betrifft ein Verfahren zur Navigation von mobilen Logistik-Robotern mittels einer Karte, die durch Erfassung einer Arbeitsumgebung des mobilen Logistik- Roboters mittels einer Sensorik erstellt wird. The invention relates to a method for navigating mobile logistics robots using a map that is created by detecting a working environment of the mobile logistics robot using sensors.
Außerdem betrifft die Erfindung ein System zur Durchführung des Verfahrens. The invention also relates to a system for carrying out the method.
Mobile Roboter kommen vermehrt in der Industrie und in Logistikbetrieben zum Einsatz, um Abläufe in der industriellen Fertigung und bei logistischen Aufgaben, beispielsweise bei der Kommissionierung, zu automatisieren. Meist werden dabei mobile Roboter mit Armmanipulatoren, insbesondere Roboterarmen, eingesetzt. Ein Beispiel hierfür sind so genannte Knickarmroboter. Mobile robots are increasingly being used in industry and in logistics companies to automate processes in industrial production and for logistical tasks, such as order picking. Mobile robots with arm manipulators, in particular robot arms, are usually used in this case. So-called articulated-arm robots are an example of this.
Besonders anspruchsvoll ist die Verwirklichung mobiler Logistik-Roboter, insbesondere autonomen Flurförderzeugen mit Roboterarmen zur Lasthandhabung, zum Beispiel mobilen Kommissionierrobotern, weil sich Logistik-Roboterfrei in einem Logistikbereich, zum Beispiel einer Lagerhalle, bewegen sollen. Dabei treffen die mobilen Logistik-Roboter ständig auf völlig neue Arbeitsumgebungen. The realization of mobile logistics robots, in particular autonomous industrial trucks with robot arms for load handling, for example mobile picking robots, is particularly demanding because logistics robots are to move freely in a logistics area, for example a warehouse. The mobile logistics robots constantly encounter completely new working environments.
Für die Navigation von automatisch fahrenden Fahrzeugen im intralogistischen Umfeld ist die Lokalisation eine Grundvoraussetzung. Basis der Lokalisation ist dabei die Übereinbringung eines Erwartungswertes mit einer sensorischen Wahrnehmung des Fahrzeugs. Gelingt die Übereinbringung der sensorischen Wahrnehmung mit dem Erwartungswert, kann daraus eine Position des Fahrzeugs errechnet werden. Dabei unterscheidet man zwischen einer relativen Lokalisation und einer globalen Lokalisation. Localization is a basic requirement for navigating automated vehicles in the intralogistics environment. The basis of the localization is the agreement of an expected value with a sensory perception of the vehicle. If the sensory perception is successfully matched with the expected value, a position of the vehicle can be calculated from this. A distinction is made between relative localization and global localization.
Um automatisch fahrende Fahrzeuge umzusetzen, ist neben der Lokalisation auch eine Fahrzeugführung notwendig, in der ein geschlossener oder offener Regelkreis auf Basis einer Zielbeschreibung und der Lokalisation geeignete Sollwerte für den Antrieb von Fahrzeugen berechnet und gegebenenfalls nachführt. Für eine globale Navigation, also für eine Kombination von Lokalisation und Fahrzeugführung, wird neben der Lokalisation häufig eine Karte verwendet, welche Verbindungsinformationen in Form von Hindernissen, Graphen oder Fahrwegen beinhaltet. Karten dienen also der Berechnung einer geeigneten Verbindung in Abhängigkeit von Verbindungsinformationen, um die aktuelle Position des Fahrzeugs mit der Zielposition zu verbinden. In order to implement automatically driving vehicles, in addition to localization, vehicle guidance is also necessary, in which a closed or open control circuit calculates suitable target values for driving vehicles on the basis of a target description and the localization and, if necessary, adjusts them. For global navigation, ie for a combination of localization and vehicle guidance, a map containing connection information in the form of obstacles, graphs or routes is often used in addition to the localization. Maps are therefore used to calculate a suitable connection based on connection information in order to connect the current position of the vehicle with the target position.
Es existieren zahlreiche Kartenarten, die zum Beispiel metrische, semantische oder topologische Karten umfassen, um Verbindungsinformationen abzubilden. Die Aufwände für die Erstellung von Karten sind dabei sehr unterschiedlich und bedingen unterschiedlich aufwendiger Verfahren. Numerous types of maps exist, including, for example, metric, semantic, or topological maps to depict connection information. The effort involved in creating maps varies greatly and requires procedures of varying complexity.
Die Erstellung von metrischen Karten zur Navigation stellt heute den Standard für die Navigation automatisch fahrender Fahrzeuge im intralogistischen Umfeld dar. Herausforderung dabei ist, dass die Erstellung metrischen Kartenmaterials entweder mit hohen technologischen Risiken, wie insbesondere bei einer Selbstkartierung, oder mit aufwendigen Vermessungen des Bewegungsraums, wie insbesondere bei einer Fremdkartierung, verbunden ist. The creation of metric maps for navigation is now the standard for navigating automatically driving vehicles in the intralogistics environment. The challenge here is that the creation of metric map material either involves high technological risks, such as in the case of self-mapping, or with complex measurements of the movement space, as in particular in the case of third-party mapping.
Bei der Selbstkartierung erstellt das Fahrzeug selbst seine Karte der Umgebung durch Explorationsfahrten. Insbesondere gilt die Lokalisation von automatischen Fahrzeugen im Innenbereich als herausfordernd, da auf eine etwaige Satellitenlokalisation aus physikalischen Gründen verzichtet werden muss. Damit das Fahrzeug eine metrische Karte seiner Umgebung erstellen kann, muss es eigens die unbekannten Bereiche, beispielsweise eines Lagerhauses, befahren und dabei kartieren. Durch Sensorungenauigkeiten, also zufällige Fehler, und Kalibrationsunterschiede, also systematische Fehler, entstehen unterschiedliche metrische Karten für jedes Fahrzeug mit integralen Fehlern. Fahrzeuge, welche diese Karten nutzen wollen, müssen mit diesen Ungenauigkeiten technologisch umgehen. With self-mapping, the vehicle creates its own map of the environment through exploration drives. In particular, the localization of automatic vehicles indoors is considered to be a challenge, since satellite localization has to be dispensed with for physical reasons. In order for the vehicle to create a metric map of its surroundings, it must specifically drive through and map out the unfamiliar areas, such as a warehouse. Sensor inaccuracies, i.e. random errors, and calibration differences, i.e. systematic errors, result in different metric maps for each vehicle with integral errors. Vehicles that want to use these maps have to deal with these inaccuracies technologically.
Karten, die durch Fremdkartierung entstehen, besitzen keine oder nur sehr geringe zufällige und systematische Fehler. Diese sind jedoch bei Umgebungsveränderungen anzupassen, inflexibel und in der Regel teuer. Bei topologische Karten handelt es sich um eine Kartenart, die dafür vorgesehen ist, Verbindungsinformationen des Bewegungsraums abzulegen. Topologische Karten stellen im Unterschied zu metrischen Karten eine sehr einfache Kartenart dar, in der der Bewegungsraum durch Kanten und Knoten dargestellt wird. Nachteilig an diesen Karten ist, dass diese für eine Navigation nicht ohne Veränderungen geeignet sind. Maps created by third-party mapping have no or only very small random and systematic errors. However, these have to be adapted to changes in the environment, are inflexible and usually expensive. Topological maps are a type of map intended to store connection information of movement space. In contrast to metric maps, topological maps represent a very simple map type in which the movement space is represented by edges and nodes. The disadvantage of these maps is that they are not suitable for navigation without modifications.
Die Verwendung von metrischen Karten ist durch Odometriefehler und Abweichungen der Hardwarekomponenten, z.B. von Laserscannern, roboterspezifisch. Das Bereitstellen der robotereigenen metrischen Karte für andere mobile Roboter gestaltet sich, wegen der entstehenden Differenzen der erkannten Umgebung und der gespeicherten metrischen Karte, als schwierig. The use of metric maps is robot-specific due to odometry errors and deviations in hardware components, e.g. from laser scanners. Providing the robot's own metric map to other mobile robots is difficult because of the resulting differences between the recognized environment and the stored metric map.
Der vorliegenden Erfindung liegt die Aufgabe zugrunde, ein Verfahren der genannten Art sowie ein System zur Durchführung des Verfahrens so auszugestalten, dass eine zuverlässige Navigation der mobilen Logistik-Roboter auch im Innenbereich ermöglicht wird. The present invention is based on the object of designing a method of the type mentioned and a system for carrying out the method in such a way that reliable navigation of the mobile logistics robots is also made possible indoors.
Diese Aufgabe wird verfahrensseitig erfindungsgemäß dadurch gelöst, dass die Karte als intelligente topologische Karte ohne Verwendung globaler metrischer Karteninformationen erstellt wird, wobei Landmarken in der Arbeitsumgebung des mobilen Logistik-Roboters, die über ein Identifikationssystem einzigartig gestaltet sind, mittels der Sensorik erfasst, durch Auswertung der Sensordaten in einer Datenverarbeitungseinheit als solche erkannt und als Knoten in der topologischen Karte gespeichert werden. In terms of the method, this object is achieved according to the invention in that the map is created as an intelligent topological map without using global metric map information, with landmarks in the working environment of the mobile logistics robot, which are uniquely designed via an identification system, being detected by the sensors, by evaluating the Sensor data are recognized as such in a data processing unit and stored as nodes in the topological map.
Um die globale Navigation der mobilen Logistik-Roboter von der metrischen Umgebung zu entkoppeln, wird also erfindungsgemäß eine smarte topologische Karte, das heißt eine intelligente topologische Karte, eingeführt. Diese smarte topologische Karte besteht aus Knoten, die einzigartige Landmarken beschreiben. In order to decouple the global navigation of the mobile logistics robots from the metric environment, a smart topological map, ie an intelligent topological map, is introduced according to the invention. This smart topological map consists of nodes that describe unique landmarks.
Vorzugsweise werden als Landmarken real platzierte Markierungen verwendet, die an markanten Positionen in der Arbeitsumgebung des mobilen Logistik-Roboters, insbesondere an Kreuzungen und/oder Kurven und/oder Stationen und/oder Aufzügen und/oder Toren, angebracht werden. Das Identifikationssystem umfasst bevorzugt Zahlen und/oder Buchstabencodes und/oder Piktogramme, die mittels der, zweckmäßigerweise am mobilen Logistik- Roboter angebrachten, Sensorik wahrgenommen und durch Auswertung der Sensordaten in der, zweckmäßigerweise ebenfalls am mobilen Logistik-Roboter untergebrachten, Datenverarbeitungseinheit erkannt und zur automatischen Navigation des mobilen Logistik-Roboters in einer Fahrzeugsteuerungseinheit verwendet werden können. Really placed markings are preferably used as landmarks, which are attached to prominent positions in the working environment of the mobile logistics robot, in particular at intersections and/or curves and/or stations and/or elevators and/or gates. The identification system preferably includes numbers and/or letter codes and/or pictograms, which are detected by means of the sensors that are expediently attached to the mobile logistics robot and recognized by evaluating the sensor data in the data processing unit that is expediently also housed in the mobile logistics robot, and for automatic Navigation of the mobile logistics robot can be used in a vehicle control unit.
Der mobile Logistik-Roboter kann also diese einzigartigen Landmarken sensorisch erfassen, als solche erkennen und als Knoten in der topologischen Karte speichern. The mobile logistics robot can therefore detect these unique landmarks using sensors, recognize them as such and save them as nodes in the topological map.
Die Knoten der topologischen Karte sind durch Kanten miteinander verbunden. Diese Kanten können insbesondere durch ein Vorgänger- / Nachfolger-Prinzip die Bewegungsrichtung der Verbindung der einzelnen Knoten anzeigen. The nodes of the topological map are connected by edges. In particular, these edges can indicate the direction of movement of the connection of the individual nodes by means of a predecessor/successor principle.
Gemäß einer besonders bevorzugten Ausgestaltung der Erfindung werden in der topologischen Karte diese Kanten, die die Knoten miteinander verbinden, mit zusätzlichen Annotationen der Kanten gespeichert. According to a particularly preferred embodiment of the invention, these edges, which connect the nodes to one another, are stored in the topological map with additional annotations of the edges.
Dabei enthalten die Annotationen der Kanten vorteilhafterweise Informationen über einen präferierten Pfad zwischen zwei Knoten und/oder über eine Distanz zwischen zwei Knoten und/oder über eine Fahrbahnbreite und/oder über Fahrbahnbehinderungen, beispielsweise Personenaufkommen, Gegenverkehr, Blockaden, und/oder über Geschwindigkeitsbeschränkungen und/oder über Regionen mit Interaktionsmöglichkeiten. The annotations of the edges advantageously contain information about a preferred path between two nodes and/or about a distance between two nodes and/or about a roadway width and/or about roadway obstructions, for example the number of people, oncoming traffic, blockages, and/or about speed limits and/or or about regions with interaction possibilities.
Die Navigation des mobilen Logistik-Roboters erfolgt entlang der Knoten bzw. des aufgenommen oder geladenen Knotennetzes. Ein möglicher Pfad der Navigation des mobilen Logistik-Roboters wird dann zweckmäßigerweise durch Ermittlung einer gültigen Knotenkombination zwischen einem Startpunkt und einem Zielpunkt auf der intelligenten topologischen Karte mittels der Datenverarbeitungseinheit durchgeführt. Der Startpunkt kann dabei durch Fahrzeugverhaltensheuristiken gefunden werden. Beispielsweise kann eine Aufforderung an den mobilen Logistik-Roboter darin bestehen, einem Fahrweg hindernisorientiert bis zum nächsten Knotenpunkt zu folgen. Aufgabe des mobilen Logistik-Roboters für die Bewegungsausführung ist es daher nicht mehr, auf einer globalen Strecke zu navigieren, sondern nur noch bis zum nächsten Knotenpunkt. Alle dafür notwendigen Informationen befinden sind in den annotierten Kanteninformationen des Verbindungselements, also der Kante zu konkreten Knoten. Diese Informationen sind ebenfalls mit systematischen zufälligen Fehlern versehen, doch sind diese Informationen sehr viel zuverlässiger, da der Bewegungsraum zum nächsten Knoten sehr viel kleiner ist und damit integrale Fehler weniger gewichtig sind. Dadurch, dass die erfindungsgemäße topologische Karte nach der Aufzeichnung völlig von der metrischen Umgebung entkoppelt ist, globale Bezüge jedoch an wichtigen Weggabelungen erstellt und vom mobilen Roboter erkannt werden, kann eine Navigation ohne globale metrische Karte erfolgen, was als wesentliche Neuerung gilt. The mobile logistics robot navigates along the nodes or the recorded or loaded node network. A possible path for the navigation of the mobile logistics robot is then expediently carried out by determining a valid combination of nodes between a starting point and a destination on the intelligent topological map using the data processing unit. The starting point can be found using vehicle behavior heuristics. For example, a request to the mobile logistics robot can consist of following a route in an obstacle-oriented manner to the next junction. The task of the mobile logistics robot for the movement execution is therefore no longer to navigate a global route, but only to the next junction. All the information required for this is in the annotated edge information of the connection element, i.e. the edge to specific nodes. This information is also subject to systematic random errors, but this information is much more reliable because the range of motion to the nearest node is much smaller and integral errors are therefore less important. Because the topological map according to the invention is completely decoupled from the metric environment after recording, but global references are created at important forks in the road and recognized by the mobile robot, navigation can take place without a global metric map, which is considered a significant innovation.
Dabei wird die Navigation des mobilen Logistik-Roboters zwischen den Knotenpunkten vorteilhafterweise reaktiv durchgeführt, wobei sich der mobile Logistik-Roboter durch Umgebungswahrnehmung mittels der Sensorik an der vorhandenen Umgebung orientiert. Hierbei kann der mobile Logistik-Roboter sein Fahrverhalten an der vorhandenen Umgebung ableiten, seien dies Hindernisse, Fahrbahnmarkierungen oder andere Orientierung gebende Merkmale. In this case, the navigation of the mobile logistics robot between the nodes is advantageously carried out reactively, with the mobile logistics robot orienting itself to the existing environment by perceiving the environment using the sensors. The mobile logistics robot can derive its driving behavior from the existing environment, be it obstacles, road markings or other features that provide orientation.
Gemäß einer bevorzugten Weiterbildung des Erfindungsgedankens ist vorgesehen, dass der mobile Logistik-Roboter die erstellte intelligente topologische Karte mit mindestens einem weiteren mobilen Logistik-Roboter teilt. Der weitere mobile Logistik- Roboter kann dann die erhaltene topologische Karte mit der eigenen Karte vergleichen und ergänzen. So wird eine Übersicht der Umgebung erstellt, in der die Verbindungen der einzelnen Landmarken bekannt sind. Mit der smarten topologischen Karte können Pfade und Aufgaben entlang dieser Verbindungen der Knotenpunkte geplant werden. Die geplanten Pfade werden dann entlang der bekannten Landmarken abgearbeitet und durch eine Wiedererkennung der Landmarken entlang des Weges bestätigt. According to a preferred development of the idea of the invention, it is provided that the mobile logistics robot shares the intelligent topological map that has been created with at least one other mobile logistics robot. The other mobile logistics robot can then compare and supplement the topological map it has received with its own map. In this way, an overview of the environment is created in which the connections of the individual landmarks are known. With the smart topological map, paths and tasks can be planned along these connections of the nodes. The planned paths are then processed along the known landmarks and confirmed by recognizing the landmarks along the way.
Lokale Navigation, Hinderniserkennung und Hindernisumfahrung, Interaktion mit Objekten und Stationen können durch die bordeigenen Sensoren und Systeme übernommen werden und finden nur lokal statt. Local navigation, obstacle detection and avoidance, interaction with objects and stations can be taken over by the on-board sensors and systems and only take place locally.
Sollten sich Pfade ändern, zum Beispiel durch eine dauerhafte Blockade von einer Verbindung zweier Knoten, das Entfernen oder Hinzufügen von Knoten etc., kann die topologische Karte agil ergänzt werden. Durch das Teilen der smarten topologischen Karte werden andere mobile Roboter direkt von den Änderungen informiert und können sich so neuen Situationen anpassen. If paths change, for example due to a permanent blockage of a connection between two nodes, the removal or addition of nodes, etc., the topological map can be supplemented in an agile manner. By sharing the smart topological map, other mobile robots are informed directly of the changes and can thus adapt to new situations.
In einer weiteren vorteilhaften Ausgestaltung der Erfindung teilen mindestens zwei mobile Logistik-Roboter Informationen über ihre geplanten Pfade in der intelligenten topologischen Karte, wobei diese Informationen in mindestens einem Verkehrsmanagementsystem zur Steuerung von Verkehrssituationen verwendet werden. So können zum Beispiel Knoten, die zukünftig angefahren werden, nur freigegeben werden, wenn diese nicht durch vorausfahrende Fahrzeuge belegt sind. In a further advantageous embodiment of the invention, at least two mobile logistics robots share information about their planned paths in the intelligent topological map, this information being used in at least one traffic management system to control traffic situations. For example, nodes that will be approached in the future can only be released if they are not occupied by vehicles driving in front.
Eine andere Weiterbildung der Erfindung sieht vor, dass der mobile Logistik-Roboter die erstellte intelligente topologische Karte mit mindestens einem manuell oder teilautomatisiert gesteuerten Fahrzeug teilt, um eine Lokalisierung des manuell oder teilautomatisiert gesteuerten Fahrzeugs zu ermöglichen. Auf diese Weise können die smarten topologischen Karten auch für manuelle oder teilautomatisierte Fahrzeuge und deren Lokalisation genutzt werden. Another development of the invention provides that the mobile logistics robot shares the generated intelligent topological map with at least one manually or partially automatically controlled vehicle in order to enable localization of the manually or partially automatically controlled vehicle. In this way, the smart topological maps can also be used for manual or semi-automated vehicles and their localization.
In einer weiteren Ausgestaltung ist es möglich, eine Aufgabenplanung auf Basis der smarten topologischen Karte zu erzeugen, so dass die Fahrzeuge Abarbeitungshierarchien erzeugen, welche für individuelle Transporte genutzt werden können. In a further refinement, it is possible to generate task planning based on the smart topological map, so that the vehicles generate processing hierarchies which can be used for individual transports.
Die Erfindung betrifft ferner ein System zur Durchführung des Verfahrens mit mindestens einem mobilen Logistik-Roboter mit einer Sensorik zur Erfassung einer Arbeitsumgebung des mobilen Logistik-Roboters und einer Datenverarbeitungseinheit zur Auswertung der Sensordaten. The invention also relates to a system for carrying out the method with at least one mobile logistics robot with a sensor system for detecting a working environment of the mobile logistics robot and a data processing unit for evaluating the sensor data.
Bei dem System wird die gestellte Aufgabe dadurch gelöst, dass Landmarken in der Arbeitsumgebung des mobilen Logistik-Roboters vorgesehen sind, die über ein Identifikationssystem einzigartig gestaltet sind und mittels der Sensorik erfasst werden können, und die Datenverarbeitungseinheit dafür eingerichtet ist, durch Auswertung der Sensordaten die Landmarken als solche zu erkennen und als Knoten in der topologischen Karte zu speichern. 1 The system solves the problem in that landmarks are provided in the working environment of the mobile logistics robot, which are uniquely designed via an identification system and can be detected by the sensors, and the data processing unit is set up to evaluate the sensor data Recognize landmarks as such and save them as nodes in the topological map. 1
Zweckmäßigerweise umfasst das Identifikationssystem optische Marker, während die Sensorik mindestens einen optischen Sensor, insbesondere eine Kamera, umfasst, welche vorzugsweise am mobilen Logistik-Roboter angebracht ist und zur notwendigen sensorischen Wahrnehmung dient. The identification system expediently includes optical markers, while the sensor system includes at least one optical sensor, in particular a camera, which is preferably attached to the mobile logistics robot and is used for the necessary sensory perception.
Grundsätzlich ist eine radiobasierte Knotenerkennung ebenso denkbar. In diesem Fall umfasst das Identifikationssystem radiobasierte Sender an den Landmarken, während die Sensorik mindestens einen radiobasierten Empfänger umfasst. In principle, radio-based node detection is also conceivable. In this case, the identification system includes radio-based transmitters at the landmarks, while the sensor system includes at least one radio-based receiver.
Die Erfindung bietet eine ganze Reihe von Vorteilen: The invention offers a whole range of advantages:
Mit der Erfindung wird eine Navigation von automatischen Fahrzeugen ohne globale metrische Karten ermöglicht. The invention enables navigation of automated vehicles without global metric charts.
Eine Karte des Arbeitsbereiches von mobilen Robotern kann mit anderen mobilen Robotern geteilt werden. Erkennt ein mobiler Roboter Veränderungen in dem Gebiet, lernen andere mobile Roboter davon. A map of mobile robot workspaces can be shared with other mobile robots. If a mobile robot recognizes changes in the area, other mobile robots learn from it.
Mehrstöckige Arbeitsbereiche können durch die smarte topologische Karte einfach und ohne Ergänzung gehandhabt werden. Es wird automatischen Fahrzeugen ermöglicht, sich beispielsweise mit Aufzügen in mehrstöckigen Warenhäusern zu orientieren und zu lokalisieren. Multi-storey work areas can be handled easily and without additions using the smart topological map. Automated vehicles are enabled to orient themselves and localize themselves, for example, with elevators in multi-storey warehouses.
Die Lokalisation von mobilen Robotern ist nicht mehr von einem globalen oder lokalen Ortungssystem, wie zum Beispiel GPS, Galileo oder WLAN, abhängig. The localization of mobile robots is no longer dependent on a global or local positioning system such as GPS, Galileo or WLAN.
Heuristische Algorithmen können mit der smarten topologischen Karte Pfade und Aufgaben planen. Die smarte topologische Karte kann hierfür heuristische Gewichtungsparameter, zum Beispiel Distanz, Fahrbahnbreite, Kurvenhäufigkeit, Personenaufkommen und Geschwindigkeitsbegrenzungen, zur Verfügung stellen. Dadurch, dass die intelligente topologische Karte kompakt die Knoten und Kanten bündelt, müssen keine globalen, metrischen occupancy grid maps verarbeitet werden. Dies führt zu einer Rechenzeitersparnis. Mobile Roboter können durch einen erweiterten Austausch ihrer geplanten Pfade erkennen, ob andere Teilnehmer ebenfalls einen geplanten Pfad auf den verwendeten Kanten haben und so aufkommende Verkehrssituationen erkennen und durch ein Verkehrsmanagement darauf reagieren. Heuristic algorithms can use the smart topological map to plan paths and tasks. For this purpose, the smart topological map can provide heuristic weighting parameters, such as distance, lane width, frequency of bends, number of people and speed limits. Because the intelligent topological map compactly bundles the nodes and edges, no global, metric occupancy grid maps have to be processed. This leads to a saving in computing time. Through an extended exchange of their planned paths, mobile robots can recognize whether other participants also have a planned path on the edges used and thus recognize upcoming traffic situations and react to them through traffic management.
Weitere Vorteile und Einzelheiten der Erfindung werden anhand der in den schematischen Figuren dargestellten Ausführungsbeispiele näher erläutert. Hierbei zeigen Further advantages and details of the invention are explained in more detail with reference to the exemplary embodiments illustrated in the schematic figures. show here
Figur 1 eine Landmarke in einem Lagerhaus aus Sicht eines mobilen Logistik- Roboters und Figure 1 is a landmark in a warehouse from the perspective of a mobile logistics robot and
Figur 2 die Situation aus Figur 1 mit dem mobilen Logistik-Roboter aus einer perspektivischen Sicht von oben. FIG. 2 shows the situation from FIG. 1 with the mobile logistics robot from a perspective view from above.
In Figur 1 ist ein Beispiel einer Landmarke 2 in einem Lagerhaus 5 dargestellt. In der Figur 1 ist lediglich eine Landmarke 2 gezeigt, in der Regel befinden sich aber mehrere Landmarken 2 in der Lagerhalle 5. Die Landmarken 2 können durch eine beliebig dargestellte eineindeutige Kennung variieren. An example of a landmark 2 in a warehouse 5 is shown in FIG. Only one landmark 2 is shown in FIG. 1, but as a rule there are several landmarks 2 in the warehouse 5. The landmarks 2 can vary by an arbitrarily represented unique identifier.
Die Landmarken 2 sind real platzierte Markierungen, die über ein Identifikationssystem 7, zum Beispiel Zahlen, Buchstabencodes oder Piktogramme, einzigartig gestaltet sind und sensorisch vom mobilen Logistik-Roboter 1 , der in der Darstellung der Figur 2 zu sehen ist, wahrgenommen werden können. Im gezeigten Fall handelt es sich bei der Landmarke 2 um ein Schild 6 mit eineindeutigen ArUco-Markern 3 als maschinenlesbare Zeichen. Die Landmarke 2 enthält zusätzlich als Übersetzung der maschinenlesbaren Zeichen eine Darstellung 4 für menschliche Interaktion. The landmarks 2 are actually placed markings that are uniquely designed via an identification system 7, for example numbers, letter codes or pictograms and can be perceived by sensors from the mobile logistics robot 1, which can be seen in the illustration in FIG. In the case shown, the landmark 2 is a sign 6 with unique ArUco markers 3 as machine-readable characters. The landmark 2 also contains a representation 4 for human interaction as a translation of the machine-readable characters.
Die Landmarken 2 werden im befahrbaren Robotergebiet, also in der Arbeitsumgebung 8 des mobilen Logistik-Roboters 1 , an markanten Positionen, zum Beispiel Kreuzungen, Kurven, Stationen, Aufzügen, Toren, angebracht. Diese einzigartigen Landmarken 2 kann der mobile Logistik-Roboter mittels seiner fahrzeugeigenen Sensorik sensorisch erfassen, als solche erkennen und als Knoten in einer topologischen Karte speichern. Um die globale Navigation des mobilen Logistik-Roboters 1 von der metrischen Umgebung zu entkoppeln, wird eine smarte topologische Karte, also eine intelligente topologische Karte, verwendet. Diese smarte topologische Karte besteht aus Knoten, die von den einzigartigen Landmarken 2 gebildet sind. The landmarks 2 are placed in the robot area that can be driven over, ie in the working environment 8 of the mobile logistics robot 1, at prominent positions, for example intersections, curves, stations, elevators, gates. The mobile logistics robot can detect these unique landmarks 2 using its on-board sensors, recognize them as such and save them as nodes in a topological map. A smart topological map, ie an intelligent topological map, is used to decouple the global navigation of the mobile logistics robot 1 from the metric environment. This smart topological map consists of nodes formed by the unique landmarks 2 .
Die Figur 2 zeigt die Situation aus Figur 1 mit dem mobilen Logistik-Roboter aus einer perspektivischen Sicht von oben. In dieser Darstellung ist auch der mobile Logistik- Roboter 1 zu sehen. Weiterhin sind mehrere einzigartige Landmarken 2 in Form von Schildern 6 zu erkennen, die an markanten Positionen in der Lagerhalle 5 angebracht sind. Diese einzigartigen Landmarken 2 kann der mobile Logistik-Roboter 1 sensorisch erfassen, als solche erkennen und als Knoten in der topologischen Karte speichern. Die Navigation des mobilen Logistik-Roboters 1 erfolgt entlang der Knoten, die die Landmarken 2 in der topologischen Karte beschreiben, beziehungsweise des aufgenommen oder geladenen Knotennetzes. FIG. 2 shows the situation from FIG. 1 with the mobile logistics robot from a perspective view from above. The mobile logistics robot 1 can also be seen in this representation. Furthermore, several unique landmarks 2 can be seen in the form of signs 6 that are attached to prominent positions in the warehouse 5 . The mobile logistics robot 1 can detect these unique landmarks 2 by sensors, recognize them as such and save them as nodes in the topological map. The navigation of the mobile logistics robot 1 takes place along the nodes that describe the landmarks 2 in the topological map, or the recorded or loaded node network.

Claims

Patentansprüche Verfahren zur Navigation von mobilen Logistik-Robotern (1 ) mittels einer Karte, die durch Erfassung einer Arbeitsumgebung (8) des mobilen Logistik-Roboters (1) mittels einer Sensorik erstellt wird, dadurch gekennzeichnet, dass die Karte als intelligente topologische Karte ohne Verwendung globaler metrischer Karteninformationen erstellt wird, wobei Landmarken (2) in der Arbeitsumgebung (8) des mobilen Logistik-Roboters (1), die über ein Identifikationssystem (7) einzigartig gestaltet sind, mittels der Sensorik erfasst, durch Auswertung der Sensordaten in einer Datenverarbeitungseinheit als solche erkannt und als Knoten in der topologischen Karte gespeichert werden. Verfahren nach Anspruch 1, dadurch gekennzeichnet, dass als Landmarken (2) real platzierte Markierungen verwendet werden, die an markanten Positionen in der Arbeitsumgebung (8) des mobilen Logistik-Roboters (1), insbesondere an Kreuzungen und/oder Kurven und/oder Stationen und/oder Aufzügen und/oder Toren, angebracht werden. Verfahren nach Anspruch 1 oder 2, dadurch gekennzeichnet, dass das Identifikationssystem (7) Zahlen und/oder Buchstabencodes und/oder Piktogramme umfasst. Verfahren nach einem der Ansprüche 1 bis 3, dadurch gekennzeichnet, dass in der topologischen Karte Kanten, die die Knoten miteinander verbinden, mit zusätzlichen Annotationen der Kanten gespeichert werden. Verfahren nach Anspruch 4, dadurch gekennzeichnet, dass die Annotationen der Kanten Informationen über einen präferierten Pfad zwischen zwei Knoten und/oder über eine Distanz zwischen zwei Knoten und/oder über eine Fahrbahnbreite und/oder über Fahrbahnbehinderungen und/oder über Geschwindigkeitsbeschränkungen und/oder über Regionen mit Interaktionsmöglichkeiten enthalten. Verfahren nach einem der Ansprüche 1 bis 5, dadurch gekennzeichnet, dass die Navigation des mobilen Logistik-Roboters (1 ) durch Ermittlung einer gültigen Knotenkombination zwischen einem Startpunkt und einem Zielpunkt auf der intelligenten topologischen Karte mittels der Datenverarbeitungseinheit durchgeführt wird. Verfahren nach einem der Ansprüche 1 bis 6, dadurch gekennzeichnet, dass die Navigation des mobilen Logistik-Roboters (1 ) zwischen den Knotenpunkten reaktiv durchgeführt wird, wobei sich der mobile Logistik-Roboter (1 ) durch Umgebungswahrnehmung mittels der Sensorik orientiert. Verfahren nach einem der Ansprüche 1 bis 7, dadurch gekennzeichnet, dass der mobile Logistik-Roboter (1 ) die erstellte intelligente topologische Karte mit mindestens einem weiteren mobilen Logistik-Roboter (1 ) teilt. Verfahren nach einem der Ansprüche 1 bis 8, dadurch gekennzeichnet, dass mindestens zwei mobile Logistik-Roboter (1 ) Informationen über ihre geplanten Pfade in der intelligenten topologischen Karte teilen, wobei diese Informationen in mindestens einem Verkehrsmanagementsystem zur Steuerung von Verkehrssituationen verwendet werden. Verfahren nach einem der Ansprüche 1 bis 9, dadurch gekennzeichnet, dass der mobile Logistik-Roboter (1 ) die erstellte intelligente topologische Karte mit mindestens einem manuell oder teilautomatisiert gesteuerten Fahrzeug teilt, um eine Lokalisierung des manuell oder teilautomatisiert gesteuerten Fahrzeugs zu ermöglichen. System zur Durchführung des Verfahrens nach einem der Ansprüche 1 bis 10 mit mindestens einem mobilen Logistik-Roboter (1 ) mit einer Sensorik zur Erfassung einer Arbeitsumgebung des mobilen Logistik-Roboters (1 ) und einer Datenverarbeitungseinheit zur Auswertung der Sensordaten, dadurch gekennzeichnet, dass Landmarken (2) in der Arbeitsumgebung (8) des mobilen Logistik-Roboters (1 ) vorgesehen sind, die über ein Identifikationssystem (7) einzigartig gestaltet sind und mittels der Sensorik erfasst werden können, und die Datenverarbeitungseinheit dafür eingerichtet ist, durch Auswertung der Sensordaten die Landmarken (2) als solche zu erkennen und als Knoten in der topologischen Karte zu speichern. System nach Anspruch 11 , dadurch gekennzeichnet, dass das Identifikationssystem (7) optische Marker umfasst und die Sensorik mindestens einen optischen Sensor, insbesondere eine Kamera, umfasst. System nach Anspruch 11 oder 12, dadurch gekennzeichnet, dass das Identifikationssystem (7) radiobasierte Sender umfasst und die Sensorik mindestens einen radiobasierten Empfänger umfasst. Claims Method for navigating mobile logistics robots (1) using a map that is created by detecting a working environment (8) of the mobile logistics robot (1) using sensors, characterized in that the map is used as an intelligent topological map without use global metric map information is created, with landmarks (2) in the working environment (8) of the mobile logistics robot (1), which are uniquely designed via an identification system (7), being recorded by means of the sensors, by evaluating the sensor data in a data processing unit as such are recognized and stored as nodes in the topological map. Method according to Claim 1, characterized in that markings that are actually placed are used as landmarks (2) at prominent positions in the working environment (8) of the mobile logistics robot (1), in particular at intersections and/or curves and/or stations and/or elevators and/or gates. Method according to Claim 1 or 2, characterized in that the identification system (7) comprises numerical and/or letter codes and/or pictograms. Method according to one of Claims 1 to 3, characterized in that edges which connect the nodes to one another are stored in the topological map with additional annotations of the edges. Method according to claim 4, characterized in that the annotations of the edges information about a preferred path between two nodes and / or a distance between two nodes and / or a lane width and / or lane obstructions and / or speed restrictions and / or Interaction regions included. Method according to one of claims 1 to 5, characterized in that the navigation of the mobile logistics robot (1) is performed by determining a valid combination of nodes between a starting point and a destination on the intelligent topological map using the data processing unit. The method according to any one of claims 1 to 6, characterized in that the navigation of the mobile logistics robot (1) is carried out reactively between the nodes, wherein the mobile logistics robot (1) orients itself by perceiving the environment using the sensors. The method according to any one of claims 1 to 7, characterized in that the mobile logistics robot (1) shares the intelligent topological map created with at least one other mobile logistics robot (1). Method according to one of Claims 1 to 8, characterized in that at least two mobile logistics robots (1) share information about their planned paths in the intelligent topological map, this information being used in at least one traffic management system for controlling traffic situations. Method according to one of claims 1 to 9, characterized in that the mobile logistics robot (1) shares the generated intelligent topological map with at least one manually or partially automatically controlled vehicle in order to enable localization of the manually or partially automatically controlled vehicle. System for performing the method according to any one of claims 1 to 10 with at least one mobile logistics robot (1) with a sensor system for detecting a working environment of the mobile logistics robot (1) and a data processing unit for evaluating the sensor data, characterized in that landmarks (2) are provided in the working environment (8) of the mobile logistics robot (1), which are uniquely designed via an identification system (7) and can be detected by the sensors, and the data processing unit is set up for this purpose by evaluating the Sensor data to recognize the landmarks (2) as such and to store them as nodes in the topological map. System according to claim 11, characterized in that the identification system (7) comprises optical markers and the sensor system comprises at least one optical sensor, in particular a camera. System according to Claim 11 or 12, characterized in that the identification system (7) comprises radio-based transmitters and the sensor system comprises at least one radio-based receiver.
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