Carpet drift estimation using differential sensors or visual measurements

• US 9,223,312 B2
• Filed: 06/07/2013
• Issued: 12/29/2015
• Est. Priority Date: 06/08/2012
• Status: Active Grant

• Current Assignee: iRobot Corporation
• Original Assignee: iRobot Corporation
• Inventors: Goel, Dhiraj, Eade, Ethan, Fong, Philip, Munich, Mario E.
• Primary Examiner(s): Patton, Spencer
• Assistant Examiner(s): MOTT, ADAM R
• Application Number:
  US13/913,258
• Publication Number:
  US 20130331988A1
• Time in Patent Office: 935 Days
• Field of Search: 700/245, 700/253, 700/254
• US Class Current: 1/1
• CPC Class Codes: B25J 11/0085 Cleaning
• CPC Class Codes: B25J 5/007 mounted on wheels
• CPC Class Codes: B25J 9/1628 characterised by the control loop
• CPC Class Codes: B25J 9/1664 characterised by motion, path, trajectory planning
• CPC Class Codes: B25J 9/1697 Vision controlled systems
• CPC Class Codes: G05D 1/0253 extracting relative motion information from a plurality of images taken successively, e.g. visual odometry, optical flow determining position or orientation from images G06T7/70
• CPC Class Codes: G05D 1/0268 using internal positioning means
• CPC Class Codes: G05D 1/027 comprising intertial navigation means, e.g. azimuth detector inertial navigation G01C21/16; inertial navigation combined with non-inertial navigation instruments G01C21/165
• 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 1/24 Arrangements for determining position or orientation
• CPC Class Codes: G05D 1/244 using passive navigation aids external to the vehicle, e.g. markers, reflectors or magnetic means
• CPC Class Codes: G05D 1/40 Control within particular dimensions
• CPC Class Codes: G05D 1/644 Optimisation of travel parameters, e.g. of energy consumption, journey time or distance
• CPC Class Codes: Y10S 901/01 Mobile robot

Abstract

Apparatus and methods for carpet drift estimation are disclosed. In certain implementations, a robotic device includes an actuator system to move the body across a surface. A first set of sensors can sense an actuation characteristic of the actuator system. For example, the first set of sensors can include odometry sensors for sensing wheel rotations of the actuator system. A second set of sensors can sense a motion characteristic of the body. The first set of sensors may be a different type of sensor than the second set of sensors. A controller can estimate carpet drift based at least on the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors.

Claims

1. A robotic device comprising:

a body;

an actuator system configured to move the body across a surface;

a first set of sensors configured to sense an actuation characteristic of the actuator system;

a second set of sensors configured to sense a motion characteristic of the body, the first set of sensors being a different type of sensor than the second set of sensors; and

a controller configured to;

estimate drift based at least on the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors;

determine from the estimated drift if the robotic device is on a carpeted or a non-carpeted surface;

in response to determination that robotic device is on a carpeted surface generate a carpet drift vector based at least on;

the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors; and

generate commands, using the carpet drift vector, configured to compensate for carpet drift;

send the generated commands to the actuator system to compensate for carpet drift.

2. The robotic device of claim 1, wherein the actuator system includes a rotatable wheel and the first set of sensors is configured to sense rotation of the wheel of the actuator system, and wherein the second set of sensors includes a gyroscopic sensor configured to sense rotation of the body.

3. The robotic device of claim 1, wherein:

the actuator system includes a rotatable wheel and the first set of sensors is configured to sense rotation of the wheel of the actuator system,

the second set of sensors includes a gyroscopic sensor configured to sense rotation of the body, and

the controller is further configured to estimate drift based at least on a comparison between a heading estimated from the sensed wheel rotation and a heading estimated from the sensed body rotation.

4. The robotic device of claim 1, wherein the controller is further configured to control the actuator system to perform a maneuver that rotates the body at least 180 degrees, and wherein the controller is further configured to estimate drift based at least on a plurality of comparisons between actuation characteristics and motion characteristics sensed during the maneuver.

5. The robotic device of claim 4, wherein the controller is further configured to estimate a magnitude of the drift based at least on a ratio of total drift to change of heading during a maneuver.

6. The robotic device of claim 1, wherein the controller is further configured to update the estimated drift based at least on a plurality of comparisons between actuation characteristics and motion characteristics sensed during a maneuver in response to detecting an obstacle.

7. The robotic device of claim 1, wherein:

the actuator system includes a rotatable wheel and the first set of sensors is configured to sense rotation of the wheel of the actuator system,

the second set of sensors includes an image sensor configured to capture two or more images, and

the controller is configured to;

estimate the motion characteristic by comparing the two or more images;

detect a common feature in each of the two or more images;

estimate the heading of the body based at least on comparing a change in a relative position of the common feature detected in the two or more images;

apply updates when on a carpeted surface to the generated carpet drift vector based at least on the comparison of the two or more images.

8. A robotic device comprising:

a left rotatable drive wheel and a right rotatable drive wheel;

a drive sub-system configured to rotate the left rotatable drive wheel and the right rotatable drive wheels differentially using a drive signal such that the robotic device moves over a carpet surface;

a first set of sensors configured to generate odometry measurements of rotations of the left rotatable drive wheel and the right rotatable drive wheel;

a second set of sensors configured to generate heading measurements of the robotic device; and

a controller configured to generate the drive signal such that the robotic device performs a maneuver having a change in heading angle, wherein the controller is further configured to;

estimate a drift based at least on estimates of change in heading during the maneuver and changes in the heading measurements during the maneuver, the estimates of changes in heading being based on the odometry measurements during the maneuver;

determine from the estimated drift if the robotic device is on a carpeted or a non-carpeted surface;

in response to a determination that the robotic device is on a carpeted surface periodically compare changes in estimated heading to changes in the heading measurements throughout a maneuver to generate multiple carpet drift estimates;

determine from the multiple carpet drift estimates if the robotic device is on a multi-carpeted surface;

generate commands, using one or more carpet drift vectors based at least on the multiple carpet drift estimates, configured to compensate for carpet drift; and

send the generated commands to the drive sub-system to compensate for carpet drift and to maintain the robot on a planned path.

9. The robotic device of claim 8, wherein the controller is further configured to continue the maneuver at least until the heading measurement indicates a change in heading of at least 180 degrees, wherein the controller is further configured to collect a plurality of odometry measurements during the maneuver, wherein the controller is further configured to collect a plurality of heading measurements during the maneuver, and wherein the controller is further configured to estimate the carpet drift based at least on comparisons between the plurality of odometry measurements and the plurality of heading measurements.

10. The robotic device of claim 8, wherein the controller is further configured to estimate the drift at least partly in response to encountering an obstacle.

11. The robotic device of claim 8, wherein the controller is further configured to estimate the drift in response to traveling a distance greater than a threshold distance since a previous estimate was performed.

12. The robotic device of claim 8, wherein the controller is further configured to adjust the odometry measurements based on the estimated drift.

13. A robotic device comprising:

an actuator system further configured to move the robotic device across a carpet surface;

a set of sensors configured to generate measurements of an actuation characteristic; and

a controller communicatively coupled to the set of sensors, wherein the controller is configured to generate odometry estimates based on the measurements of the actuation characteristic, and wherein the controller is further configured to;

estimate drift based at least on the odometry estimates and visual observations of motion, the visual observations of motion being based at least on two or more images of the images captured by a camera;

determine from the estimated carpet drift if the robotic device is on a carpeted or a non-carpeted surface;

in response to determination that robotic device is on a carpeted surface generate a carpet drift vector based at least on;

the actuation characteristic measurements and the visual observations of motion based at least on two or more images of the images captured by the camera; and

generate commands, using the carpet drift vector, configured to compensate for carpet drift;

send the generated commands to the actuator system to compensate for carpet drift.

14. The robotic device of claim 13, further comprising the camera, wherein the controller is further configured to:

generate the visual observations of motion of the robotic device based at least on two or more images of the images captured by the camera;

extract features from the two or more images;

match the extracted features from the two or more images;

generate the visual observations of motion based on a motion of matching features relative to the two or more images; and

apply updates when on a carpeted surface to the generated carpet drift vector based at least on the comparison of the two or more images.

15. The robotic device of claim 13, wherein the controller is further configured to generate the visual observations of motion in response to a difference between a motion of the matching features and a motion predicted by the odometry estimates is below a threshold.

16. The robotic device of claim 13, wherein the controller is further configured to estimate the carpet drift based at least on using a Kalman filter to process visual observations of motion.

17. A mobile robotic device comprising:

a first set of sensors configured to generate odometry measurements;

a second set of sensors configured to generate heading measurements of the mobile robotic device;

a camera configured to capture images; and

a controller communicatively coupled to the first and second sets of sensors and to the camera, wherein the controller is configured to selectively operate in a first mode and selectively operate in a second mode, wherein;

when operating in the first mode the controller is further configured to;

estimate a drift based at least on a heading estimated from the odometry measurements and on the heading measurements generated by the second set of sensors;

determine from the first mode estimated drift if the robotic device is on a carpeted or a non-carpeted surface;

in response to determination that robotic device is on a carpeted surface generate a carpet drift vector based at least on;

the odometry measurements sensed by the first set of sensors and the heading measurements sensed by the second set of sensors; and

when operating in the second mode, the controller is further configured to;

generate visual observations of motion of the mobile robotic device based at least on two or more images of the images captured by the camera, and wherein the controller is further configured to estimate a drift based at least on the odometry measurements and the visual observations of motion;

determine from the second mode estimated drift if the robotic device is on a carpeted or a non-carpeted surface;

in response to determination that robotic device is on a carpeted surface generate a carpet drift vector based at least on;

the odometry measurements and the visual observations of motion based at least on two or more images of the images captured by the camera.

18. The mobile robotic device of claim 17, further comprising differentially driven drive wheels, wherein the controller is further configured to operate in the first mode if an absolute differential rotation of the drive wheels is greater than a threshold.

19. The mobile robotic device of claim 17, wherein the controller is further configured to compute an uncertainty associated the visual observations of motion, and wherein the controller is further configured to operate in the second mode if the uncertainty is below a threshold.