A computer-implemented method for operating multiple mobile agents in an environment having improved scalability

Abstract

A computer-implemented method with increased scalability for operating a plurality of mobile agents that are in communication via a communication topology and move in an environment, the environment c

Description

TECHNICAL FIELD The invention relates to multi-robot task allocation, specifically multi-vehicle task allocation. BACKGROUND W. Chen and Y.-Y. Chen, “Finite-Time Coordinated Path Following Control of Leader-Following Multi-Agent Systems”, preprint available from https: / / doi.Org / 10.21203 / rs.3.rs-560294 / v1 discloses a continuous feedback method to achieve both path following and a formation moving along desired orbits at a finite time is presented. It is assumed that the topology among the virtual leader and the followers is directed. An additional condition of so called barrier function to yield all the agents moving within a limited area is designed. A continuous finite-time path following control law is first designed based on the barrier function and backstepping. Then a continuous finite-time formation algorithm is designed by regarding the path following errors as disturbances. G. Russo and M. di Bernardo, “Solving the rendezvous problem for multi-agent systems using contraction theory”, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, Shanghai, China, 2009, pp. 5821-5826, doi: 10.1109 / CDC.2009.5400731, discloses a strategy based on the use of contraction theory to coordinate motion in multiagent systems. Two possible solutions to the rendezvous problem are presented in planar roving agents by means of both linear and nonlinear communication protocols. US 9 469 476 B1 discloses a method for dynamically configuring a delivery system for delivering products to smart mats. A delivery coordination server determines a location of multiple smart mats. Each of the smart mats includes a positioning system and a transmitter that transmits a message describing the real-time geophysical location of the smart mats. The delivery coordination server receives a message describing a location of a first delivery vehicle that is transporting a first package addressed for delivery to a first smart mat. The delivery coordination server determines that the first smart mat has moved to a location that is within a predetermined distance of a second smart mat, to which a second delivery vehicle is scheduled to deliver a second package. The delivery coordination server directs the first delivery vehicle to transfer the first package to the second delivery vehicle for delivery to the first smart mat. US 11 157 866 B2 discloses a method for intelligent package delivery. The method comprises obtaining order information for a plurality of package delivery orders, wherein the order information includes one or more package pickup stops and one or more package drop off stops; and determining one or more optimized package delivery route for one more vehicle using the order information, wherein an optimized package delivery route of the one or more optimized package delivery route includes a first stop associated to a first order of the plurality of package delivery orders and a second stop associated to a second order of the plurality of package delivery orders. Unpublished German patent application 10 2023 111 100.0 discloses a distributed approach for a group of robots to determine a coalition that is best suitable for solving a given task. The distributed approach allows for a better fault tolerance, resilience, and scalability. By using a breadth-first search approach, the coalition formation problem can be solved with improved optimality. In general, the coalitions determined with this approach are better suited to solve the assigned task compared to other coalition formation approaches. Unpublished German patent application 10 2023 111 099.3 discloses a method where a group of robots can be formed into a coalition for performing a task. The whole group of robots can be partitioned so as to have all robots performing tasks. However, it is not that easy to find a partition that assigns the tasks such that the coalition best suited for performing the task actually does it. With this idea the coalitions are improved by transforming the coalitions by adding or removing robots, e.g., by splitting or merging coalitions or by swapping individual robots between coalitions. The resulting coalitions are then better suited to perform the task compared to untransformed coalitions. In other words, the transformed coalitions have the largest possible utility value for performing the task under the circumstances. Unpublished German patent application 10 2023 116 197.0 discloses a method to coordinate multiple mobile agents, such as mobile robots or vehicles, to collectively perform a task that could not be performed by a single mobile agent alone. For example, multiple mobile robots could be needed to have enough weight capacity to carry a certain package. In case of passengers, it may be necessary to pick up more than a single vehicle can carry. The preset-time and the control commands allow for multiple mobile agents to arrive more or less simultaneously at their starting location and destination. It is possible to simultaneously form multiple groups of mobile agents that are going to perform their tasks. As a result, the overall capacity and functionality of a system having multiple mobile agents can be improved. SUMMARY OF THE INVENTION It is the object of the invention to improve scalability of dial-a-ride systems. The object is achieved by the subject-matter of the independent claims. Preferred embodiments are subject-matter of the dependent claims. The invention provides a computer-implemented method for operating a plurality of mobile agents that are in communication via a communication topology and move in an environment, the environment comprising a set of depots, a set of pick-up locations, and a set of drop-off locations, wherein the method comprises: a) generating transport information that is indicative of any of a number of mobile agents, a pick-up location, a drop-off location, and at least one preset-time, wherein each mobile agent is associated with a depot, wherein the preset-time is indicative of the maximum time period in which the number of mobile agents has to complete a movement phase; b) at least one movement phase including, for each of the number of mobile agents, generating a control command based on the transport information, wherein the control command causes the respective mobile agent to move from a starting location to a destination in accordance with the transport information; wherein each control command is generated such that the respective mobile agent arrives at its destination within the preset-time, wherein in response to receiving a transport request at least one mobile agent is joined with and / or removed from the communication topology to generate an updated communication topology, wherein the control command is generated based on the updated communication topology and the preset-time. With this approach it is possible to coordinate multiple mobile agents, such as mobile robots or vehicles, to collectively perform a task that could not be performed by a single mobile agent alone. For example, multiple mobile robots could be needed to have enough weight capacity to carry a certain package. In case of passengers, it may be necessary to pick up more than a single vehicle can carry. The preset-time and the control commands allow for multiple mobile agents to arrive more or less simultaneously at their starting location and destination. It is possible to simultaneously form multiple groups of mobile agents that are going to perform their tasks. During the movement phase it is possible to add or remove agents from the communication topology or network. Consequently, the system can be flexibly scaled up or down as the transport demand increases or decreases. Preferably, in step b) the control command is generated such that, after the collective arrival of the mobile agents at the destination, the mobile agents perform a task. The task performance may be automated or contingent on human interaction. For example, the mobile agents may pick up a package. In case of passengers, the mobile agents may wait for the passengers to board the vehicle. Preferably, wherein in step b) a first movement phase is an active phase that includes, for each of the number of mobile agents, generating a control command based on the transport information, wherein the control command causes the respective mobile agent to move from its depot as the starting location to a pick-up location in accordance with the transport information, wherein each control command is generated such that the respective mobile agent arrives at the pick-up location within the preset-time. With this approach delays in the system can be reduced, since the mobile agents can arrive (nearly) simultaneously at the pickup location in a coordinated manner in order to be able to pick up the package or passengers. Preferably, in the active phase, the transport request causes at least one mobile agent to join and / or being removed from the communication topology. The change in communication topology allows the addition or removal of mobile agents pursuant to the current demand in the dial-a-ride-application. Preferably, in step b) a second movement phase is a handshake phase that includes, for each of the number of mobile agents, generating a control command based on the transport information, wherein the control command causes the respective mobile agent to move from a pick-up location to a drop-off location in accordance with the transport information, wherein each control command is generated such that the respective mobile agent arrives at the pick-up location within the preset-time. With this approach the actual task is completed within a given time-window and reduced delays, since the resources provided by the mobile agents can be used in a more time efficient manner. Preferably, in the handshake phase, the transport request causes at least one mobile agent to be removed from the communication topology or no change to the communication topology. With the possibility of removing superfluous mobile agents, transport resources can be better used and the overall performance of the system may increase. Preferably, wherein in step b) a third movement phase is a bye-bye phase that includes, for each of the number of mobile agents, generating a control command based on the transport information, wherein the control command causes the respective mobile agent to move from a drop-off location back to its depot, wherein each control command is generated such that the respective mobile agent arrives at its depot within the preset-time. With this approach a more efficient flow of packages or passengers can be achieved since as soon as the task is completed, the mobile agents clear the environment and get ready for the next mission. Preferably, the control command is generated such that, after the collective arrival of the mobile agents at the pickup location, the mobile agents collectively pick up a package or a passenger. Preferably, the control command is generated such that, after the collective arrival of the mobile agents at the pickup location, the mobile agents collectively transport a package or a passenger to the drop off location. Preferably, the control command is generated such that, after the collective arrival of the mobile agents at the drop off location, the mobile agents collectively drop off a package or a passenger and the mobile agents return to their respective depots. Coordinated movement, pickup and drop off procedures as well as return to the depots improves the performance of the overall system. Preferably, the mission information includes a single preset-time for all movement phases or an individual preset-time for each movement phase. With this approach the preset-time can be adapted more flexibly to the tasks or environmental situation, e.g., traffic distance between waypoints, etc. Preferably, the number of mobile agents includes a leader agent, and for all remaining mobile agents, a proportional delay factor is determined such that the travel times of the leader agent and the remaining mobile agents from the starting location to the destination within the respective phase are identical. With this approach the actions of the mobile agents are adapted to a single mobile agent. A more coordinated performance of the tasks and phases is expected. Preferably, the control commands are generated to coordinate the mobile agents by determining, for each mobile agent, a normalized acceleration based on arrival times of neighboring mobile agents and an auxiliary function that depends on the presettime. By controlling the acceleration of each mobile agent, and thereby its current velocity and position, each group of mobile agents can be coordinated to arrive at the same time at its destination. Preferably, the normalized acceleration is determined according to Vs^f) C ^sp where vs^pi(t) designates the acceleration between starting location s and destination p for mobile agent number i at time t, Csp designates the euclidean distance between starting location s and destination p, (p(t) designates the auxiliary function and <p(t) its derivative with respect to time t, S;(t) designates a correction that depends on neighboring mobile agents, and y and e are tuning parameters. With this equation for the acceleration, the coordination between the mobile agents is improved. Preferably, the auxiliary function is chosen as {•pa (y _ yja ’ 0 <t <T 1, t >T where parameter a >2 is a free parameter. With this auxiliary function, it can be assured that all requests regarding pickup and drop off locations can be respected within the given time window T. Preferably, the correction is chosen as (0 — / ciij 8j „ 8[ „ ^hp ^sp where nonzero at denotes a weighted gain and Xt designates the set of neighboring agents such that >0. With this correction, only neighboring mobile agents influence each other. Preferably, the neighboring agents are chosen such that their communication graph forms a directed spanning tree. The invention provides a mobile robot, a vehicle or a data processing apparatus comprising means for carrying out the previously described method. The invention provides a computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the previously described method. The invention provides a computer-readable medium or a data carrier signal comprising the computer program. It is an idea to propose a multi-vehicle-based scalability method for dial-a-ride applications where transportation requests may be removed or joined at almost any time. Compared to most of the existing methods, the proposed method assures prespecified task achievement while permitting vehicles to be deleted or added, thus solving the scalability issue that remains a challenge in the multi-vehicle field. For dial-a-ride applications, vehicles generally start from original depots to arrive at pick-up points. Subsequently, the vehicles proceed to drop-off points (destinations) to drop off cargo or passengers. Eventually, the vehicles return to depots (not necessarily the original ones). For such applications, transportation requests may be deleted or added from time to time. The transportation requests may be generated by another system that organizes logistics or can be generated by users that request transport via an app, for example. Another idea is devoted to the dial-a-ride problem where transportation tasks can be completed, despite of the presence of task removing or task adding. It proposes a multi-vehicle-based scalability method for dial-a-ride applications, by which transportation requests can be cooperatively achieved while allowing task removing or adding at any operational time. In some embodiments, the system comprises a network of interacting robots / vehicles among which robots / vehicles can be removed from or added to the network at any time. Specifically, such a model can be specified by a fleet of interacting vehicles whose number is time-dependent. The goal of the multi-vehicle-based scalability method is to ensure that despite the presence of vehicle removing / adding, all specified transportation requests can be cooperatively completed. In some embodiments a group of vehicles, each of them preferably allocated by a transportation request, can be used to complete transportation missions at which transportation requests may be deleted or added at any time. The objective is to devise a multi-vehicle-based scalability method such that a vehicle joining and removing is permissible at any time; all transportation requests (i.e., cooperatively arriving at the pickup and drop-off points, and returning to the depots) can be cooperatively assured. For a dial-a-ride application, the method can have a three-phase configuration. An active phase that involves the movement from the depot to the pick-up point (short: depot to pick-up, D2P); a handshake phase that involves the movement from the pick-up point to the drop-off point (short: pick-up to drop-off, P2D); and a bye-bye phase that involves movement from the drop-off point to the (not necessarily the same) depot (short: drop-off point to depot, D2D). The multi-vehicle-based scalability method is used to handle the task deleting and adding that may arise in the D2P and P2D phases. In some embodiments the input includes locations of original and / or final depots, transportation requests and a time window, preferably for each phase. The method processes the input and outputs a vehicle schedule policy. In some embodiments in the active phase, if new transportation requests arise, the structure topology of the vehicles is reconstructed by adding the associated interconnection relations into the underlying communication topology. In some embodiments in the active phase, if some transportation requests are removed, the structure topology of the vehicles is reconstructed by deleting the associated interconnection relations from the underlying communication topology. In some embodiments in the active phase, by a coordinating method, the vehicles can be cooperatively steered to pick-up points. In some embodiments in the handshake phase, if some transportation requests are deleted, then the associated vehicles are immediately removed; and / or equivalently, the associated interconnection relations from the underlying communication topology can be removed. In some embodiments in the handshake phase, the vehicles can be cooperatively steered to drop-off points (destinations). In some embodiments in the bye-bye phase, the vehicles cooperatively return to depots. In some embodiments a schematic for multi-vehicle-based scalability formulation is provided where vehicles may be added or removed. Such a formulation can enhance the flexibility and scalability of the overall system. For a dial-ride-application, if new transportation requests arise, new vehicles can be added (where it is assumed that vehicles and transportation requests are compatible). This corresponds to the procedure of vehicle joining. When some transportation requests are deleted, some vehicles can or should be removed. This corresponds to the procedure of vehicle removing. It is also possible that new transportation requests arise while some of the existing ones should be deleted. Consequently, new vehicles may be added and some vehicles should be deleted. This corresponds to the procedure of vehicle joining and removing more or less simultaneously. A general view on how a dial-a-ride application can be handled using the disclosed method is given. Specifically, once the original transportation request, location of depot and time window are given, vehicles can start from depots to arrive at respective pick-up points. Such a procedure can be determined by vehicle dynamics or structure. In the meantime, some transportation requests may be removed or added. A mechanism, composed of a normal vehicle model and judging framework (vehicle removing and joining), is used to steer vehicles to arrive at pick-up points. This corresponds to the active phase (D2P). Afterwards, once transportation request and time window are given, vehicles can start from pick-up points to drop-off points, depending on prescribed vehicle dynamics or structure. Similarly, some transportation requests may be removed. A mechanism, composed of a normal vehicle model and judging framework (vehicle removing), is used to steer vehicles to arrive at destinations. This corresponds to the handshake phase (P2D). As long as all transportation requests are completed, vehicles can return to depots eventually, governed by a vehicle dynamics mechanism. This corresponds to the bye-bye phase (D2D). With this method the scalability issue of multi-vehicle-based scalability methods for dial-a-ride applications can be resolved. The multi-vehicle-based scalability method is autonomous, and can preserve the scalability property, and thus can potentially be deployed in large-scale autonomous systems. This disclosure proposes a method that completes all transportation requests within certain time-windows even if there are changes, i.e., additions or removals, of transport requests. BRIEF DESCRIPTION OF THE DRAWINGS Embodiments of the invention are described in more detail with reference to the accompanying schematic drawings. Fig. 1 illustrates a schematic environment in which mobile agents can move; Fig. 2 depicts an embodiment of an active phase; Fig. 3 depicts an embodiment of a handshake phase; Fig. 4 depicts an embodiment of a bye-bye phase; and Fig. 5 to Fig. 7 depict an embodiment of a method for operating multiple mobile agents. DETAILED DESCRIPTION OF EMBODIMENT According to the Fig. 1, a method for operating multiple mobile agents 26, such as mobile robots or vehicles, includes an active phase 10, a handshake phase 12 and a bye-bye phase 14. Referring to Fig. 1 and Fig. 2, in the active phase 10 transport information 16 is generated. The transport information 16 includes pick-up location 18, a drop-off location 20 and preferably an amount of vehicles as mobile agents 26. The active phase 10 may further include a preparation step. The preparation step includes selection of a preset-time constraint Ti. The preset-time constraint Ti can be determined based on the drop-off location 20. Furthermore, the preparation step determines a communication topology £±. The communication topology £r is indicative of which mobile agents 26 can communicate with each other. In particular, the communication topology £r includes information about the nearest neighboring mobile agents 26 of each mobile agent 26. The communication topology £r includes a plurality of nodes and edges. Each node represents one of the mobile agents 26. Each edge connects two nodes, where the edge indicates that the mobile agents 26 represented by the nodes have an established communication channel between them. When another mobile agent 26 is added to the communication topology £lt e.g., due to a corresponding transport request 30 (described in more detail below), a new node is added to the communication topology £±. The node gets connected to at least one previously existing node via an edge, in general the previous node from which the added mobile agent 26 received the transport request 30. When a mobile agent 26 is removed from the communication topology £lt the corresponding node and each edge associated with said node are removed from the communication topology £x. The preset-time constraint Ti and the communication topology £x are fed into a transport-space dynamic model 22. The transport-space dynamic model 22 is indicative of the movement of each mobile agent 26 between its respective starting location 24 (i.e., its associated depot) and the pick-up location 18. Initially, the transport-space dynamic model 22 determines a Euclidean distance Csp between the starting location 24 and the pick-up location 18 for each mobile agent 26. The distance can be retrieved from map data of the environment, for example. The transport-space dynamic model 22 may arbitrarily select one of the mobile agents 26 as a leader agent. Preferably, the leader agent is the one having the largest value of Euclidean distance Csp. The leader agent is typically designated i = 1 and gets assigned a proportional delay factor of = 1. The remaining mobile agents 26 get associated a proportional delay factor 5, that can be estimated using the respective euclidean distance and typical velocity of the respective mobile agent 26. The transport-space dynamic model 22 includes the following equations: ^sp v TvJ7 where designates the acceleration between starting location s and destination p for mobile agent 26 number i at time t, Csp designates the euclidean distance between starting location s and pick-up location p, <p(t) designates the auxiliary function and ¢(0 its derivative with respect to time t, 2,(0 designates a correction that depends on neighboring mobile agents 26, and y and e are tuning parameters. The auxiliary function is chosen as f'T’ Cl ---- 0 <t <T (T-tr’ 1, t >T where parameter a >2 is a free parameter and T is the preset-time Ti. The correction is chosen as = (3) J 1 J J chp csp 1 where nonzero a, denotes a weighted gain and designates the set of neighboring agents such that >0. It should be noted that in equations (1) and (2) the velocity vh^pj(t) is typically a vector and may include components indicative of the position of the respective mobile agent 26 as well as its orientation. For each mobile agent 26 the equation (1) is solved using numerical integration techniques. Thereby the time evolution of the agent position, agent velocity and / or agent acceleration are obtained. These data are transformed into control commands 28 for each mobile agent 26 to cause movement of the mobile agent 26 in accordance with transport information 16 from the starting location 24 to the pick-up location 18. The control command 28 is executed by the mobile agent 26. As long as the mobile agent 26 has not reached the pick-up location 18, a transport request 30 can be received by the mobile agent 26. The transport request 30 can be indicative of an addition and / or removal of mobile agents 26 to the communication topology Thus, the transport request 30 may cause a change to the communication topology into a changed communication topology £2 by joining (J), removing (R) or both (J+R) mobile agents 26. In other words, for each time step that the mobile agents 26 are on their way to the pick-up location 18, transport requests 30 can be processed and mobile agents 26 can be added and / or removed for the next time step(s). For example, if more passengers dial for a ride, a transport request 30 is generated that causes more mobile agents 26 to be added to the communication topology (see Fig. 5, dash-dotted lines). If some passengers cancel their ride, a transport request 30 is generated that causes the corresponding mobile agents 26 to be removed from the communication topology (see Fig. 6, dashed lines). If in a time step, some passengers dial a ride and others cancel their ride, a plurality of transport requests 30 are generated, which cause mobile agents 26 to be simultaneously added (see Fig. 7, dash-dotted lines) and removed (see Fig. 7, dashed lines). If the mobile agent 26 has received the transport request 30 and the changed communication topology £2 is generated, equation (1) is solved again based on the changed communication topology T2. The active phase 10 includes a check step which checks whether the mobile agent 26 has reached the pick-up location 18 within an acceptable tolerance regarding time and / or space. If this is not the case, the parameters of the transport-space dynamic model 22 are optimized and equation (1) is solved again. If the mobile agent 26 has reached the pick-up location 18, then passengers can be picked up and the handshake phase 12 is started. Referring to Fig. 1 and to Fig. 3, in the handshake phase 12 the mobile agents 26 move from the pick-up location 18 to the drop-off location 20. The movement of the mobile agents 26 from the pick-up location 18 to the drop-off location 20 is again determined by solving equation (1) similar to the action phase 10, where the pick-up location 18 is the starting location s and the drop-off location 20 is the destination p. However, in this embodiment it is assumed that a transport request 30 was received in the action phase 10 so that the transport-space dynamic model 22 is fed with the changed communication topology £2. As long as the mobile agent 26 has not reached the drop-off location 20, a transport request 30 can be received by the mobile agent 26. The transport request 30 can change the changed communication topology £2 to a further changed communication topology £3 by removing (R) mobile agents 26. It is also possible that the transport request 30 can cause the given time window Ti to be exceeded. In this case or if no transport request 30 is received, the communication topology remains the same (N). If the mobile agent 26 has received the transport request 30 and the further changed communication topology £3 is generated, equation (1) is solved again based on the further changed communication topology £3. Similarly, the handshake phase 12 includes a check step which checks whether the mobile agent 26 has reached the drop-off location 20 within an acceptable tolerance regarding space and / or time. If this is not the case, the parameters of the transportspace dynamic model 22 are optimized and equation (1) is solved again. If the mobile agent 26 has reached the drop-off location 20, then the passengers are dropped off and the bye-bye phase 30 is started. Referring to Fig. 1 and to Fig. 4, in the bye-bye phase 14 the mobile agents 26 move from the drop-off location 20 to a depot 32, in which mobile agents 26 can be housed. The depot 32 can be the same depot 32 from which the mobile agent 26 started or a different depot 32. During the bye-bye phase 14 no more transport requests 30 are processed. In the bye-bye phase 14 the current communication topology £j, where i = 1,2, or 3, is processed. If a transport request 30 is received by a mobile agent 26 during that phase, but before the mobile agent 26 reached the depot 32, the whole process can be started from the beginning, effectively treating the transport request 30 as initial transport information 16. Alternatively, transport requests 30 may be ignored until the mobile agents 26 reached their respective depots 32. A check step checks whether the mobile agent 26 has reached the depot 32 within an acceptable tolerance regarding space and / or time. If this is not the case, the parameters of the transport-space dynamic model 22 are optimized and equation (1) is solved again. If the mobile agent 26 has reached its destination, the system waits for the next transport request 30 which initiates transport information 16 generation. REFERENCE SIGNS active phase handshake phase bye-bye phase transport information pick-up location drop-off location transport-space dynamic model starting location mobile agent control command transport request depot

Claims

1. A computer-implemented method for operating a plurality of mobile agents (26) that are in communication via a communication topology and move in an environment, the environment comprising a set of depots (32), a set of pick-up locations (18), and a set of drop-off locations (20), wherein the method comprises: a) generating transport information (16) that is indicative of any of a number of mobile agents (26), a pick-up location (18), a drop-off location (20), and at least one presettime (Ti), wherein each mobile agent (26) is associated with a depot (32), wherein the preset-time (Ti) is indicative of the maximum time period in which the number of mobile agents (26) has to complete a movement phase;b) at least one movement phase including, for each of the number of mobile agents (26), generating a control command (28) based on the transport information (16), wherein the control command (28) causes the respective mobile agent (26) to move from a starting location (24) to a destination in accordance with the transport information (16); wherein each control command (28) is generated such that the respective mobile agent (26) arrives at its destination within the preset-time (Ti), characterized in that in response to receiving a transport request (30) at least one mobile agent (26) is joined with and / or removed from the communication topology to generate an updated communication topology, wherein the control command (28) is generated based on the updated communication topology and the preset-time (Ti).

2. The method according to any of the preceding claims, wherein in step b) a first movement phase is an active phase (10) that includes, for each of the number of mobile agents (26), generating a control command (28) based on the transport information (16), wherein the control command (28) causes the respective mobile agent (26) to move from its depot (32) as the starting location (24) to a pick-up location (18) in accordance with the transport information (16), wherein each control command (28) is generated such that the respective mobile agent (26) arrives at the pick-up location (18) within the preset-time (Ti).

3. The method according to claim 2, wherein in the active phase (10), the transport request (30) causes at least one mobile agent (26) to join and / or being removed from the communication topology.

4. The method according to any of the preceding claims, wherein in step b) a second movement phase is a handshake phase (12) that includes, for each of the number of mobile agents (26), generating a control command (28) based on the transport information (16), wherein the control command (28) causes the respective mobile agent (26) to move from a pick-up location (18) to a drop-off location (20) in accordance with the transport information (16), wherein each control command (28) is generated such that the respective mobile agent (26) arrives at the pick-up location (18) within the preset-time (Ti).

5. The method according to claim 4, wherein in the handshake phase (12), the transport request (30) causes at least one mobile agent (26) to be removed from the communication topology or no change to the communication topology.

6. The method according to any of the preceding claims, wherein in step b) a third movement phase is a bye-bye phase (14) that includes, for each of the number of mobile agents (26), generating a control command (28) based on the transport information (16), wherein the control command (28) causes the respective mobile agent (26) to move from a drop-off location (20) back to its depot (32), wherein each control command (28) is generated such that the respective mobile agent (26) arrives at its depot (32) within the preset-time (Ti).

7. The method according to any of the preceding claims, wherein the transport information (16) includes a single preset-time (Ti) for all movement phases or an individual preset-time for each movement phase.

8. The method according to any of the preceding claims, wherein the number of mobile agents (26) includes a leader agent, and for all remaining mobile agents (26), a proportional delay factor is determined such that the travel times of the leader agent and the remaining mobile agents (26) from the starting location (16) to the destination within the respective phase are identical.

9. The method according to any of the preceding claims, wherein the control commands (28) are generated to coordinate the mobile agents (26) by determining, for each mobile agent (26), a normalized acceleration based on arrival times of neighboring mobile agents (26) and an auxiliary function that depends on the presettime.

10. The method according to claim 9, wherein the normalized acceleration is determined according towhere i^ / t) designates the acceleration between starting location s and destination p for mobile agent number i at time t, Csp designates the euclidean distance between starting location s (16) and destination p, ¢)(0 designates the auxiliary function and <p(0 its derivative with respect to time t, S,(t) designates a correction that depends on neighboring mobile agents (26), and y and e are tuning parameters.

11. The method according to claim 9 or 10, wherein the auxiliary function is chosen as(p(t) = / (7- 'I 1,where parameter a >2 is a free parameter.

12. The method according to claim 10 or 11, wherein the correction is chosen aswhere nonzero at denotes a weighted gain and Nt designates the set of neighboring mobile agents such that >0.

13. A mobile robot, a vehicle or a data processing apparatus comprising means for carrying out the method according to any of the preceding claims.

14. A computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the method according to any of the claims 1 to 12.

15. A computer-readable medium or a data carrier signal comprising the computer program according to claim 14.

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