Adaptive mapping with spatial summaries of sensor data

• US 9,404,756 B2
• Filed: 11/17/2015
• Issued: 08/02/2016
• Est. Priority Date: 09/30/2011
• Status: Active Grant

• Current Assignee: iRobot Corporation
• Original Assignee: iRobot Corporation
• Inventors: Fong, Philip, Eade, Ethan, Munich, Mario E.
• Primary Examiner(s): Tarcza, Thomas
• Assistant Examiner(s): GOLDMAN, RICHARD A
• Application Number:
  US14/944,152
• Publication Number:
  US 20160069691A1
• Time in Patent Office: 259 Days
• Field of Search: 701/400, 701/409, 701/445, 701/446, 701/447, 701/448, 701/450, 701/451, 701/23, 701/25, 701/26, 701/517, 701/532, 700/259, 700/25, 700/3, 700/258, 702/150, 702/151, 702/152
• US Class Current: 1/1
• CPC Class Codes: G01C 21/20 Instruments for performing navigational calculations G01C21/24, G01C21/26 take precedence
• CPC Class Codes: G01C 21/206 specially adapted for indoor navigation
• CPC Class Codes: G01C 21/3881 Tile-based structures
• CPC Class Codes: G05B 15/00 Systems controlled by a computer G05B13/00, G05B19/00 take precedence; automatic controllers with particular characteristics G05B11/00
• 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: G05D 1/0238 using obstacle or wall sensors G05D1/0246 and G05D1/0289 take precedence; lidar systems designed for anti-collision purposes G01S17/93
• CPC Class Codes: G05D 1/0246 using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: Y10S 901/00 Robots

Abstract

A system and method for mapping parameter data acquired by a robot mapping system is disclosed. Parameter data characterizing the environment is collected while the robot localizes itself within the environment using landmarks. Parameter data is recorded in a plurality of local grids, i.e., sub-maps associated with the robot position and orientation when the data was collected. The robot is configured to generate new grids or reuse existing grids depending on the robot'"'"'s current pose, the pose associated with other grids, and the uncertainty of these relative pose estimates. The pose estimates associated with the grids are updated over time as the robot refines its estimates of the locations of landmarks from which determines its pose in the environment. Occupancy maps or other global parameter maps may be generated by rendering local grids into a comprehensive map indicating the parameter data in a global reference frame extending the dimensions of the environment.

Claims

1. A method of generating a map using mapping parameters acquired by a mobile robotic system in an environment, the method comprising:

for a given local grid in a plurality of local grids;

mapping by the mobile robotic system local parameter data to a corresponding grid, wherein the corresponding grid includes a two dimensional Cartesian representation depicting;

locations of obstacles detected by the mobile robotic system within the environment;

spaces traversed by the mobile robotic system within the environment; and

merging by the mobile robotic system parameter data from the plurality of local grids into one or more spatial summaries in response to one or more of;

elapsed time,

space covered by the mobile robotic system or area mapped by the mobile robotic system,

a grid memory limitation, or

total number of grids or anchor nodes.

2. The method as defined in claim 1, wherein an origin of the two dimensional Cartesian representation coincides with a starting position of the mobile robotic system.

3. The method as defined in claim 1, wherein the given local grid comprises a map of local parameter data located relative to an anchor node, wherein the anchor node represents an estimate of a pose of the mobile robotic system at a location.

4. The method as defined in claim 1, wherein the locations of obstacles detected by the mobile robotic system within the environment comprises obstacles detected by a bump sensor.

5. The method as defined in claim 1, wherein the obstacles detected by the mobile robotic system within the environment comprise walls.

6. A method of generating a map using mapping parameters acquired by a mobile robotic system in an environment, the method comprising:

mapping by the mobile robotic system parameter data to a grid that includes a two dimensional Cartesian representation depicting;

locations of obstacles detected by the mobile robotic system within the environment;

spaces traversed by the mobile robotic system within the environment.

7. The method as defined in claim 6, the method comprising:

merging by the mobile robotic system parameter data from a plurality of grids into a spatial summary in response to one or more of;

elapsed time,

space covered by the mobile robotic system or area mapped by the mobile robotic system,

a grid memory limitation, or

total number of grids or anchor nodes;

wherein;

an origin of the two dimensional Cartesian representation coincides with a starting position of the mobile robotic system,

a given grid in the plurality of grids comprises a map of local parameter data located relative to an anchor node, wherein the anchor node represents an estimate of a pose of the mobile robotic system at a location, and

the locations of obstacles detected by the mobile robotic system within the environment comprises obstacles detected by a bump sensor.

8. The method as defined in claim 6, wherein an origin of the two dimensional Cartesian representation coincides with a starting position of the mobile robotic system.

9. The method as defined in claim 6, wherein the grid comprises a map of local parameter data located relative to an anchor node, wherein the anchor node represents an estimate of a pose of the mobile robotic system at a location.

10. The method as defined in claim 6, wherein the locations of obstacles detected by the mobile robotic system within the environment comprises obstacles detected by a bump sensor.

11. The method as defined in claim 6, wherein the obstacles detected by the mobile robotic system within the environment comprise walls.