Joint camera and inertial measurement unit calibration
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for calibrating an augmented reality device using camera and inertial measurement unit data. In some implementations, a bundle adjustment process jointly optimizes or estimates states of the augmented reality device. The process can use, as input, visual and inertial measurements as well as factory-calibrated sensor extrinsic parameters. The process performs bundle adjustment and uses non-linear optimization of estimated states constrained by the measurements and the factory calibrated extrinsic parameters. The process can jointly optimize inertial constraints, IMU calibration, and camera calibrations. Output of the process can include most likely estimated states, such as data for a 3D map of an environment, a trajectory of the device, and/or updated extrinsic parameters of the visual and inertial sensors (e.g., cameras and IMUs).
1 . A system comprising:
one or more computers and one or more storage devices on which are stored instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:
receiving, from a camera included in a device, two images (a) of an environment in which the device is located (b) that each depict a portion of the environment that includes a point and is represented by an environment model of the environment that has a three-dimensional map point at a location that represents the point in the environment, the camera having camera calibration data that identifies a first rotation and a first translation that are both between the camera and a first sensor in the device;
receiving, from an inertial measurement unit included in the device, inertial data for the device, the inertial measurement unit having inertial measurement unit calibration data that identifies a second rotation and a second translation that are both between the inertial measurement unit and a second sensor in the device; and
jointly determining, using the two images, the inertial data, the camera calibration data, the inertial measurement unit calibration data, and the location for the three-dimensional map point or an initial estimated position of the device in the environment:
a) updated camera calibration data that identifies an updated first rotation and an updated first translation between the camera and the first sensor;
b) updated inertial measurement unit calibration data that identifies an updated second rotation and an updated second translation between the inertial measurement unit and the second sensor; and
c) at least one of (i) an updated estimated position of the device in the environment or (ii) an updated environment model of the environment in which the device is located including an updated location for the three-dimensional map point.
2 . The system of claim 1 , wherein:
the first sensor comprises a reference sensor, and the second sensor comprises the reference sensor; or
the first sensor comprises the inertial measurement unit, and the second sensor comprises the camera; or
the first sensor and the second sensor comprise the inertial measurement unit that is a reference sensor; or
the first sensor and the second sensor comprise the camera that is a reference sensor.
3 . The system of claim 1 , the operations comprising:
presenting, on a display, content for the environment using (i) the updated estimated position of the device in the environment, (ii) the updated environment model of the environment in which the device is located including the updated location for the three-dimensional map point, or (iii) both.
4 . The system of claim 1 , the operations comprising:
determining, using a first penalty function, a first error value that indicates a predicted accuracy of the inertial measurement unit calibration data; and
determining, using a second penalty function, a second error value that indicates a predicted accuracy of the camera calibration data, wherein:
jointly determining the updated camera calibration data, the updated inertial measurement unit calibration data, and (i) the updated estimated position of the device in the environment or (ii) the updated environment model of the environment comprises minimizing the first error value and the second error value.
5 . The system of claim 4 , wherein one or more of:
i) the operations comprise selecting, using the inertial data, a first weight for the first penalty function, the one or more computers configured to select different weights based on different inertial data, wherein:
determining the first error value comprises determining, using the first penalty function and the first weight, the first error value; or
ii) wherein jointly determining the updated camera calibration data, the updated inertial measurement unit calibration data, and (i) the updated estimated position of the device in the environment or (ii) the updated environment model of the environment comprises minimizing the first error value and the second error value comprises minimizing a difference between (a) a factory calibration that indicates a default space between the camera and the first sensor, and (b) a currently predicted space between the first and the first sensor.
6 . The system of claim 5 , wherein, one or more of:
a) selecting the first weight comprises:
determining a covariance for the inertial data; and
selecting the first weight using the covariance for the inertial data; or
b) the default space between the camera and the first sensor comprises one or more default translation values and one or more default rotation values; or
c) the currently predicted space between the camera and the first sensor comprises one or more currently predicted translation values and one or more currently predicted rotation values.
7 . The system of claim 1 , wherein jointly determining the updated camera calibration data, the updated inertial measurement unit calibration data, and (i) the updated estimated position of the device in the environment or (ii) the updated environment model of the environment comprises:
determining the updated camera calibration data using the two images, the inertial data, the camera calibration data, the inertial measurement unit calibration data, one or more constraints that indicate a limit for an amount of movement between the camera and the first sensor, and the location for the three-dimensional map point or the initial estimated position of the device in the environment.
8 . The system of claim 7 , wherein one or more of:
a) the operations comprise:
determining an estimated distance between the inertial measurement unit and the second sensor using the inertial data, wherein jointly determining the updated camera calibration data, the updated inertial measurement unit calibration data, and (i) the updated estimated position of the device in the environment or (ii) the updated environment model of the environment comprises:
comparing (i) the estimated distance between the inertial measurement unit and the second sensor and (ii) the one or more constraints that indicate the limit for the amount of movement between the camera and the first sensor; or
b) wherein the limit for an amount of movement between the camera and the first sensor comprises a maximum distance between the camera and the first sensor, a maximum rotation between a first surface on the camera and a second surface on the first sensor, or both; or
c) wherein the limit for an amount of movement between the camera and the first sensor comprises a minimum distance between the camera and the first sensor, a minimum rotation between a first surface on the camera and a second surface on the first sensor, or both; or
d) wherein the limit for an amount of movement between the camera and the first sensor comprises a maximum distance between the inertial measurement unit and the second sensor, a maximum rotation between a first surface on the inertial measurement unit and a second surface on the second sensor, or both; or
e) wherein the limit for an amount of movement between the camera and the first sensor comprises a minimum distance between the inertial measurement unit and the second sensor, a minimum rotation between a first surface on the inertial measurement unit and a second surface on the second sensor, or both.
9 . The system of claim 8 , wherein, one or more of:
f) the device includes:
the camera and a second different camera; and
the inertial measurement unit that is physically closer to the camera than any other cameras included in the device and a second different inertial measurement unit that is physically closer to the second different camera than any other cameras included in the device; and
the second sensor is the second different inertial measurement unit; or
g) the device includes:
the camera and a second different camera; and
the inertial measurement unit that is within a threshold physical distance from the camera and a second different inertial measurement unit that is within the threshold physical distance from the second different camera.
10 . The system of claim 1 , wherein:
the device includes two or more cameras; and
jointly determining the updated camera calibration data, the updated inertial measurement unit calibration data, and (i) the updated estimated position of the device in the environment or (ii) the updated environment model of the environment comprises jointly determining, for each of the two or more cameras, camera calibration data for the camera with respect to each of the other cameras included in the two or more cameras.
11 . The system of claim 1 , wherein:
the inertial data comprise position data that represents a position relative to a global reference frame, orientation data, angular velocity data, and linear velocity data; and
jointly determining the updated camera calibration data, the updated inertial measurement unit calibration data, and (i) the updated estimated position of the device in the environment or (ii) the updated environment model of the environment comprises determining the updated camera calibration data using the two images, the inertial data, the camera calibration data, the inertial measurement unit calibration data, the position data that represents a position relative to the global reference frame, the orientation data, the angular velocity data, and the linear velocity data.
12 . The system of claim 11 , wherein:
the inertial data comprise acceleration data; and
determining the updated camera calibration data comprises determining the updated camera calibration data using the two images, the camera calibration data, the inertial measurement unit calibration data, the position data that represents a position relative to the global reference frame, the orientation data, the angular velocity data, the linear velocity data, and the acceleration data.
13 . The system of claim 1 , wherein, one or more of:
a) the system is the device and comprises:
the camera; and
the inertial measurement unit; or
b) the device comprises a wearable device, a headset, or an augmented reality device.
14 . The system of claim 1 , wherein, one or more of:
a) jointly determining the updated camera calibration data, the updated inertial measurement unit calibration data, and (i) the updated estimated position of the device in the environment or (ii) the updated environment model of the environment comprises determining the updated environment model of the environment by updating the environment model; or
b) jointly determining the updated camera calibration data, the updated inertial measurement unit calibration data, and (i) the updated estimated position of the device in the environment or (ii) the updated environment model of the environment comprises determining a trajectory of the device in the environment; or
c) jointly determining the updated camera calibration data, the updated inertial measurement unit calibration data, and (i) the updated estimated position of the device in the environment or (ii) the updated environment model of the environment comprises determining an orientation of the device in the environment using the two images and the inertial data; or
d) jointly determining the updated camera calibration data, the updated inertial measurement unit calibration data, and (i) the updated estimated position of the device in the environment or (ii) the updated environment model of the environment comprises determining a trajectory of the device in the environment using the two images and the inertial data; or
e) jointly determining the updated camera calibration data, the updated inertial measurement unit calibration data, and (i) the updated estimated position of the device in the environment or (ii) the updated environment model of the environment comprises determining a mapping of image data for one or more images from the two images to locations in the environment model of the environment in which the device is located; or
f) receiving the two images comprises receiving at least one image from the two images that depicts data not represented by the environment model of the environment in which the device is located.
15 . The system of claim 14 , the operations comprising:
determining a prior position of the device, wherein jointly determining the updated camera calibration data, the updated inertial measurement unit calibration data, and (i) the updated estimated position of the device in the environment or (ii) the updated environment model of the environment is responsive to determining that a predetermined time period after the determination of the prior position of the device has expired.
16 . The system of claim 1 , the operations comprising maintaining, in a memory, the environment model of the environment in which the device is located.
17 . The system of claim 1 , the operations comprising:
determining, for the camera, whether a difference between (a) the updated camera calibration data and (b) the camera calibration data satisfies a threshold value; and
in response to determining that the difference satisfies the threshold value, updating a calibration profile for the camera using the updated camera calibration data.
18 . The system of claim 17 , wherein the updated camera calibration data comprises a translation value and a rotation value.
19 . A computer-implemented method comprising:
receiving, from a camera included in a device, two images (a) of an environment in which the device is located (b) that each depict a portion of the environment that includes a point and is represented by an environment model of the environment that has a three-dimensional map point at a location that represents the point in the environment, the camera having camera calibration data that identifies a first rotation and a first translation that are both between the camera and a first sensor in the device;
receiving, from an inertial measurement unit included in the device, inertial data for the device, the inertial measurement unit having inertial measurement unit calibration data that identifies a second rotation and a second translation that are both between the inertial measurement unit and a second sensor in the device; and
jointly determining, using the two images, the inertial data, the camera calibration data, the inertial measurement unit calibration data, and the location for the three-dimensional map point or an initial estimated position of the device in the environment:
a) updated camera calibration data that identifies an updated first rotation and an updated first translation between the camera and the first sensor;
b) updated inertial measurement unit calibration data that identifies an updated second rotation and an updated second translation between the inertial measurement unit and the second sensor; and
c) at least one of (i) an updated estimated position of the device in the environment or (ii) an updated environment model of the environment in which the device is located including an updated location for the three-dimensional map point.
20 . A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising:
receiving, from a camera included in a device, two images (a) of an environment in which the device is located (b) that each depict a portion of the environment that includes a point and is represented by an environment model of the environment that has a three-dimensional map point at a location that represents the point in the environment, the camera having camera calibration data that identifies a first rotation and a first translation that are both between the camera and a first sensor in the device;
receiving, from an inertial measurement unit included in the device, inertial data for the device, the inertial measurement unit having inertial measurement unit calibration data that identifies a second rotation and a second translation that are both between the inertial measurement unit and a second sensor in the device; and
jointly determining, using the two images, the inertial data, the camera calibration data, the inertial measurement unit calibration data, and the location for the three-dimensional map point or an initial estimated position of the device in the environment:
a) updated camera calibration data that identifies an updated first rotation and an updated first translation between the camera and the first sensor;
b) updated inertial measurement unit calibration data that identifies an updated second rotation and an updated second translation between the inertial measurement unit and the second sensor; and
c) at least one of (i) an updated estimated position of the device in the environment or (ii) an updated environment model of the environment in which the device is located including an updated location for the three-dimensional map point.