ROBOT CLEANER AND CONTROLLING METHOD OF THE SAME

• US 20120106829A1
• Filed: 10/26/2011
• Published: 05/03/2012
• Est. Priority Date: 11/03/2010
• Status: Active Grant

• Current Assignee: LG Electronics, Inc. (LG Corporation)
• Original Assignee: LG Electronics, Inc. (LG Corporation)
• Inventors: Lee, Seongsu, Baek, Seungmin, Na, Sangik, Oh, Se-Young, Joo, Kwangro, Yoon, Jeongsuk, Kim, Yiebin, LEE, Tae-Kyeong, Baek, Sanghoon
• Granted Patent: US 8,705,842 B2
• Time in Patent Office: Days
• US Class Current: 382/153
• CPC Class Codes: G05D 1/0242 using non-visible light signals, e.g. IR or UV signals
• CPC Class Codes: G05D 1/0255 using acoustic signals, e.g. ultra-sonic singals sonar systems designed for anti-collision purposes G01S15/93
• CPC Class Codes: G05D 1/0272 comprising means for registering the travel distance, e.g. revolutions of wheels measuring distance traversed on the ground by vehicles, e.g. using odometers G01C22/00
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30

Abstract

A robot cleaner and a method for controlling the same are provided. A region to be cleaned may be divided into a plurality of sectors based on detection data collected by a detecting device, and a partial map for each sector may be generated. A full map of the cleaning region may then be generated based on a position of a partial map with respect to each sector, and a topological relationship between the partial maps. Based on the full map, the robot cleaner may recognize its position, allowing the entire region to be completely cleaned, and allowing the robot cleaner to rapidly move to sectors that have not yet been cleaned.

Claims

1. A robot cleaner that divides a full region into one or more sectors to perform a cleaning operation, the robot cleaner comprising:

one or more detecting devices configured to detect objects within the one or more sectors and configured to output corresponding detection data; and

a controller configured to generate a partial map for each of the one or more sectors based on the detection data, and configured to generate a full map corresponding to the full region based on a relative position of the one or more sectors.

2. The robot cleaner of claim 1, wherein the controller comprises:

a feature line extracting module configured to extract one or more feature lines for each of the one or more sectors based on the detection data; and

a partial map generating module configured to generate a partial map for each of the one or more sectors based on the one or more feature lines.

3. The robot cleaner of claim 2, wherein the partial map generating module compensates for an orientation direction of a corresponding sector based on the one or more feature lines, and generates the partial map based on the compensated sector.

4. The robot cleaner of claim 2, wherein the controller further comprises a position recognizing module configured to recognize a position of each of the one or more sectors based on the detection data and the one or more feature lines.

5. The robot cleaner of claim 2, wherein the controller further comprises a full map generating module configured to generate a topological map indicating a position of each of the one or more sectors and a relative position between the one or more sectors, and configured to generate the full map based on the topological map.

6. The robot cleaner of claim 5, wherein the one or more sectors comprises a plurality of sectors, and wherein the full map generating module matches feature lines respective corresponding to two separate sectors, and determines whether the two separate sectors overlap each other based on a level of matching of the feature lines.

7. The robot cleaner of claim 6, wherein the full map generating module compensates for the topological map based on a position error between the two overlapping sectors, and generates the full map based on the compensated topological map.

8. A method of controlling a robot cleaner, the method comprising:

dividing a cleaning region into a plurality of sectors;

detecting objects within each of the plurality of sectors;

generating a partial map for each of the plurality of sectors based on the detection of objects within each of the plurality of sectors; and

generating a full map of the cleaning region based on a relative position of the partial maps corresponding to the plurality of sectors.

9. The method of claim 8, further comprising extracting one or more feature lines based on the detection of objects within each of the plurality of sectors, wherein generating a partial map comprises generating a partial map using the one or more feature lines.

10. The method of claim 9, wherein generating a partial map further comprises:

compensating for an orientation of each of the plurality of sectors using the respective one or more feature lines; and

generating a partial map for each of the plurality of sectors based on the compensation.

11. The method of claim 9, wherein extracting one or more feature lines comprises:

accumulating detection data;

extracting a plurality of feature points from the detection data;

grouping the plurality of feature points into respective clusters to form feature lines; and

calculating a length and a reliability of the feature lines of each of the clusters.

12. The method of claim 9, wherein generating a partial map includes:

determining validity of a corresponding one of the one or more feature lines extracted from detection data based on an object detected while moving along an outer peripheral surface of each sector; and

updating an importance level of the detection data if it is determined that the feature line is valid.

13. The method of claim 12, wherein generating a partial map further comprises:

determining whether a current feature line extracted from the detection data is similar to a previously-extracted feature line; and

merging the current and previously-extracted feature lines together if it is determined that they are similar to each other.

14. The method of claim 10, wherein compensating for an orientation of each of the plurality of sectors comprises calculating a compensation amount assuming feature lines of the sector are substantially perpendicular to each other, and adjusting the orientation of the sector based on the calculated compensation amount.

15. The method of claim 9, further comprising compensating for a position of each of the plurality of sectors based on the respective detection of objects within each of the plurality of sectors and the one or more feature lines respectively corresponding to each of the plurality of sectors.

16. The method of claim 15, wherein compensating for a position comprises:

determining whether a feature line extracted from detection data collected corresponding to an object detected while moving along an outer peripheral surface of a sector is valid;

updating an importance of the detection data if it is determined that the feature line is valid; and

compensating for a position based on the updated importance of the detection data.

17. The method of claim 8, wherein generating a full map comprises:

generating a topological map based on a position of each of the partial maps and relative positions between adjacent partial maps; and

generating the full map based on the topological map.

18. The method of claim 17, wherein generating the full map further comprises:

merging feature lines within two sectors;

determining whether the two sectors overlap each other based on a result of the merging; and

adjusting the topological map based on a position error between the two sectors that overlap each other.

19. A storage medium including an algorithm provided therein, the algorithm comprising:

dividing a full region into a plurality of sectors;

detecting objects with the plurality of sectors;

extracting one or more feature lines based on the detection of objects within the plurality of sectors;

generating a partial map for each of the plurality of sectors using the one or more feature lines; and

generating a full map of the full region based on a relative position of the partial maps.

20. The algorithm of claim 19, further comprising generating a topological map based on a position of each partial map and a relative position between the partial maps.