METHOD FOR BYPASSING IMPASSABLE OBJECTS BY A ROBOT

Abstract

A method for bypassing impassable objects by a robot through the use of artificial intelligence. A reliable and low-cost bypassing of obstacles taking account of data privacy aspects is achieved in that in the event of a collision of the robot with an obstacle, an optical original recording of the obstacle is produced, artificial duplicates being generated from the original recording, the duplicates being used to train the artificial intelligence. A system has a robot and an IT infrastructure configured to execute the method.

Claims

1-10. (canceled)

11. A method for a bypassing of impassable obstacles by a robot, which comprises the steps of: detecting a collision of the robot with an obstacle as the robot moves through a room; producing an optical original recording of the obstacle; generating a plurality of artificial duplicates from the optical original recording, the artificial duplicates in each case take account of a geometry of the obstacle and differ from one another; training an artificial intelligence using at least some of the artificial duplicates in a training process such that the robot detects the obstacle prior to the collision with the obstacle; and using a training result of a training process for the bypassing of the obstacle by the robot.

12. The method according to claim 11, which further comprises: generating training duplicates and test duplicates from the optical original recording; training the artificial intelligence in the training process with the training duplicates; breaking down the training process into intervals and an intermediate result of the training process is tested in a test process with at least some of the test duplicates in order to determine how likely the robot is to detect the obstacle prior to the collision; and using the intermediate result as the training result if a likelihood lies above a predetermined value.

13. The method according to claim 11, which further comprises generating at least some of the artificial duplicates such that surroundings of the obstacle differ from one of the artificial duplicates to another.

14. The method according to claim 11, which further comprises generating at least some of the artificial duplicates such that a position of the obstacle differs from one of the artificial duplicates to another.

15. The method according to claim 11, which further comprises producing the optical original recording at a distance from the obstacle.

16. The method according to claim 11, wherein: the method is a computer-implemented method; the robot is a household robot; and the artificial intelligence is a neural network.

17. A system, comprising: a robot having an optical recording facility for producing optical recordings and a movement facility for moving said robot; an information technology (IT) infrastructure having an artificial intelligence; and the system being embodied to carry out the method as claimed in claim 11.

18. The system according to claim 17, wherein said robot has a controller which is a component of said IT infrastructure; wherein said IT infrastructure has a main structure, separate from said robot, which contains said artificial intelligence; and further comprising a communication facility for communication between said controller and said main structure.

19. The system according to claim 17, wherein said robot has a detector for detecting collisions of said robot with obstacles.

20. The system according to claim 17, wherein: said robot is a household robot; and said artificial intelligence is a neural network.

21. A non-transitory computer program having computer-executable instructions which when executed by a system containing a robot having an optical recording facility for producing optical recordings and a movement facility for moving said robot and an information technology (IT) infrastructure having an artificial intelligence, the computer-executable instructions causing the system to: detect a collision of the robot with an obstacle as the robot moves through a room; produce an optical original recording of the obstacle; generate a plurality of artificial duplicates from the optical original recording, the artificial duplicates in each case take account of a geometry of the obstacle and differ from one another; train the artificial intelligence using at least some of the artificial duplicates in a training process such that the robot detects the obstacle prior to the collision with the obstacle; and use a training result of the training process for bypassing of the obstacle by the robot.

22. A non-transitory computer-readable medium having computer-executable instructions for performing the method according to claim 11.

Description

[0042] In the drawings, in each case in schematic form,

[0043] FIG. 1 shows a highly simplified, symbolic representation of a system with a robot and an IT infrastructure,

[0044] FIG. 2 shows a flowchart of a method for operating the system.

[0045] A system 1, as is shown by way of example in highly simplified form in FIG. 1, is operated in accordance with a method which is shown by way of example in FIG. 2 on the basis of a flowchart.

[0046] The system 1 comprises a robot 2 as well as an IT infrastructure 3. In the exemplary embodiment shown, the robot 2 is a household robot 4, for example a cleaning robot 5 for cleaning a household (not shown). The robot 2 has an optical recording facility 6, which is preferably used for moving and navigating the robot 2. With the optical recording facility 6, it is possible in particular to produce optical recordings of the surroundings of the robot 2. The robot 2 also has a movement facility 7 for automatically moving the robot 2. The movement facility 7 can have for example an electric motor (not shown), which drives at least one wheel (not shown) of the robot 2. To supply energy to the robot 2, the robot also has an energy storage unit 8, in particular a rechargeable battery 9. The robot 2 embodied as a cleaning robot 5 also has a cleaning facility 10, for example a suction facility 11, with which the robot 2 cleans a room (not shown), in particular the household. The robot 2 also has a detection facility 12, which is embodied such that it detects a collision of the robot 2 with an obstacle (not shown).

[0047] The IT infrastructure 3 comprises components arranged in the robot 2 as well as components separate from the robot 2, and is indicated in FIG. 1 by a dashed box. A control facility 13 of the robot 2 is a component of the IT infrastructure 3. The control facility 13 is connected in a communicative manner to the recording facility 6 and the movement facility 7. The control facility is preferably also connected in a communicative manner to the detection facility 12. A routine 20 (see FIG. 2) for moving the robot 2, also referred to in the following as the movement routine 20, is stored in the control facility 13. For example, a room through which the robot 2 is required or permitted to move is mapped in the movement routine 20. The movement routine 20 can also contain obstacles which are to be bypassed by the robot 2, wherein these obstacles are also referred to in the following as known obstacles.

[0048] The IT infrastructure 3 further comprises a main structure 14, which in the example shown and preferably is a cloud service 15. The main structure 14 comprises an artificial intelligence 16, in particular a neural network 17. The robot 2, in particular the control facility 13, and the main structure 14 communicate with one another via a communication facility 18, preferably wirelessly, wherein the communication facility 18 on the robot 2 and on the main structure 14 in each case has a communication unit 19.

[0049] In accordance with the flowchart shown by way of example in FIG. 2, the robot 2 is moved through the room using the movement routine 20. Here, the surroundings are monitored with the recording facility 6. When known obstacles are detected, they are bypassed, in other words a collision of the robot 2 with the known obstacle is prevented. The recording facility 6 is thus used to navigate the robot 2. During operation, a cleaning of the room, in particular of a substrate (not shown), takes place by way of the robot 2 embodied as a cleaning robot 5 with the aid of the cleaning facility 10.

[0050] A method for bypassing obstacles which are not taken into account in the movement routine 20, also referred to in the following as unknown obstacles, is triggered when the robot 2 collides with such an obstacle. For this reason, the transition to a subsequent measure 21 is shown dashed in FIG. 2. Here, during this measure 21 which triggers the method, also referred to in the following as the detection measure 21, a collision of the robot 2 with the obstacle is detected. The detection facility 12 of the robot 2 is used for this purpose. The collision which has taken place with the obstacle serves as a reason to assume that an unknown obstacle is involved. During a subsequent measure 22, the robot 2 is moved away from the obstacle so that the robot 2 is arranged at a distance from the obstacle. This measure 22 is therefore also referred to in the following as the distance measure 22. With the robot 2 located at a distance from the obstacle, an optical recording of the obstacle is produced with the aid of the recording facility 6 during a measure 23 which is also referred to in the following as the recording measure 23, wherein this recording is also referred to in the following as the original recording. The original recording is then transmitted with the aid of the communication facility 18 to the main structure 14.

[0051] The method is continued in the main structure 14. In the main structure 14, during a duplication measure 24, a multiplicity of duplicates 25 of the original recording is generated artificially. The duplicates 25 in each case take account of the geometry of the obstacle and differ from one another. The differences in the duplicates 25 can be realized by artificially generated, different positions of the obstacle and/or artificially generated, different colors of the obstacle and/or artificially generated, different backgrounds of the obstacle. The duplicates 25 are divided into two groups, namely into training duplicates 25a and test duplicates 25b.

[0052] The artificial intelligence 16 is subsequently trained with the training duplicates 25a in a training process 26. In the training process 26, the artificial intelligence 16, in particular the neural network 17, is trained such that the robot 2 detects the obstacle prior to a collision and bypasses it in the movement routine 20. In a test process 27, the training process 26 is broken down into intervals and thus paused. During the test process 27, a result of the training process 26 achieved to date, also referred to in the following as the intermediate result, is tested. Here, the test duplicates 25b are used during the test process 27. In the test process 26, testing is carried out with at least some of the test duplicates 25b to determine how likely the robot 2, in particular the movement routine 20 using the intermediate result, is to detect the obstacle prior to a collision. If the likelihood lies below a predetermined value, the method returns to the training process 26 and the training process 26 is continued. If the likelihood lies above the predetermined value, the intermediate result is captured as the training result and used during the movement routine 20 of the robot 2. For this purpose, the main structure 14 uses the communication facility 18 to transmit the training result to the control facility 13 in order to integrate the training result into the movement routine 20. The integration of the training result into the movement routine 20 can take place within the robot 2, in particular by way of the control facility 13. Alternatively, the main structure 14 can integrate the training result into the movement routine 20 and transmit the movement routine 20 which takes account of the training result in particular to the control facility 13, which then uses the movement routine 20 which takes account of the training result.

[0053] The robot 2 can be operated normally during the training process 26 and the test process 27. This means in particular that the robot 2 can use the available movement routine 20 during the training process 26 and the test process 27.

LIST OF REFERENCE CHARACTERS

[0054] 1 System [0055] 2 Robot [0056] 3 IT infrastructure [0057] 4 Household robot [0058] 5 Cleaning robot [0059] 6 Recording facility [0060] 7 Movement facility [0061] 8 Energy storage unit [0062] 9 Battery [0063] 10 Cleaning facility [0064] 11 Suction facility [0065] 12 Detection facility [0066] 13 Control facility [0067] 14 Main structure [0068] 15 Cloud service [0069] 16 Artificial intelligence [0070] 17 Neural network [0071] 18 Communication facility [0072] 19 Communication unit [0073] 20 Movement routine [0074] 21 Detection measure [0075] 22 Distance measure [0076] 23 Distance measure [0077] 24 Duplication measure [0078] 25 Duplicate [0079] 26 Training process [0080] 27 Test process