IP Library Granted Patent US 12,429,868
Granted Patent B2
US 12,429,868 · App. 18/215,817 · Granted Sep 30, 2025

Method and device for determining motion parameter of autonomous mobile device

Inventors: Xingguo Xing (Beijing, CN); Rui Zhu (Beijing, CN); Minsheng Wu (Beijing, CN); Xin Wu (Beijing, CN)
Assignee: QFEELTECH (BEIJING) CO., LTD.
G05D1/0055G05D1/0238G05D1/0253G06T7/246G06T2207/30252
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,429,868
App. No.
18/215,817
Granted
Sep 30, 2025
Kind
B2
Abstract

The present disclosure provides a method and a device for determining a motion parameter of an autonomous mobile device. The method includes: an anti-fall sensor detects a current chassis-floor distance between a chassis of the autonomous mobile device and a current floor, and transmits the current chassis-floor distance to a processor; the processor determines a correction coefficient corresponding to the current chassis-floor distance; the processor obtains an output of an optic flow sensor; the processor determines the motion parameter corresponding to the current chassis-floor distance based on a correction coefficient, a calibration coefficient, and the output of the optic flow sensor, which increases the accuracy of the motion parameter obtained through computation.

Claims (70)

1. A method for determining a motion parameter of an autonomous mobile device, comprising:

detecting, by an anti-fall sensor of the autonomous mobile device, a current chassis-floor distance between a chassis of the autonomous mobile device and a current floor, and transmitting the current chassis-floor distance to a processor of the autonomous mobile device;

determining, by the processor, a correction coefficient corresponding to the current chassis-floor distance;

obtaining, by the processor, an output of an optic flow sensor of the autonomous mobile device; and

determining, by the processor, the motion parameter based on multiplying the correction coefficient, a calibration coefficient, and the output of the optic flow sensor to obtain the motion parameter corresponding to the current chassis-floor distance,

wherein the calibration coefficient is, when the autonomous mobile device moves at a calibrated chassis-floor distance, a correspondence relationship between the output of the optic flow sensor and an actual motion parameter,

wherein the correction coefficient is used to correct the calibration coefficient, when the current chassis-floor distance is different from the calibrated chassis-floor distance, to obtain the motion parameter corresponding to the current chassis-floor distance, and

wherein the motion parameter includes at least one of a displacement or a velocity.

2. The method of claim 1 ,

wherein the actual motion parameter is an actual displacement,

wherein the calibration coefficient is obtained through the following steps:

obtaining, by the processor, when the autonomous mobile device moves at the calibrated chassis-floor distance, the actual displacement of the autonomous mobile device and the output of the optic flow sensor, wherein the actual displacement is a displacement actually measured through a length measuring tool; and

calculating, by the processor, the calibration coefficient as a ratio between the actual displacement and the output of the optic flow sensor.

3. The method of claim 1 , wherein determining, by the processor, the correction coefficient corresponding to the current chassis-floor distance, comprises:

obtaining, by the processor, the correction coefficient through inquiring a pre-stored mapping relationship or through computation, wherein the mapping relationship is a correspondence relationship between multiple to-be-detected chassis-floor distances and correction coefficients,

wherein the mapping relationship is obtained through the following steps:

for the multiple to-be-detected chassis-floor distances, when the optic flow sensor moves at the multiple to-be-detected chassis-floor distances, obtaining, by the processor, actual displacements of the optic flow sensor and outputs of the optic flow sensor;

calculating, by the processor, a correspondence coefficient of a to-be-detected chassis-floor distance as, when the optic flow sensor moves at each to-be-detected chassis-floor distance, a ratio between an actual displacement of the optic flow sensor and an output of the optic flow sensor; and

calculating, by the processor, the correction coefficient corresponding to the to-be-detected chassis-floor distance as a ratio between the correspondence coefficient of the to-be-detected chassis-floor distance and the calibration coefficient, and forming, by the processor, the mapping relationship based on the multiple to-be-detected chassis-floor distances and the corresponding correction coefficients.

4. The method of claim 1 , wherein prior to determining, by the processor, the correction coefficient corresponding to the current chassis-floor distance, the method further comprises:

determining, by the processor, whether a changing frequency of the chassis-floor distance within a predetermined time period exceeds a predetermined value; and

when the predetermined value is exceeded, executing, by the processor, an alarming process.

5. An autonomous mobile device, comprising:

an optic flow sensor;

a processor; and

an anti-fall sensor that detects a current chassis-floor distance between a chassis of the autonomous mobile device and a current floor on which the autonomous mobile device is disposed, and transmits the current chassis-floor distance to the processor;

wherein the processor is configured to:

determine a correction coefficient corresponding to the current chassis-floor distance;

obtain an output of the optic flow sensor; and

determine a motion parameter corresponding to the current chassis-floor distance based on the correction coefficient, a calibration coefficient, and the output of the optic flow sensor,

wherein the calibration coefficient is, when the autonomous mobile device moves at a calibrated chassis-floor distance, a correspondence relationship between the output of the optic flow sensor and an actual motion parameter,

wherein the processor determines the motion parameter based on multiplying the correction coefficient, the calibration coefficient, and the output of the optic flow sensor to obtain the motion parameter corresponding to the current chassis-floor distance,

wherein the processor corrects the calibration coefficient using the correction coefficient, when the current chassis-floor distance is different from the calibrated chassis-floor distance, to obtain the motion parameter corresponding to the current chassis-floor distance, and

wherein the motion parameter includes at least one of a displacement or a velocity.

6. The autonomous mobile device of claim 5 ,

wherein the actual motion parameter is an actual displacement, and

wherein the processor obtains the calibration coefficient by:

obtaining, when the autonomous mobile device moves at the calibrated chassis-floor distance, the actual displacement of the autonomous mobile device and the output of the optic flow sensor, wherein the actual displacement is a displacement actually measured through a length measuring tool; and

calculating the calibration coefficient as a ratio between the actual displacement and the output of the optic flow sensor.

7. The autonomous mobile device of claim 5 , wherein when the processor determines the correction coefficient corresponding to the current chassis-floor distance, the processor obtains the correction coefficient through inquiring a pre-stored mapping relationship or through computation, wherein the mapping relationship is a correspondence relationship between multiple to-be-detected chassis-floor distances and correction coefficients,

wherein the processor obtains the mapping relationship through the following steps:

for the multiple to-be-detected chassis-floor distances, when the optic flow sensor moves at the multiple to-be-detected chassis-floor distances, obtaining, by the processor, actual displacements of the optic flow sensor and outputs of the optic flow sensor;

calculating, by the processor, a correspondence coefficient of a to-be-detected chassis-floor distance as, when the optic flow sensor moves at each to-be-detected chassis-floor distance, a ratio between an actual displacement of the optic flow sensor and an output of the optic flow sensor; and

calculating, by the processor, the correction coefficient corresponding to the to-be-detected chassis-floor distance as a ratio between the correspondence coefficient of the to-be-detected chassis-floor distance and the calibration coefficient, and forming, by the processor, the mapping relationship based on the multiple to-be-detected chassis-floor distances and the corresponding correction coefficients.

8. The autonomous mobile device of claim 5 , wherein the processor is configured to:

prior to determining the correction coefficient corresponding to the current chassis-floor distance:

determine whether a changing frequency of the chassis-floor distance within a predetermined time period exceeds a predetermined value; and

when the predetermined value is exceeded, execute an alarming process.

9. A non-transitory computer-readable storage medium storing computer-executable instructions, which when executed by a processor of an autonomous mobile device, cause the autonomous mobile device to perform a method comprising:

detecting, by an anti-fall sensor of the autonomous mobile device, a current chassis-floor distance between a chassis of the autonomous mobile device and a current floor, and transmitting the current chassis-floor distance to the processor;

determining, by the processor, a correction coefficient corresponding to the current chassis-floor distance;

obtaining, by the processor, an output of an optic flow sensor of the autonomous mobile device; and

determining, by the processor, the motion parameter based on multiplying the correction coefficient, a calibration coefficient, and the output of the optic flow sensor to obtain the motion parameter corresponding to the current chassis-floor distance;

wherein the calibration coefficient is, when the autonomous mobile device moves at a calibrated chassis-floor distance, a correspondence relationship between the output of the optic flow sensor and an actual motion parameter,

wherein the correction coefficient is used to correct the calibration coefficient, when the current chassis-floor distance is different from the calibrated chassis-floor distance, to obtain the motion parameter corresponding to the current chassis-floor distance, and

wherein the motion parameter includes at least one of a displacement or a velocity.

10. The non-transitory computer-readable storage medium of claim 9 ,

wherein the actual motion parameter is an actual displacement, and

wherein the calibration coefficient is obtained through the following steps:

obtaining, by the processor, when the autonomous mobile device moves at the calibrated chassis-floor distance, the actual displacement of the autonomous mobile device and the output of the optic flow sensor, wherein the actual displacement is a displacement actually measured through a length measuring tool; and

calculating, by the processor, the calibration coefficient as a ratio between the actual displacement and the output of the optic flow sensor.

11. The non-transitory computer-readable storage medium of claim 9 , wherein determining, by the processor, the correction coefficient corresponding to the current chassis-floor distance, comprises:

obtaining, by the processor, the correction coefficient through inquiring a pre-stored mapping relationship or through computation, wherein the mapping relationship is a correspondence relationship between multiple to-be-detected chassis-floor distances and correction coefficients,

wherein the mapping relationship is obtained through the following steps:

for the multiple to-be-detected chassis-floor distances, when the optic flow sensor moves at the multiple to-be-detected chassis-floor distances, obtaining, by the processor, actual displacements of the optic flow sensor and outputs of the optic flow sensor;

calculating, by the processor, a correspondence coefficient of a to-be-detected chassis-floor distance as, when the optic flow sensor moves at each to-be-detected chassis-floor distance, a ratio between an actual displacement of the optic flow sensor and an output of the optic flow sensor; and

calculating, by the processor, the correction coefficient corresponding to the to-be-detected chassis-floor distance as a ratio between the correspondence coefficient of the to-be-detected chassis-floor distance and the calibration coefficient, and forming, by the processor, the mapping relationship based on the multiple to-be-detected chassis-floor distances and the corresponding correction coefficients.

12. The non-transitory computer-readable storage medium of claim 9 , wherein prior to determining, by the processor, the correction coefficient corresponding to the current chassis-floor distance, the method further comprises:

determining, by the processor, whether a changing frequency of the chassis-floor distance within a predetermined time period exceeds a predetermined value; and

when the predetermined value is exceeded, executing, by the processor, an alarming process.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 25, 2023
From: XING, XINGGUO; ZHU, RUI; WU, MINSHENG; WU, XIN
To: QFEELTECH (BEIJING) CO., LTD.
Reel/Frame 065660/0076 →
NOTICE OF GRANT OF SECURITY INTEREST IN PATENTS Recorded Jul 20, 2023
From: SHARKNINJA OPERATING LLC
To: BANK OF AMERICA, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 064600/0098 →