IP Library Granted Patent US 12,642,408
Granted Patent B2
US 12,642,408 · App. 18/197,008 · Granted Jun 2, 2026

Station device on which cordless vacuum cleaner is docked and communication method of the station device

Inventors: Seongu Lee (Suwon-si, KR); Hyunkoo Kang (Suwon-si, KR); Seehyun Kim (Suwon-si, KR); Juhyuk Kim (Suwon-si, KR); Sanghyuk Park (Suwon-si, KR); Yeongju Lee (Suwon-si, KR); Jaeshik Jeong (Suwon-si, KR); Jeonghee Cho (Suwon-si, KR); Sanghwa Choi (Suwon-si, KR)
Assignee: SAMSUNG ELECTRONICS CO., LTD.
A47L9/2873A47L5/26A47L9/0063A47L9/28A47L9/2842A47L9/2857A47L9/2894G06F8/65G06F8/71H04L12/2814H04L67/00H04L67/12A47L2201/02H04L2012/2841H04L2012/285
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 12,642,408
App. No.
18/197,008
Granted
Jun 2, 2026
Kind
B2
Abstract

A communication method of a station device may include receiving a new version of software related to control of a cordless vacuum cleaner from a server device, storing the received new version of software in a memory, identifying whether a preset condition under which the new version of software is downloadable to the cordless vacuum cleaner is satisfied, and when the preset condition is satisfied, transmitting the new version of software stored in the memory to the cordless vacuum cleaner.

Claims (43)

1 . A station device configured to dock a cordless vacuum cleaner and charge a battery of the cordless vacuum cleaner, the station device comprising:

a communication interface configured to communicate with the cordless vacuum cleaner and a server device;

a charging terminal configured to charge the battery of the cordless vacuum cleaner;

a memory storing one or more instructions; and

at least one processor configured to:

receive a new version of software related to control of the cordless vacuum cleaner from the server device through the communication interface of the station device;

store the received new version of software in the memory of the station device;

identify whether a preset condition under which the new version of software is downloadable to the cordless vacuum cleaner is satisfied; and

when the preset condition is satisfied, transmit the new version of software stored in the memory of the station device to the cordless vacuum cleaner through the communication interface of the station device.

2 . The station device of claim 1 , wherein the communication interface is further configured to communicate with the server device through a first communication scheme and communicate with the cordless vacuum cleaner through a second communication scheme that is different from the first communication scheme.

3 . The station device of claim 2 , wherein the first communication scheme comprises a Wireless Fidelity (Wi-Fi)™ communication scheme, and

the second communication scheme comprises a Bluetooth Low Energy (BLE) communication scheme.

4 . The station device of claim 1 , wherein the preset condition comprises at least one of a condition for communication connection with the cordless vacuum cleaner or a condition for a docking state of the cordless vacuum cleaner.

5 . The station device of claim 1 , wherein the software related to control of the cordless vacuum cleaner comprises an artificial intelligence (AI) model trained to infer a usage environment state of a brush device, based on data related to flow path pressure inside the cordless vacuum cleaner and data related to a load of the brush device connected to the cordless vacuum cleaner.

6 . The station device of claim 5 , wherein the AI model comprises at least one of a support vector machine (SVM) model, a neural network model, a random forest model, or a graphical model.

7 . The station device of claim 5 , wherein the usage environment state of the brush device comprises at least one of a state of a surface to be cleaned on which the brush device is located, a relative position state of the brush device within the surface to be cleaned, or a state of the brush device being lifted from the surface to be cleaned.

8 . The station device of claim 1 , wherein the new version of software comprises a new version of an AI model trained to additionally infer a new usage environment state.

9 . The station device of claim 1 , wherein the new version of software comprises a new AI model corresponding to a new type of a brush device.

10 . The station device of claim 1 , wherein the new version of software comprises a control algorithm related to an operation mode newly added to the cordless vacuum cleaner or a diagnosis algorithm for diagnosing the state of the cordless vacuum cleaner.

11 . The station device of claim 10 , wherein the control algorithm comprises an algorithm for controlling power consumption of a suction motor in the cordless vacuum cleaner or revolutions per minute (RPM) of a rotating brush of a brush device connected to the cordless vacuum cleaner.

12 . The station device of claim 1 , wherein the new version of software comprises a new algorithm for controlling at least one of RPM of a rotating brush, trip level, or setting values of a lighting device of a new type of a brush device.

13 . The station device of claim 1 , wherein the at least one processor is further configured to periodically compare first version information of software installed on the cordless vacuum cleaner with second version information of software registered in the server device, and

when the first version information is different from the second version information, receive the new version of software from the server device.

14 . The station device of claim 13 , wherein the at least one processor is further configured to:

receive, from the cordless vacuum cleaner, the first version information of the software installed on the cordless vacuum cleaner; and

receive, from the server device, the second version information of the software registered in the server device.

15 . A communication method of a station device configured to dock a cordless vacuum cleaner and charge a battery of the cordless vacuum cleaner, the communication method comprising:

receiving, by at least one processor of the station device, a new version of software related to control of the cordless vacuum cleaner from a server device through a communication interface of the station device;

storing, by the at least one processor of the station device, the received new version of software in a memory of the station device;

identifying, by the at least one processor of the station device, whether a preset condition under which the new version of software is downloadable to the cordless vacuum cleaner is satisfied; and

when the preset condition is satisfied, transmitting, by the at least one processor of the station device, the new version of software stored in the memory of the station device to the cordless vacuum cleaner through the communication interface of the station device,

wherein the station device is configured to charge the battery of the cordless vacuum cleaner.

16 . The communication method of claim 15 , wherein the communication interface of the station device is configured to communicate with the server device through a first communication scheme and communicate with the cordless vacuum cleaner through a second communication scheme that is different from the first communication scheme,

the first communication scheme comprises a Wireless Fidelity (Wi-Fi)™ communication scheme, and

the second communication scheme comprises a Bluetooth Low Energy (BLE) communication scheme.

17 . The communication method of claim 15 , wherein the identifying of whether the preset condition is satisfied comprises identifying whether a communication channel with the cordless vacuum cleaner has been established or identifying whether the cordless vacuum cleaner is docked on the station device.

18 . The communication method of claim 15 , wherein the software related to control of the cordless vacuum cleaner comprises an artificial intelligence (AI) model trained to infer a usage environment state of a brush device, based on data related to flow path pressure inside the cordless vacuum cleaner and data related to a load of the brush device connected to the cordless vacuum cleaner, and

the new version of software related to control of the cordless vacuum cleaner comprises a new version of an AI model trained to additionally infer a new usage environment state or a new AI model corresponding to a new type of the brush device.

19 . The communication method of claim 15 , wherein the new version of software comprises a control algorithm related to an operation mode newly added to the cordless vacuum cleaner or a diagnosis algorithm for diagnosing the state of the cordless vacuum cleaner, and

the control algorithm comprises an algorithm for controlling power consumption of a suction motor in the cordless vacuum cleaner or revolutions per minute (RPM) of a rotating brush of a brush device connected to the cordless vacuum cleaner.

20 . The communication method of claim 15 , wherein the receiving of the new version of software from the server device comprises:

periodically comparing first version information of software installed on the cordless vacuum cleaner with second version information of software registered in the server device; and

when the first version information is different from the second version information, receiving the new version of software from the server device.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 23, 2024
From: LEE, SEONGU; KANG, HYUNKOO; KIM, SEEHYUN; KIM, JUHYUK; PARK, SANGHYUK; LEE, YEONGJU; JEONG, JAESHIK; CHO, JEONGHEE; CHOI, SANGHWA
To: SAMSUNG ELECTRONICS CO., LTD.
Reel/Frame 068055/0652 →
Priority Claims (2)
KR 10-2022-0059225 · May 13, 2022 · national
KR 10-2022-0156792 · Nov 21, 2022 · national
Continuity (2)
Continuation PCTKR2023006218 · May 8, 2023
Related Publication 20230363603A1 · Nov 16, 2023
References Cited (36)
US 5722109A · Delmas et al. · 1998 [cited by applicant]
US 8683645B2 · Glassman · 2014 [cited by applicant]
US 10681864B2 · Matt et al. · 2020 [cited by applicant]
US 20160066759A1 · Langhammer · 2016 [cited by examiner]
US 20180078107A1 · Gagnon · 2018 [cited by examiner]
US 20200221633A1 · Einecke et al. · 2020 [cited by applicant]
US 20210089040A1 · Ebrahimi Afrouzi et al. · 2021 [cited by applicant]
US 20210169290A1 · No · 2021 [cited by applicant]
US 20210251451A1 · Ko et al. · 2021 [cited by applicant]
US 20220032450A1 · Kim et al. · 2022 [cited by applicant]
US 20220354327A1 · Kim et al. · 2022 [cited by applicant]
US 20240118708A1 · Yang et al. · 2024 [cited by applicant]
EP 4057569A1 · 2022 [cited by examiner]
EP 4505926A1 · 2025 [cited by applicant]
JP H05192279A · 1993 [cited by applicant]
JP H0759698A · 1995 [cited by applicant]
JP 6884596B2 · 2021 [cited by examiner]
JP 2021168826A · 2021 [cited by applicant]
KR 101179592B1 · 2012 [cited by applicant]
KR 20120114669A · 2012 [cited by applicant]
KR 20190069216A · 2019 [cited by applicant]
KR 20200009680A · 2020 [cited by applicant]
KR 20200027320A · 2020 [cited by applicant]
KR 20200068033A · 2020 [cited by applicant]
KR 20200119063A · 2020 [cited by applicant]
KR 20210073058A · 2021 [cited by applicant]
KR 20210073120A · 2021 [cited by applicant]
KR 20210105207A · 2021 [cited by applicant]
KR 20220046860A · 2022 [cited by applicant]
KR 102427836B1 · 2022 [cited by examiner]
TW 201429438A · 2014 [cited by examiner]
WO WO2013175933A1 · 2013 [cited by examiner]
WO 2021133105A1 · 2021 [cited by applicant]
Robotic vacuum cleaner, Wikipedia, 2021, 7 pages, [retrieved on Jan. 15, 2026], Retrieved from the Internet: <URL:https://web.archive.org/web/20211218190109/https://en.wikipedia.org/wiki/Robotic_vacuum_cleaner>. [cited by examiner]
International Search Report and Written Opinion for International Application No. PCT/KR2023/006218; International Filing Date May 8, 2023; Date of Mailing Aug. 16, 2023; 10 Pages. [cited by applicant]
Extended European Search Report corresponding to Application No. 23803785.7-1215; Dated Mar. 27, 2025. [cited by applicant]