METHOD FOR ASCERTAINING A DIRECTION OF TRAVEL OF AN AT LEAST SEMIAUTONOMOUSLY OR AUTONOMOUSLY MOVABLE UNIT, AND DEVICE OR SYSTEM

Abstract

A method for ascertaining a direction of travel and/or a future path of travel of a robot and/or a vehicle, movable at least semiautonomously or autonomously in a dynamically changeable surrounding area. The method includes: measuring and/or ascertaining surrounding-area parameters, which may each be assigned to at least one moving, external object in the area surrounding the unit; executing at least one movement prediction algorithm for ascertaining, in each instance, at least one probabilistic movement prediction parameter for detected external objects as a function of measured surrounding-area parameters assigned to the individual external objects; executing at least one movement determination algorithm for ascertaining at least one short-term movement parameter for each detected external objects as a function of measured surrounding-area parameters assigned to the individual external objects; the movement prediction algorithm and the movement determination algorithm being executed at least substantially independently of each other.

Claims

1-11. (canceled)

12. A method for ascertaining a direction of travel and/or a future path of travel of a unit movable at least semiautonomously or autonomously in a dynamically changeable surrounding area, the method comprising the following steps: measuring and/or ascertaining a plurality of surrounding-area parameters, which may each be assigned to at least one moving, external object in an area surrounding the unit; executing at least one movement prediction algorithm for ascertaining at least one probabilistic movement prediction parameter for each detected external object as a function of the surrounding-area parameters assigned to the detected external object; executing at least one movement determination algorithm for ascertaining at least one short-term movement parameter for each detected external object as a function of the surrounding-area parameter assigned to the detected external object; and wherein the movement prediction algorithm and the movement determination algorithm are executed at least substantially independently of each other, to ascertain a future direction of travel and/or a future path of travel of the unit.

13. The method as recited in claim 12, wherein the unit is a robot and/or a vehicle.

14. The method as recited in claim 12, further comprising: subsequently to the executing of the movement determination algorithm, executing at least one emergency collision prevention algorithm is a part of a model predictive control of the unit, wherein emergency control including emergency braking and/or an evasive movement of the unit and/or of a future path of travel, is carried out using the emergency collision prevention algorithm, when a virtual spacing of a position of the unit on the future path of travel of the unit and a future position of a detected external object ascertained as a function of an ascertained short-term movement parameter of the at least one short-term movement parameter, falls below a predefined limiting value at at least one instant.

15. The method as recited in claim 12, further comprising: subsequently to the executing of the movement prediction algorithm, executing at least one pathfinding algorithm including a theta* pathfinding algorithm, wherein, using the pathfinding algorithm, a future path of travel of the unit is determined dynamically as a function of the ascertained probabilistic movement prediction parameters of the detected external object.

16. The method as recited in claim 12, wherein, to ascertain the future path of travel and/or direction of travel of the unit as a function of the detected external object, the movement determination algorithm is considered at a higher priority than the movement prediction algorithm.

17. The method as recited in claim 12, wherein, in the step of executing the movement determination algorithm, a number of short-term movement parameters or of values of a short-term movement parameter is ascertained, inversely proportionally, for each detected external object, as a function of a number and/or a type of different, measured surrounding-area parameters of the detected external object.

18. The method as recited in claim 12, wherein, in the step of executing the movement determination algorithm, at least one short-term movement parameter of each detected external object is ascertained as a purely deterministic variable as a function of measured surrounding-area parameters of the external object exclusively using a stored physical computational model.

19. The method as recited in claim 12, wherein all of detected external objects are filtered for moving or mobile external objects, wherein, in the executing of the movement determination algorithm, only surrounding-area parameters associated with moving or mobile external objects being taken into consideration for ascertaining the short-term movement parameters.

20. The method as recited in claim 12, wherein the movement determination algorithm is utilized to ascertain a surrounding-area parameter of the external object.

21. The method as recited in claim 12, wherein the movement determination algorithm and the movement prediction algorithm are executed in a periodically repeated manner, the movement determination algorithm being executed at a higher frequency than the movement prediction algorithm.

22. A device or system, comprising: at least one processing unit, configured to ascertaining a direction of travel and/or a future path of travel of a unit movable at least semiautonomously or autonomously in a dynamically changeable surrounding area, wherein the processing unit is configured to: measure and/or ascertain a plurality of surrounding-area parameters, which may each be assigned to at least one moving, external object in an area surrounding the unit; execute at least one movement prediction algorithm for ascertaining at least one probabilistic movement prediction parameter for each detected external object as a function of the surrounding-area parameters assigned to the detected external object; execute at least one movement determination algorithm for ascertaining at least one short-term movement parameter for each detected external object as a function of the surrounding-area parameter assigned to the detected external object; and wherein the movement prediction algorithm and the movement determination algorithm are executed at least substantially independently of each other, to ascertain a future direction of travel and/or a future path of travel of the unit.

23. The device or system as recited in claim 22, wherein the device is a robot movable semiautonomously or autonomously.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Further advantages are derived from the following description of figures. An exemplary embodiment of the present invention is depicted in the figures. The disclosure herein includes numerous features in combination. One skilled in the art will necessarily consider the features individually, as well, and unite them to form useful, further combinations.

[0030] FIG. 1 shows a schematic representation of a system of an example embodiment of the present invention, which includes a semiautonomously movable unit, for carrying out a method of the present invention of controlling the unit in a dynamically changeable surrounding area.

[0031] FIG. 2 shows a block diagram of the method of the present invention for controlling the unit of the present invention.

[0032] FIG. 3 shows a schematic representation of an example of the execution of the method according to the present invention.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

[0033] Shown in FIG. 1, is a schematic representation of a system 10, including at least one device taking the form of an autonomously movable unit 12, in particular, an autonomous vehicle, during a movement of unit 12 in a dynamically changeable surrounding area 28. Unit 12 includes a detection unit 14, a drive unit 16, and a control and/or regulating unit 18. Unit 12/the device is intended for carrying out a method 19 of ascertaining a direction of travel and/or a path of travel of unit 12 in dynamically changeable surrounding area 28. In particular, control and/or regulating unit 18 includes a processing unit 20, which takes the form of, in particular, part of system 10. A plurality of external objects 22, 24, 26 are situated in surrounding area 28 of system 10, in particular, of unit 12 or the device; the external objects moving or being positioned statically within surrounding area 28. In particular, unit 12 moves relative to external objects 22, 24, 26. By way of example, two moving external objects 22, 24 and one static external object 26 are shown in FIG. 1. Detection unit 14 is preferably intended for detecting external objects 22, 24, 26 in surrounding area 28. In particular, detection unit 14 includes a camera and a lidar system (not shown individually in the figures). As an alternative to processing unit 20, which takes the form of part of unit 12, it is possible for system 10, in particular, control and/or regulating unit 18, to include a remote processing unit 30, which takes the form of, for example, part of a network, a smart-home system, a cloud, or the like. In particular, system 10 includes a communications unit 32 for communicating wirelessly with remote processing unit 30, with other units or devices of system 10, and/or with external units. Communications unit 32 preferably includes at least one communications element 33, which takes the form of part of unit 12 or is situated on unit 12. Other embodiments of system 10, in particular, of unit 12 and/or of detection unit 14, are also possible. For example, it is possible for unit 12/the device to take the form of a working robot moving semiautonomously or fully autonomously, such as a robot vacuum cleaner, a robot lawn mower, or the like. In addition, it is possible for system 10 to include more than one device and/or more than one unit 12 moving autonomously. Alternatively, or in addition, it is possible for detection unit 14 to be formed separately from unit 12. In an alternative exemplary embodiment of system 10, the device takes the form of a robot, which moves in surrounding area 28; detection unit 14 being situated in or on a working region of the robot and preferably being intended for detecting the robot, as well as external objects 22, 24, 26 in a surrounding area 28 of the robot.

[0034] Detection unit 14 is intended for measuring surrounding-area parameters of detected external objects 22, 24, 26. For example, surrounding-area parameters of external objects 22, 24, 26 measured by detection unit 14 take the form of a position of an external object 22, 24, 26 in space, a distance of an external object 22, 24, 26 from detection unit 14, or the like. Control and/or regulating unit 18 is configured to ascertain surrounding-area parameters of external objects 22, 24, 26 as a function of data about external objects 22, 24, 26 acquired by detection unit 14. For example, surrounding-area parameters of external objects 22, 24, 26 ascertained, using control and/or regulating unit 18, take the form of a velocity of an external object 22, 24, 26, a direction of movement of an external object 22, 24, 26, or the like. Surrounding-area parameters, which are each ascertained over more than one image and/or scene recorded by detection unit 14, are preferably ascertained with the aid of control and/or regulating unit 18.

[0035] The three different external objects 22, 24, 26 in surrounding area 28 of unit 12 are shown illustratively in FIG. 1. A first external object 22 of the three external objects 26 takes the form of a stationary object; no movement of the first external object 26 being measured. A second external object 22 of the three external objects 22, 24, 26 moves relative to unit 12 and relative to surrounding area 28. For example, a direction of movement 34 and a velocity are ascertained as surrounding-area parameters for second external object 22, using detection unit 14 and control and/or regulating unit 18. In addition, it is possible for a type of external object 22 and/or further additional data about second external object 22 to be additionally ascertained for second external object 22, using detection unit 14 and control and/or regulating unit 18. By comparison of acquired data with at least one data set, it is possible for a vehicle model, an identity of a person, or the like to be identified as additional information about an external object, using, in particular, external processing unit and/or an external unit. For example, it is possible for second external object 22 to be recognized as a vehicle of a certain vehicle model; by identifying the vehicle model, additional information, such as unladen weight, maximum speed, or the like being able to be ascertained as additional surrounding-area parameters. A third external object 24 of the three external objects 22, 24, 26 moves relative to unit 12 and relative to surrounding area 28 and preferably takes the form of a pedestrian.

[0036] Control and/or regulating unit 18, in particular processing unit 20, is configured to execute a movement prediction algorithm 36 (cf. FIG. 2) for ascertaining, in each instance, at least one probabilistic movement prediction parameter for detected external objects 22, 24, 26 as a function of measured surrounding-area parameters assigned to individual external objects 22, 24, 26. Control and/or regulating unit 18, in particular processing unit 20, is configured to execute a movement determination algorithm 38 (cf. FIG. 2) for ascertaining, in each instance, at least one short-term movement parameter for detected external objects 22, 24, 26 as a function of measured surrounding-area parameters assigned to individual external objects 22, 24, 26. Control and/or regulating unit 18, in particular, processing unit 20, is configured to execute movement prediction algorithm 36 and movement determination algorithm 38 at least substantially independently from each other, in order to ascertain a future direction of travel and a future path of travel 40 of unit 12, respectively. In at least one step, in order to ascertain future path of travel 40 and/or direction of travel of unit 12 as a function of detected external objects 22, 24, 26, movement determination algorithm 38 is considered by control and/or regulating unit 18, in particular, processing unit 20, at a higher priority than movement prediction algorithm 36.

[0037] With the aid of movement determination algorithm 38, control and/or regulating unit 18, in particular, processing unit 20, is preferably configured to ascertain the short-term movement parameter(s) as a purely deterministic variable, using a physical computational model. Control and/or regulating unit 18, in particular, processing unit 20, is preferably configured to filter detected, moving external objects 22, 24, 26 out of detected external objects 22, 24, 26; only external objects 22, 24 moving relative to surrounding area 28 being selected for consideration in movement determination algorithm 38. In this context, for example, first external object 26 would not be considered for movement determination algorithm 38, since it is stationary. However, it is also possible for all detected external objects 22, 24, 26 to be considered for movement determination algorithm 38. In each instance, a short-term movement parameter is ascertained for second external object 22 and third external object 24, using movement determination algorithm 38; each short-term movement parameter preferably corresponding to a path of travel 42, 44 of respective external object 22, 24, which respective external object 22, 24 covers, in particular, independently of steering angles or the like, within a subsequent short-term interval. All detected external objects 22, 24, 26 are considered for movement prediction algorithm 36; in each instance, at least one probabilistic movement prediction parameter, in particular, a plurality of probabilistic movement prediction parameters, being ascertained for each detected external object 22, 24, 26. Preferably, the probabilistic movement prediction parameters each take the form of a possible time characteristic 46, 48 (shown illustratively as paths of travel in FIG. 1) of a future position of respective external object 22, 24, 26, in particular, in a time frame exceeding a short-term interval. It is possible for the probabilistic movement prediction parameters to be ascertained with the aid of movement prediction algorithm 36 as a function of known behavioral patterns, stored traffic rules, or the like. Alternatively, or in addition, it is possible for the probabilistic movement prediction parameters to be ascertained with the aid of movement prediction algorithm 36 as a function of electronic data exchanged with respective external object 22, 24, 26, for example, if respective external object 22, 24, 26 takes the form of another networked and/or autonomous/semiautonomous unit. The ascertained short-term movement parameters are preferably intended for a description of a future movement of an external object 22, 24, 26 in a short-term interval. The ascertained probabilistic movement prediction parameter(s) is/are preferably intended for probabilistic pathfinding for the device/unit 12 in surrounding area 28; in particular, possible future paths of travel of external objects 22, 24, 26 and/or possible time characteristics 46, 48 of a future position of external objects 22, 24, being taken into account.

[0038] A block diagram of method 19 is shown in FIG. 2. In a step 50, surrounding area 28, as well as external objects 22, 24, 26 in surrounding area 28, are monitored. In addition, movement parameters of unit 12, such as a velocity, a direction of movement, an acceleration, or the like, are measured. In one step, in particular, step 50, the surrounding-area parameters of external objects 22, 24, 26 are ascertained and transmitted to control and/or regulating unit 18. It is also possible for the surrounding-area parameters to be ascertained at least partially or completely by control and/or regulating unit 18, using, in particular, data acquired by detection unit 14. In a further step 52, moving external objects 22, 24 and external objects 26 stationary relative to surrounding area 28 are distinguished. Measured and/or ascertained surrounding-area parameters are transmitted to processing unit 18, which executes movement prediction algorithm 36 and movement determination algorithm 38 independently from each other, in particular, in two further steps 54, 56. Preferably, in step 56, it is possible for only external objects 22, 24 that are moving relative to surrounding area 28 to be selected for movement determination algorithm 38. Preferably, in step 54, it is possible for all detected external objects 22, 24, 26 to be selected for movement prediction algorithm 36. In a further step 58, with the aid of a pathfinding algorithm 64, in each instance, at least one possible future path of travel 40, in particular, in each instance, a plurality of possible future paths of travel 40, of unit 12, is/are ascertained as a function of the probabilistic movement prediction parameters for detected external objects 22, 24, 26 ascertained by movement prediction algorithm 36, and as a function of measured and/or ascertained surrounding-area parameters. In particular, in further step 58, at least one future path of travel 40 of unit 12/the device is ascertained, for example, using a two-dimensional cost map and/or a theta* planning function, as a function of the ascertained probabilistic movement prediction parameters, in particular, ascertained possible future paths of travel 42, 44 of external objects 22, 24, 26. In a further step 60, unit 12/the device is controlled, in particular, using model predictive control (MPC). Unit 12/the device is preferably controlled with the aid of control and/or regulating unit 18 as a function of the at least one ascertained future path of travel 40 of unit 12/the device.

[0039] In step 60, an emergency collision prevention algorithm 62 is executed; emergency control 66, in particular, emergency braking and/or an evasive movement, of unit 12 (see FIG. 1, shown by way of example as an evasive maneuver, using the steering angle) being carried out, if a, in particular, virtual, spacing of a position of unit 12 on future path of travel 40 of unit 12 and a future position of external object 22, 24, 26 ascertained as a function of an ascertained short-term movement parameter of an external object 22, 24, 26, falls below a predefined limiting value at at least one instant. In particular, emergency collision prevention algorithm 62 is executed at a higher priority than the control of unit 12/the device as a function of ascertained, possible future path of travel 40; for example, emergency control 66, in particular, emergency braking and/or an evasive movement, a movement originally planned, and/or a steering angle originally planned, being replaced and/or executed prior to this. Control and/or emergency control 66, in particular, emergency braking and/or an evasive movement, of unit 12 is preferably taken into account in further monitoring of surrounding area 28 and/or in a movement parameter of unit 12. In particular, surrounding area 28 and/or external objects 22, 24, 26 are monitored continuously by detection unit 14. Emergency collision prevention algorithm 62, in particular, emergency control 66, is intended for directly preventing collisions of the device/of unit 12 with external objects 22, 24, 26.

[0040] An example of the execution of method 19 of ascertaining a direction of travel and/or a future path of travel of the unit 12 movable at least semiautonomously or autonomously in dynamically changeable surrounding area 28, is shown schematically in FIG. 3. In a method step 68 of method 19, external objects 22, 24, 28 and surrounding-area parameters of external objects 22, 24, 26 are monitored. In a method step of method 19, in particular, method step 68 or a further method step following it, as an alternative, or in addition, surrounding-area parameters of detected external objects 22, 24, 26 are ascertained partially or completely, with the aid of control and/or regulating unit 18, as a function of data about external objects 22, 24, 26 acquired by detection unit 14. In particular, the surrounding-area parameters may each be assigned to at least one external object 22, 24, 26, which moves relative to unit 12 and is in the area 28 surrounding unit 12. In a method step of method 19, in particular, method step 68, at least one movement parameter of unit 12, which describes, in particular, a current movement of unit 12 in surrounding area 28 and/or in space, is measured. It is possible for the movement parameter(s) of unit 12 to be measured, for example, via drive unit 16 of unit 12, with the aid of detection unit 14 and/or with the aid of control and/or regulating unit 18.

[0041] In a further method step 70 of method 19, all of the detected external objects 22, 24, 26 are filtered for moving or movable external objects 22, 24, 26; in particular, in the case of executing movement determination algorithm 38 later, in particular, only surrounding-area parameters associated with external objects 22, 24 moving and/or movable relative to surrounding area 28 being taken into consideration for ascertaining short-term movement parameters. As an alternative, it is possible for all detected, external objects 22, 24, 26 to be considered for movement determination algorithm 38.

[0042] In a further method step 72 of method 19, in particular, with the aid of processing unit 20, the movement prediction algorithm 36 for ascertaining, in each instance, at least one probabilistic movement prediction parameter for detected external objects 22, 24, 26, is executed as a function of measured surrounding-area parameters assigned to individual external objects 22, 24, 26. In a further method step 74 of method 19, in particular, with the aid of processing unit 20, the movement determination algorithm 38 for ascertaining, in each instance, at least one short-term movement parameter for detected external objects 22, 24, 26, is executed as a function of measured surrounding-area parameters assigned to individual external objects 22, 24, 26. In order to ascertain a future direction of travel and/or a future path of travel of unit 12, movement prediction algorithm 36 and movement determination algorithm 38 are executed at least substantially independently of each other. To ascertain the future path of travel and/or the future direction of travel of unit 12 as a function of detected external objects 22, 24, 26, movement determination algorithm 38 is considered at a higher priority than movement prediction algorithm 36. In a method step of method 19, in particular, method step 74, a number of short-term movement parameters or of values of a short-term movement parameter is ascertained, in particular, inversely proportionally, for respective external object 22, 24, 26 as a function of a number and/or type of different, measured surrounding-area parameters of individual external objects 22, 24, 26. In a method step of method 19, in particular, method step 74, at least one short-term movement parameter of one of detected external objects 22, 24, 26 is ascertained as a purely deterministic variable as a function of measured surrounding-area parameters of respective external object 22, 24, 26, in particular, exclusively with the aid of a stored physical computational model. Preferably, all of the short-term movement parameters ascertained by movement determination algorithm 38 are ascertained exclusively with the aid of the stored physical computational model, in the form of purely deterministic variables.

[0043] In a further method step 76 of method 19, pathfinding algorithm 64, in particular, a theta* pathfinding algorithm, is executed; with the aid of pathfinding algorithm 64, a, in particular, possible, future path of travel of unit 12 being determined dynamically as a function of the ascertained probabilistic movement prediction parameters of detected external objects 22, 24, 26.

[0044] In a further method step 78 of method 19, emergency collision prevention algorithm 62, which takes the form of, in particular, a part of model predictive control of unit 12, is executed, in particular, with the aid of control and/or regulating unit 18; emergency control, in particular, emergency braking and/or an evasive movement, of unit 12 being carried out with the aid of emergency collision prevention algorithm 62, if a, in particular, virtual, spacing of a position of unit 12 on the future path of travel of unit 12 and a future position of an external object 22, 24, 26 ascertained as a function of an ascertained short-term movement parameter, falls below a predefined limiting value at at least one instant. For example, an external object 22 (see FIG. 1) is ascertained, which would collide with, or has a high probability of colliding with, unit 12. Using emergency collision prevention algorithm 62, in particular, the above-mentioned emergency control 66 is preferably determined, by which unit 12 has, in particular, at least a certain probability of being able to prevent a collision with external object 22. For example, in this instance, emergency control 66 takes the form of the steering of unit 12 at a certain angle, as well as the simultaneous braking by a certain amount. In one method step of method 19, in particular, method step 78, a future path of travel of unit 12 is ascertained; in particular, in order to ascertain the future path of travel and/or direction of travel of unit 12 as a function of detected external objects 22, 24, 26, emergency control 66, which is carried out as a function of output signals of movement determination algorithm 38, being considered at a higher priority than the possible future path of travel of unit 12 ascertained by pathfinding algorithm 64 and/or as a function of output signals of movement prediction algorithm 36. In at least one method step of method 19, such as method step 80, it is possible for at least one short-term movement parameter of an external object 22, 24, 26 ascertained by movement determination algorithm 38, to be utilized, for example, to ascertain a surrounding-area parameter of respective external object 22, 24, 26, in particular, in a future iteration of method 19. Movement determination algorithm 38 and movement prediction algorithm 36 are executed in a periodically repeated manner; movement determination algorithm 38 being executed at a higher frequency than movement prediction algorithm 36. Pathfinding algorithm 64 and emergency collision prevention algorithm 62 are preferably executed in a periodically repeated manner; emergency collision prevention algorithm 62 preferably being executed at a higher frequency than pathfinding algorithm 64. If, for example, an external object 22 is ascertained, which would collide with unit 12, or has a high probability of colliding with it, in a directly subsequent short-term interval, then, in method step 78, emergency control 66 is first executed and/or initiated by control and/or regulating unit 18, instead of or before a movement of unit 12 along another future path of travel of unit 12 ascertained, in particular, using pathfinding algorithm 64, is executed and/or initiated by control and/or regulating unit 18.

[0045] In a further method step 80 of method 19, the future path of travel of unit 12 is determined by emergency control 66, in particular, emergency braking and/or an evasive movement, or by the future path of travel ascertained by pathfinding algorithm 64. The future, determined path of travel of unit 12 is preferably implemented by control and/or regulating unit 18; in particular, unit 12 being forced to move along the future path of travel determined. For example, drive unit 16 and/or at least a steering unit of unit 12/the device is controlled and/or regulated with the aid of control and/or regulating unit 18, using control signals.

[0046] A possible example of an embodiment of method 19 is described, in particular, in FIG. 3. Other refinements of method 19 are also possible, for example, having a different order of method steps 68, 70, 72, 74, 76, 78, 80 and/or a different number of method steps 68, 70, 72, 74, 76, 78, 80.