IP Library › Granted Patent US 12,292,748
Granted Patent B2
US 12,292,748 · App. 18/840,332 · Granted May 6, 2025

Lawn mower control method and device, lawn mower, and storage medium

Inventor: Li Yuan (Guangdong, CN)
Assignee: SHENZHEN MAMMOTION INNOVATION CO., LIMITED
G05D1/86A01D34/006G05D1/87G05D2107/23
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Quick Facts
Patent No.
US 12,292,748
App. No.
18/840,332
Granted
May 6, 2025
Kind
B2
Abstract

A lawn mower control method and device, a lawn mower, and a storage medium. The method comprises: detecting operating data and sensing data of a plurality of operating sensors provided on a lawn mower, wherein the plurality of operating sensors comprise at least two different types of sensors; fusing the sensing data of the plurality of operating sensors to obtain environment data around the lawn mower; determining, when it is detected that a fault occurs in any of the operating sensors, a fault type of a faulty sensor according to the operating data of the faulty sensor and the environment data around the lawn mower; and controlling, if the fault type of the faulty sensor is a first fault type, the faulty sensor to stop operating, and a backup sensor corresponding to the faulty sensor to start operating.

Claims (69)

1. A lawn mower control method, comprising:

detecting operating data and sensing data of a plurality of operating sensors provided on a lawn mower, wherein the plurality of operating sensors comprise at least two different types of sensors, the at least two different types of sensors comprise image sensors and position sensors, sensing data of the at least two different types of sensors is configured to obtain an information of obstacle;

fusing the sensing data of the plurality of operating sensors to obtain environment data around the lawn mower, the environment data comprises the information of obstacle;

determining, when it is detected that a fault occurs in any of the operating sensors, a fault type of a faulty sensor according to the operating data of the faulty sensor the environment data around the lawn mower, and a correspondence table corresponding to the faulty sensor, wherein the faulty sensor is an operating sensor in which a fault occurs, the correspondence table comprises a correspondence of various fault types with a range of parameters, the range of parameters comprising a range of operating data and a range of environment data; and

controlling, in response to the fault type of the faulty sensor is a first fault type, the faulty sensor to stop operating, and a backup sensor corresponding to the faulty sensor to start operating.

2. The method according to claim 1 , wherein

the correspondence table is a preset correspondence table or a correspondence table obtained from a server based on historical fault data.

3. The method according to claim 2 , before controlling a backup sensor corresponding to the faulty sensor to start operating, further comprising:

determining the backup sensor corresponding to the faulty sensor;

the step of determining the backup sensor corresponding to the faulty sensor comprising:

determining an identification of the faulty sensor;

determining an identification associated with the identification of the faulty sensor according to the identification of the faulty sensor and a preset association relationship, wherein the preset association relationship comprises an association relationship between an identification of each operating sensor and an identification of a respective backup sensor; and

determining the backup sensor indicated by the identification associated with the identification of the faulty sensor as the backup sensor corresponding to the faulty sensor.

4. The method according to claim 1 , wherein the step of determining the fault type of the faulty sensor according to the operating data of the faulty sensor, the environment data around the lawn mower, and a correspondence table corresponding to the faulty sensor comprises:

determining, in response to the operating data of the faulty sensor and the environment data around the lawn mower satisfy a range of parameters corresponding to the first fault type characterizing a hardware fault, that the fault type of the faulty sensor is the first fault type; and

determining, in response to the operating data of the faulty sensor and the environment data around the lawn mower satisfy a range of parameters corresponding to a second fault type characterizing a software fault, that the fault type of the faulty sensor is the second fault type.

5. The method according to claim 4 , further comprising:

controlling the faulty sensor to restart in response to the fault type of the faulty sensor is the second fault type.

6. The method according to claim 5 , after controlling the faulty sensor to restart, further comprising:

controlling, in response to it is detected that a fault still occurs in the faulty sensor after restarting, the faulty sensor to stop operating, and the backup sensor corresponding to the faulty sensor to start operating.

7. The method according to claim 4 , before controlling a backup sensor corresponding to the faulty sensor to start operating, further comprising:

determining the backup sensor corresponding to the faulty sensor;

the step of determining the backup sensor corresponding to the faulty sensor comprising:

determining an identification of the faulty sensor;

determining an identification associated with the identification of the faulty sensor according to the identification of the faulty sensor and a preset association relationship, wherein the preset association relationship comprises an association relationship between an identification of each operating sensor and an identification of a respective backup sensor; and

determining the identification of the respective backup sensor indicated by the identification associated with the identification of the faulty sensor as the backup sensor corresponding to the faulty sensor.

8. The method according to claim 1 , wherein

using a trained fault recognition model to perform fault recognition based on the operating data of the faulty sensor and the environment data around the lawn mower, so as to obtain the fault type of the faulty sensor; wherein a training method for the trained fault recognition model comprises:

obtaining a training data, the training data comprising operating data and environment data, and a true fault type of a sample faulty sensor when a fault occurs in the sample faulty sensor, wherein the true fault type of the sample faulty sensor comprises the first fault type characterizing a hardware fault and a second fault type characterizing a software fault; and

using the training data to train a fault recognition model to be trained, so as to obtain the trained fault recognition model.

9. The method according to claim 8 , before controlling a backup sensor corresponding to the faulty sensor to start operating, further comprising:

determining the backup sensor corresponding to the faulty sensor;

the step of determining the backup sensor corresponding to the faulty sensor comprising:

determining an identification of the faulty sensor;

determining an identification associated with the identification of the faulty sensor according to the identification of the faulty sensor and a preset association relationship, wherein the preset association relationship comprises an association relationship between an identification of each operating sensor and an identification of a respective backup sensor; and

determining the identification of the respective backup sensor indicated by the identification associated with the identification of the faulty sensor as the backup sensor corresponding to the faulty sensor.

10. The method according to claim 8 , further comprising:

controlling the faulty sensor to restart in response to the fault type of the faulty sensor is the second fault type.

11. The method according to claim 1 , before controlling a backup sensor corresponding to the faulty sensor to start operating, further comprising:

determining the backup sensor corresponding to the faulty sensor;

the step of determining the backup sensor corresponding to the faulty sensor comprising:

determining an identification of the faulty sensor;

determining an identification associated with the identification of the faulty sensor according to the identification of the faulty sensor and a preset association relationship, wherein the preset association relationship comprises an association relationship between an identification of each operating sensor and an identification of a respective backup sensor; and

determining the identification of the respective backup sensor indicated by the identification associated with the identification of the faulty sensor as the backup sensor corresponding to the faulty sensor.

12. A lawn mower, comprising a memory storing a computer program, and a processor, wherein the processor, when executing the computer program, implements a method of claim 1 .

13. The lawn mower according to claim 12 , wherein the correspondence table is a preset correspondence table or a correspondence table obtained from a server based on historical fault data.

14. The lawn mower according to claim 12 , wherein the step of determining the fault type of the faulty sensor according to the operating data of the faulty sensor, the environment data around the lawn mower, and a correspondence table corresponding to the faulty sensor comprises:

determining, in response to the operating data of the faulty sensor and the environment data around the lawn mower satisfy a range of parameters corresponding to the first fault type characterizing a hardware fault, that the fault type of the faulty sensor is the first fault type; and

determining, in response to the operating data of the faulty sensor and the environment data around the lawn mower satisfy a range of parameters corresponding to a second fault type characterizing a software fault, that the fault type of the faulty sensor is the second fault type.

15. The lawn mower according to claim 14 , further comprising:

controlling the faulty sensor to restart in response to the fault type of the faulty sensor is the second fault type.

16. The lawn mower according to claim 12 , wherein comprises:

using a trained fault recognition model to perform fault recognition based on the operating data of the faulty sensor and the environment data around the lawn mower, so as to obtain the fault type of the faulty sensor; wherein a training method for the trained fault recognition model comprises:

obtaining training data, the training data comprising operating data and environment data, and a true fault type of the sample faulty sensor when a fault occurs in a sample faulty sensor, wherein the true fault type comprises the first fault type characterizing a hardware fault and a second fault type characterizing a software fault; and

using the training data to train a fault recognition model to be trained, so as to obtain the trained fault recognition model.

17. The lawn mower according to claim 16 , further comprising:

controlling the faulty sensor to restart in response to the fault type of the faulty sensor is the second fault type.

18. The lawn mower according to claim 12 , before controlling a backup sensor corresponding to the faulty sensor to start operating, further comprising:

determining the backup sensor corresponding to the faulty sensor;

the step of determining the backup sensor corresponding to the faulty sensor comprising:

determining an identification of the faulty sensor;

determining an identification associated with the identification of the faulty sensor according to the identification of the faulty sensor and a preset association relationship, wherein the preset association relationship comprises an association relationship between an identification of each operating sensor and an identification of a respective backup sensor; and

determining the identification of the respective backup sensor indicated by the identification associated with the identification of the faulty sensor as the backup sensor corresponding to the faulty sensor.

19. A computer-readable storage medium having stored thereon a computer program, wherein the computer program, when executed by a processor, implements a method of claim 1 .

20. A lawn mower control device, comprising:

a detection unit configured to detect operating data and sensing data of a plurality of operating sensors provided on a lawn mower, wherein the plurality of operating sensors comprise at least two different types of sensors, the at least two different types of sensors comprise image sensors and position sensors, sensing data of the at least two different types of sensors is configured to obtain an information of obstacle;

a fusion unit configured to fuse the sensing data of the plurality of operating sensors to obtain environment data around the lawn mower, the environment data comprises information of the obstacle;

a determination unit configured to determine, when it is detected that a fault occurs in any of the operating sensors, a fault type of a faulty sensor according to the operating data of the faulty sensor, the environment data around the lawn mower, and a correspondence table corresponding to the faulty sensor, wherein the faulty sensor is an operating sensor in which a fault occurs, the correspondence table comprises a correspondence of various fault types with a range of parameters, the range of parameters comprising a range of operating data and a range of environment data; and

a control unit configured to control, in response to the fault type of the faulty sensor is a first fault type, the faulty sensor to stop operating, and a backup sensor corresponding to the faulty sensor to start operating.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 7, 2025
From: YUAN, LI
To: SHENZHEN MAMMOTION INNOVATION CO., LIMITED
Reel/Frame 070152/0749 →
Priority Claims (1)
CN 202210414693.3 · Apr 20, 2022 · national
Continuity (1)
Related Publication 20250110512A1 · Apr 3, 2025
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