Deprecated. Don't use it any more. We only keep this field for backwards compatibility of our data collections.

A unique identifier of a specific camera. This identifier determines which underlying driver is used to access a camera.

Deprecated. Use sensor_configs of size one with camera_params instead.

Deprecated. Use sensor_configs of size one with camera_params instead.

A list of camera settings. Camera settings are applied in the order in which they are defined. The specification of camera settings is optional.

A list of per-sensor configurations. These include per-sensor calibrations and poses. The specification of sensor configurations is optional.

The intrinsic camera parameters. If they are not presented, we are dealing with an uncalibrated camera.

The distortion params of the camera. If they are not present, the camera is either uncalibrated or it provides undistorted images (in all likelihood synthetic one).

The SFNC conforming feature name.

GenICam: IInteger - maps to a slider with value, min, max, and increment

GenICam: IFloat - maps to a slider with value, min, and max

GenICam: IBoolean - maps to a check box

GenICam: IString - maps to an edit box showing a string

GenICam: IEnumeration - maps to a drop down box

GenICam: ICommand

The SFNC conforming feature name.

The SFNC conforming feature name.

The hand eye calibration result.

The hand eye calibration request.

Camera name.

Robot name.

The calibration object name.

The timeout which is used for retrieving frames from the underlying driver implementation. If this timeout is implemented by the underlying camera driver, it will not spend more than the specified time when waiting for new frames. The timeout should be greater than the combined exposure and processing time. Processing times can be roughly estimated as a value between 10 - 50 ms. The timeout just serves as an upper limit to prevent blocking calls within the camera driver. In case of intermittent network errors users can try to increase the timeout. The default timeout (if unspecified) of 500 ms works well in common setups.

Optional. Request data only for the following sensor ids (i.e. transmit mask). Empty returns all sensor images.

Additional global (applied to all sensor images) post processing options on whether the image should be undistorted, cropped, resized and encoding formats.

If set the capture result will be stored in the specified key value store location, which will also be returned instead of the capture result itself.

Additional post processing options for each sensor. If present, sensor post processing options will override the global post processing options.

If set, images will be logged using the passed context. It contains e.g. the IDs of skills and plans.

Handle for the camera to capture from

Timestamp at which the images were captured. Value matches each sensor_image's acquisition_time, and is duplicated for capture result processing convenience.

Images for each of the captured sensors

Duration needed to capture all images excluding post processing like HDR. Not all camera drivers will provide it.

The configuration of the camera which should be created.

The handle is server specific and an internal identifier for the camera. The handle format is considered to be an implementation detail and will change between different server invocations.

Image resolution along x axis, in pixels.

Image resolution along y axis, in pixels.

First radial distortion coefficient.

Second radial distortion coefficient.

Third radial distortion coefficient.

First tangetial distortion coefficient.

Second tangetial distortion coefficient.

Fourth radial distortion coefficient.

Fifth radial distortion coefficient.

Sixth radial distortion coefficient.

First thin prism distortion coefficient.

Second thin prism distortion coefficient.

Third thin prism distortion coefficient.

Fourth thin prism distortion coefficient.

First tilt distortion coefficient.

Second tilt distortion coefficient.

The type of calibration to perform. Depending on this type, the returned HandEyeCalibrationResult will contain a corresponding result type.

The pairs of input poses to be used for the hand-eye-calibration. These have to cover all six degrees of freedom sufficiently so that the calibration result can be accurate.

If the intrinsics are specified, then it will be used along with pattern detections (as defined in InputPosePair above) to estimate the new camera to object poses. This is needed in case, we are doing the intrinsics and hand eye calibration as well. The intrinsics will not be saved to the camera config by this skill, but you can use the frontend to save the camera config instead.

The errors resulting from the hand-eye-calibration. The lower, the more accurate the calibration result is.

The image buffer's encoding.

Stores the underlying semantic pixel data which is stored in an image.

The image's number of channels, i.e. components per pixel.

The underlying data type of the pixels.

The width and height (cols and rows) of an image. This parameter is optional and must be specified when images are uncompressed, i.e. when encoding is ENCODING_UNSPECIFIED.

The actual underlying data.

The packing type of the pixels. If not present, implementations should default to PACKING_TYPE_INTERLEAVED.

Detections of the calibration plate.

Image dimensions.

Reprojection error in pixels.

3D error in m.

Focal length in horizontal direction. Required. The focal length is specified in pixels.

Focal length in vertical direction. Required. The focal length is specified in pixels.

Horizontal location of the principal point in the image plane. Required. The principal point is specified in pixels.

Vertical location of the principal point in the image plane. Required. The principal point is specified in pixels.

The dimensions of the image plane.

A list of unique camera identifiers. These can be used to create a CameraConfig which is required during camera creation.

The detected 2D image points.

The corresponding 3D model points.

The corresponding marker id. Optional. Only needed for visualization purposes for Charuco boards.

Class id (e.g., "pattern-1234").

Pattern detection.

Note that the driver (PhoXiControl) must be running on the workstation to be able to connect to the Photoneo.

Class id (e.g., "marker-1234").

Pose of the object.

Between 0..1. Unused in case of ground truth data.

Visibility score for the pose. Between 0..1. The visibility score indicates the proportion of the object that is visible, signifying their foreground presence. It helps in prioritizing the selection of parts during, for example, the picking process. It is defined as: Visible pixels / (Visible pixels + Occluded pixels)

Unique ID of this pose estimate, should be unique for a given scene of objects. Useful for debugging purposes.

Optional: Input image with overlaid pose estimations. This field will be only populated if requested in the run config.

Specifies how the returned image should be encoded.

If true, the returned image will be distorted. If false, the returned image might be undistorted depending whether the camera has undistortion parameters defined.

Optionally crops the image. Note that cropping happens after undistortion but before resizing.

Resize dimensions.

Resize width. Height is set automatically to aspect ratio.

Resize height. Width is set automatically to aspect ratio.

The identifier of the camera from which setting access is read.

The setting name. The setting name must be defined by the Standard Feature Naming Conventions (SFNC) which is part of the GenICam standard.

The access mode of a specific setting.

The identifier of the camera from which setting properties are read.

The setting name. The setting name must be defined by the Standard Feature Naming Conventions (SFNC) which is part of the GenICam standard.

The properties of a specific setting. For numeric properties (integer and float), these include the valid range of parameters, their increment and their unit. For enumerations the properties contain the values (as strings) which can be set.

The identifier of the camera from which setting properties are read.

The setting name. The setting name must be defined by the Standard Feature Naming Conventions (SFNC) which is part of the GenICam standard.

The current values of a specific setting. The following types of settings are supported int64, double, bool, string or an enum value.

The device_id becomes the ROS namespace of this camera.

The driver type, used to determine the ROS service prefix.

ComponentIDValue or 0 for GenICam, sensor number for other cameras (e.g. IPS PU)

Transforms the sensor data into the reference coordinate system of the camera.

Sensor camera parameters.

Configuration (calibration) for the sensor

Timestamp at which the image was captured

Frame data

SourceIDValue for Genicam, sensor number for other cameras (e.g. IPS PU)

Transforms the sensor data into the reference coordinate system of the camera.

Supported pixel types

Dimensions of sensor output

A human readable display name.

Is sensor currently disabled

Sensor camera parameters from factory

The identifier of the camera on which settings are updated.

The settings values which will be used to for a parameter update.

go/unspecified-enum

uint8_t

uint16_t

uint32_t

int8_t

int16_t

int32_t

float

double

uncompressed data, go/unspecified-enum

JPG compression

PNG compression

WEBP compression

YUV420P colorspace

The camera is stationary (fixed in world-space/relative to the robot's base). An object is attached (typically a calibration plate) to the robot's flange and was detected in the camera image from varying robot flange positions.

Object -?- Flange "!": known poses (input) ! ! "-?-": unknown poses (output) Camera -?- Base

The camera is attached to the robot's flange. A stationary object (fixed in world-space/relative to the robot' base) was detected in the camera image from varying robot flange positions.

Camera -?- Flange "!": known poses (input) ! ! "-?-": unknown poses (output) Object -?- Base

This will default to NONLINEAR.

NOTYPO Mili Shah (2013): "Solving the robot-world/hand-eye calibration problem using the kronecker product."

Aiguo Li, Lin Wang, and Defeng Wu (2010): "Simultaneous robot-world and hand-eye calibration using dual-quaternions and kronecker product."

Refines the solution from the SHAH algorithm by a Ceres-based non-linear optimization.

R. Tsai, R. Lenz (1989): "A New Technique for Fully Autonomous and Efficient 3D Robotics Hand/Eye Calibration".

F. Park, B. Martin (1994): "Robot Sensor Calibration: Solving AX = XB on the Euclidean Group".

R. Horaud, F. Dornaika (1995): "Hand-eye Calibration".

N. Andreff, R. Horaud, B. Espiau (1999): "On-line Hand-Eye Calibration".

K. Daniilidis (1999): "Hand-Eye Calibration Using Dual Quaternions".

go/unspecified-enum

Pixel channels are stored interleaved, e.g., rgbrgbrgb… for RGB images.

Pixel channels are stored in separate planes, e.g., rrrr…rrrbbb…bbbggg…ggg

go/unspecified-enum

Used for 1- and 3-channel intensity images.

Used for depth images.

Used for 3D point clouds.

Used for normals.