Liquid droplet path prediction

• US 10,780,861 B2
• Filed: 01/08/2019
• Issued: 09/22/2020
• Est. Priority Date: 01/08/2019
• Status: Active Grant

• Current Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Original Assignee: Ford Global Technologies, LLC (Ford Motor Company)
• Inventors: Herman, David Michael, Arunmozhi, Ashwin, Krishnan, Venkatesh, Patil, Sunil
• Primary Examiner(s): Niu, Feng
• Application Number:
  US16/242,225
• Publication Number:
  US 20200216033A1
• Time in Patent Office: 623 Days
• CPC Class Codes: B60S 1/0844 including a camera
• CPC Class Codes: B60S 1/56 specially adapted for cleaning other parts or devices than front windows or windscreens rear-view mirror arrangements mounted on vehicle exterior including cleaning devices B60R1/0602
• CPC Class Codes: G05D 1/0088 characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours using knowledge based models G06N5/00
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/20076 Probabilistic image processing
• CPC Class Codes: G06T 2207/20081 Training; Learning
• CPC Class Codes: G06T 2207/20084 Artificial neural networks [ANN]
• CPC Class Codes: G06T 2207/30192 Weather; Meteorology
• CPC Class Codes: G06T 2207/30252 Vehicle exterior; Vicinity of vehicle
• CPC Class Codes: G06T 7/20 Analysis of motion motion estimation for coding, decoding, compressing or decompressing digital video signals H04N19/43, H04N19/51
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06T 7/277 involving stochastic approaches, e.g. using Kalman filters
• CPC Class Codes: G06T 7/70 Determining position or orientation of objects or cameras camera calibration G06T7/80
• CPC Class Codes: G06V 20/56 exterior to a vehicle by using sensors mounted on the vehicle
• CPC Class Codes: G06V 20/58 Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads

Abstract

A system includes a processor and a memory storing instructions executable by the processor to predict a path of a liquid droplet on a surface, and then, actuate one or more vehicle components based on the path.

Claims

1. A system, comprising:

a processor; and

a memory storing instructions executable by the processor to;

predict a path of a liquid droplet on a surface; and

then, actuate one or more vehicle components based on the path.

2. The system of claim 1, the instructions further including instructions to determine that the path is from a low priority area on the surface to a high priority area on the surface, wherein the high priority area has a higher probability of containing detectable objects that may interfere with operation of a vehicle as compared to the low priority area.

3. The system of claim 1, the instructions further including instructions to predict the path based on at least one of a vehicle velocity, a wind velocity, an incline angle of the surface, a vehicle acceleration, a size of the liquid droplet, and a hydrophobicity of the surface.

4. The system of claim 1, the instructions further including instructions to predict the path based on stored data indicating one or more previous positions of the liquid droplet.

5. The system of claim 1, the instructions further including instructions to actuate the one or more vehicle components by actuating a cleaning system.

6. The system of claim 5, the instructions further including instructions to predict a second path of the liquid droplet after actuating the cleaning system.

7. The system of claim 1, the instructions further including instructions to actuate the one or more vehicle components by actuating at least one of a steering system, a braking system, and a propulsion system.

8. The system of claim 1, the instructions further including instructions to wait an amount of time after predicting the path, and then update one or more parameters of the prediction based on a comparison of a position of the liquid droplet with the path.

9. The system of claim 1, further comprising an optical sensor defining a field of view and in communication with the processor, wherein the surface is in the field of view.

10. The system of claim 1, the instructions further including instructions to identify an amount of time for the liquid droplet to reach a future position, and to determine the amount of time to reach the future position is greater than a threshold amount of time.

11. The system of claim 1, wherein the surface is on one of a lens and a windshield.

12. A method, comprising:

predicting a path of a liquid droplet on a surface; and

then, actuating one or more vehicle components based on the path.

13. The method of claim 12, wherein the path is predicted based on at least one of a vehicle velocity, a wind velocity, an incline angle of the surface, a vehicle acceleration, a size of the liquid droplet, and a hydrophobicity of the surface.

14. The method of claim 12, further comprising waiting an amount of time after predicting the path, and then updating one or more parameters of the prediction based on a comparison of a position of the liquid droplet with the path.

15. The method of claim 12, further comprising identifying an amount of time for the liquid droplet to reach a future position, and to determine the amount of time to reach the future position is greater than a threshold amount of time.

16. The method of claim 12, wherein actuating one or more vehicle components includes actuating a cleaning system, and further comprising predicting a second path of the liquid droplet after actuating the cleaning system.

17. The method of claim 12, wherein the path is predicted based on stored data indicating one or more previous positions of the liquid droplet.

18. A system, comprising:

means for detecting a liquid droplet on a surface;

means for predicting a path of the liquid droplet on the surface; and

means for moving the liquid droplet relative to the surface based on the path.

19. The system of claim 18, further comprising means for navigating a vehicle based on the path.

20. The system of claim 18, further comprising means for determining that the path is from a low priority area on the surface to a high priority area on the surface, wherein the high priority area has a higher probability of containing detectable objects that may interfere with operation of a vehicle as compared to the low priority area.