SilhouetteMatch¶
Introduction¶
The SilhouetteMatch module is an optional on-board module of the rc_cube and requires a separate SilhouetteMatch license to be purchased.
Note
This module is not available in camera pipelines of type blaze
.
The module detects objects by matching a predefined silhouette (“template”) to edges in the image.
The SilhouetteMatch module can detect objects in two different scenarios:
With calibrated base plane: The objects are placed on a common base plane, which must be calibrated before the detection, and the objects have significant edges on a common plane that is parallel to the base plane.
With object plane detection: The objects can be placed at different, previously unknown heights, if the objects have a planar surface and their outer contours are well visible in the images (e.g. stacked flat objects).
Templates for object detection can be created by uploading a DXF file and specifying the object height. The correct scale and unit of the contours are extracted from the DXF file. If no units are present in the DXF file, the user has to specify which units should be used. When the outer contour of the object in the DXF file is closed, a 3D collision model is created automatically by extruding the contour by the given object height. This model will then be used for collision checking and in 3D visualizations. Uploading a DXF file can be done in the Web GUI via the + Create a new Template button in the SilhouetteMatch Templates and Grasps section on the or pages.
Roboception also offers a template generation service on their website, where the user can upload CAD files or recorded data of the objects and request object templates for the SilhouetteMatch module.
The object templates consist of significant edges of each object. These template edges are matched to the edges detected in the left and right camera images, considering the actual size of the objects and their distance from the camera. The poses of the detected objects are returned and can be used for grasping, for example.
The SilhouetteMatch module offers:
- A dedicated page on the rc_cube Web GUI for easy setup, configuration, testing, and application tuning.
- A REST-API interface and a KUKA Ethernet KRL Interface.
- The definition of 2D regions of interest to select relevant parts of the camera image (see Setting a region of interest).
- A load carrier detection functionality for bin-picking applications (see LoadCarrier), to provide grasps for objects inside a bin only.
- Storing of up to 50 templates.
- The definition of up to 50 grasp points for each template via an interactive visualization in the Web GUI.
- Collision checking between the gripper and the load carrier, the calibrated base plane, other detected objects and/or the point cloud.
- Support for static and robot-mounted cameras and optional integration with the Hand-eye calibration module, to provide grasps in the user-configured external reference frame.
- Selection of a sorting strategy to sort the detected objects and returned grasps.
- 3D visualization of the detection results with grasp points and gripper animations in the Web GUI.
Note
This module is pipeline specific. Changes to its settings or parameters only affect the respective camera pipeline and have no influence on other pipelines running on the rc_cube.
However, the object templates and grasp points are stored globally. Setting, changing or deleting an object template or its grasps affects all camera pipelines.
Suitable objects¶
The SilhouetteMatch module is intended for objects which have significant edges on a common plane that is parallel to the plane on which the objects are placed. This applies to flat, nontransparent objects, such as routed, laser-cut or water-cut 2D parts and flat-machined parts. More complex parts can also be detected if there are significant edges on a common plane, e.g. a special pattern printed on a flat surface. The detection works best for objects on a texture-free plane. The color of the base plane should be chosen such that a clear contrast between the objects and the base plane appears in the intensity image.
In case the objects are not placed on a common base plane or the base plane cannot be calibrated beforehand, the objects need to have a planar surface and their outer contour must be well visible in the left and right images. Furthermore, the template for these objects must have a closed outer contour.
Suitable scene¶
The scene must meet the following conditions to be suitable for the SilhouetteMatch module:
- The objects to be detected must be suitable for the SilhouetteMatch module as described above.
- Only objects belonging to one specific template are visible at a time (unmixed scenario). In case other objects are visible as well, a proper region of interest (ROI) must be set.
- In case a calibrated base plane is used: The offset between the base plane normal and the camera’s line of sight does not exceed 10 degrees.
- In case the object planes are detected automatically: The offset between the object’s planar surface normal and the camera’s line of sight does not exceed 25 degrees.
- The objects are not partially or fully occluded.
- All visible objects are right side up (no flipped objects).
- The object edges to be matched are visible in both, left and right camera images.
Base-plane calibration¶
In case all objects are placed on a common plane that is known beforehand, a base-plane calibration should be performed before triggering a detection. Thereby, the distance and angle of the plane on which the objects are placed is measured and stored persistently on the rc_cube.
Separating the detection of the base plane from the actual object detection renders scenarios possible in which the base plane is temporarily occluded. Moreover, it increases performance of the object detection for scenarios where the base plane is fixed for a certain time; thus, it is not necessary to continuously re-detect the base plane.
The base-plane calibration can be performed in three different ways, which will be explained in more detail further down:
- AprilTag based
- Stereo based
- Manual
The base-plane calibration is successful if the normal vector of the estimated base plane is at most 10 degrees offset to the camera’s line of sight. If the base-plane calibration is successful, it will be stored persistently on the rc_cube until it is removed or a new base-plane calibration is performed.
Note
To avoid privacy issues, the image of the persistently stored base-plane calibration will appear blurred after rebooting the rc_cube.
In scenarios where the base plane is not accessible for calibration, a plane parallel to the base plane can be calibrated.
Then an offset
parameter can be used to shift the estimated plane onto the actual base plane where
the objects are placed. The offset
parameter gives the distance in meters by which the estimated plane
is shifted towards the camera.
In the REST-API, a plane is defined by a normal
and a distance
.
normal
is a normalized 3-vector, specifying the normal of the plane.
The normal points away from the camera.
distance
represents the distance of the plane from the camera along the normal.
Normal and distance can also be interpreted as \(a\), \(b\), \(c\), and \(d\) components
of the plane equation, respectively:
AprilTag based base-plane calibration¶
AprilTag detection (ref. TagDetect) is used to find AprilTags in the scene and fit a plane through them. At least three AprilTags must be placed on the base plane so that they are visible in the left and right camera images. The tags should be placed such that they are spanning a triangle that is as large as possible. The larger the triangle, the more accurate is the resulting base-plane estimate. Use this method if the base plane is untextured and no external random dot projector is available. This calibration mode is available via the REST-API interface and the rc_cube Web GUI.
Stereo based base-plane calibration¶
The 3D point cloud computed by the stereo matching module is used to fit a plane
through its 3D points.
Therefore, the region of interest (ROI) for this method must
be set such that only the relevant base plane is included.
The plane_preference
parameter allows to select whether the plane closest to
or farthest from the camera should be used as base plane.
Selecting the closest plane can be used in scenarios where the base plane is
completely occluded by objects or not accessible for calibration.
Use this method if the base plane is well textured or you can
make use of a random dot projector to project texture on the base plane.
This calibration mode is available via the REST-API interface
and the rc_cube Web GUI.
Manual base-plane calibration¶
The base plane can be set manually if its parameters are known, e.g. from previous calibrations. This calibration mode is only available via the REST-API interface and not the rc_cube Web GUI.
Setting a region of interest¶
If objects are to be detected only in part of the camera’s field of view, a 2D region of interest (ROI) can be set accordingly as described in Region of interest.
Setting of grasp points¶
To use SilhouetteMatch directly in a robot application, up to 50 grasp points can be defined for each template. A grasp point represents the desired position and orientation of the robot’s TCP (Tool Center Point) to grasp an object as shown in Fig. 22.
Each grasp consists of an id
which must be
unique within all grasps for an object template, the template_id
representing the template
to which the grasp should be attached, and the pose
in the coordinate frame of the object template.
Grasp points can be set via the REST-API interface,
or by using the interactive visualization in the Web GUI.
Furthermore, a priority
(spanning -2 for very low to 2 for very high) can be assigned to a grasp.
Priorities can facilitate robot applications and shorten response times when the run-time parameter
only_highest_priority_grasps
is set to true. In this case collision checking concludes when
grasps with the highest possible priority have been found. Finally, different grasps can be associated with
different grippers by specifying a gripper_id
. These individual grippers are then used for collision checking
of the corresponding grasps instead of the gripper defined in the detect_object
request. If no gripper_id
is given, the gripper
defined in the detect_object
request will be used for collision checking.
When a grasp is defined on a symmetric object, all grasps symmetric to the defined one
will automatically be considered in the SilhouetteMatch module’s detect_object
service call. Symmetric grasps
for a given grasp point can be retrieved using the get_symmetric_grasps
service call and visualized in the Web GUI.
Users can also define replications of grasps around a custom axis. These replications spawn multiple grasps and free users
from setting too many grasps manually. The replication origin is defined as a coordinate frame in the object’s coordinate
frame and the x axis of the replication origin frame corresponds to the replication axis.
The grasp is replicated by rotating it around this x axis
starting from its original pose. The replication is done in steps of size step_x_deg
degrees.
The range is defined by the minimal and maximal boundaries min_x_deg
and max_x_deg
.
The minimal (maximal) boundary must be a non-positive (non-negative) number up to (minus) 180 degrees.
Setting grasp points in the Web GUI¶
The rc_cube Web GUI provides an intuitive and interactive way of defining grasp points for object templates. In a first step, the object template has to be uploaded to the rc_cube. This can be done in the Web GUI in any pipeline under + Add a new Template in the Templates and Grasps section, or in in the SilhouetteMatch Templates and Grasps section. Once the template upload is complete, a dialog with a 3D visualization of the object template is shown for adding or editing grasp points. The same dialog appears when editing an existing template. If the template contains a collision model or a visualization model, this 3D model is visualized as well.
by clicking onThis dialog provides two ways for setting grasp points:
- Adding grasps manually: By clicking on the + symbol, a new grasp is placed in the object origin. The grasp can be given a unique name which corresponds to its ID. The desired pose of the grasp can be entered in the fields for Position and Roll/Pitch/Yaw which are given in the coordinate frame of the object template represented by the long x, y and z axes in the visualization. The grasp point can be placed freely with respect to the object template - inside, outside or on the surface. The grasp point and its orientation are visualized in 3D for verification.
- Adding grasps interactively: Grasp points can be added interactively by first clicking on the Add Grasp button in the upper right corner of the visualization and then clicking on the desired point on the object template visualization. If the 3D model is displayed, the grasps will be attached to the surface of the 3D model. Otherwise, the grasp is attached to the template surface. The grasp orientation is a right-handed coordinate system and is chosen such that its z axis is perpendicular to the surface pointing inside the template at the grasp position. The position and orientation in the object coordinate frame is displayed on the right. The position and orientation of the grasp can also be changed interactively. In case Snap to surface is disabled (default), the grasp can be translated and rotated freely in all three dimensions by clicking on Move Grasp in the visualization menu and then dragging the grasp along the appropriate axis to the desired position. The orientation of the grasp can also be changed by rotating the axis with the mouse. In case Snap to surface is enabled in the visualization, the grasp can only be moved along the model surface.
Users can also specify a grasp priority by changing the Priority slider. A dedicated gripper can be selected in the Gripper drop down field.
By activating the Replication check box, users can replicate the grasp around a custom axis. The replication axis and the resulting replicated grasps are visualized. The position and orientation of the replication axis relative to the object coordinate frame can be adjusted interactively by clicking on Move Replication Axis in the visualization menu and then dragging the axis to the desired position and orientation. The grasps are replicated within the specified rotation range at the selected rotation step size. Users can cycle through a visualization of the replicated grasps by dragging the bar below Cycle through n replicated grasps in the View Options section of the visualization menu. If a gripper is selected for the grasp or a gripper has been chosen in the visualization menu, the gripper is also shown at the currently selected grasp.
If the object template has symmetries, the grasps which are symmetric to the defined grasps can be displayed along with their replications (if defined) by enabling … symmetries in the View Options section of the visualization menu. The user can also cycle through a visualization of the symmetric grasps by dragging the bar below Cycle through n symmetric grasps.
Setting grasp points via the REST-API¶
Grasp points can be set via the REST-API interface
using the set_grasp
or set_all_grasps
services
(see Internal services).
A grasp consists of the template_id
of the template
to which the grasp should be attached, an id
uniquely identifying the grasp point and
the pose
. The pose is given in the coordinate frame of the object template and
consists of a position
in meters and an orientation
as quaternion.
A dedicated gripper can be specified through setting the gripper_id
field. The
priority
is specified by an integer value, ranging from -2 for very low, to 2 for very high with a step size
of 1. The replication origin is defined as a transformation in the object’s coordinate frame and the x axis
of the transformation corresponds to the replication axis. The
replication range is controlled by the min_x_deg
and max_x_deg
fields and the step size step_x_deg
.
Setting the preferred orientation of the TCP¶
The SilhouetteMatch module determines the reachability of grasp points based on the preferred orientation of the
gripper or TCP. The preferred orientation can be set via the set_preferred_orientation
service or on
the SilhouetteMatch page in the Web GUI.
The resulting direction of the TCP’s z axis is used to reject grasps which cannot be reached by the gripper.
Furthermore, the preferred orientation can be used to sort the reachable grasps by setting the corresponding
sorting strategy.
The preferred orientation can be set in the camera coordinate frame or in the external coordinate frame, in case a hand-eye calibration is available. If the preferred orientation is specified in the external coordinate frame and the sensor is robot mounted, the current robot pose has to be given to each object detection call, so that the preferred orientation can be used for filtering and, optionally, sorting the grasps on the detected objects. If no preferred orientation is set, the orientation of the left camera is used as the preferred orientation of the TCP.
Setting the sorting strategies¶
The objects and grasps returned by the detect_object
service call are sorted according to a sorting strategy which can be
chosen by the user. The following sorting strategies are available and
can be set in the Web GUI
or using the set_sorting_strategies
service call:
preferred_orientation
: objects and grasp points with minimal rotation difference between their orientation and the preferred orientation of the TCP are returned first,direction
: objects and grasp points with the shortest distance along a defined directionvector
in a givenpose_frame
are returned first.
If no sorting strategy is set or default sorting is chosen in the Web GUI, sorting is done based on a combination of
preferred_orientation
and the minimal distance from the camera along the z axis of the preferred orientation of the TCP.
Detection of objects¶
For triggering the object detection, in general, the following information must be provided to the SilhouetteMatch module:
- The template of the object to be detected in the scene.
- The coordinate frame in which the poses of the detected objects shall be returned (ref. Hand-eye calibration).
Optionally, further information can be given to the SilhouetteMatch module:
- A flag
object_plane_detection
determining whether the surface plane of the objects should be used for the detection instead of the calibrated base plane. - An offset, in case the calibrated base plane should be used but the objects are not lying on this plane but on a plane parallel
to it. The offset is the distance between both planes
given in the direction towards the camera. If omitted, an offset of 0 is assumed. It must not be set if
object_plane_detection
is true. - The ID of the load carrier which contains the objects to be detected.
- The ID of the region of interest where to search for the load carrier if a load carrier is set. Otherwise, the ID of the region of interest where the objects should be detected. If omitted, objects are matched in the whole image.
- The current robot pose in case the camera is mounted on the robot and
the chosen coordinate frame for the poses is
external
or the preferred orientation is given in the external frame. - Collision detection information: The ID of the gripper to enable collision checking and optionally a pre-grasp offset to define a pre-grasp position. Details on collision checking are given below in CollisionCheck.
In case the object_plane_detection
flag is not true,
objects can only be detected after a successful base-plane calibration.
It must be ensured that the position and orientation of the base plane
does not change before the detection of objects.
Otherwise, the base-plane calibration must be renewed.
When object_plane_detection
is set to true, a base-plane calibration is not required and
an existing base-plane calibration will be ignored. During detection, the scene is clustered into
planar surfaces and template matching is performed on each plane whose tilt with respect to the
camera’s line of sight is less than 25° and whose size is large enough to contain the selected template.
When a match is found, its position and orientation are refined using the image edges and the
point cloud inside the template’s outer contour. For this, it is required that the outer contour of
the template is closed and that the object’s surface is planar.
On the Web GUI the detection can be tested in the Try Out section of the SilhouetteMatch page. Different image streams can be selected to show intermediate results and the final matches as shown in Fig. 23.
The “Template” image stream shows the template to be matched in red with the defined grasp points in green (see Setting of grasp points). The template is warped to the size and tilt matching objects on the calibrated base plane or, in case
object_plane_detection
was used, the highest segmented plane, would have. The corresponding plane is shown in dark blue.The “Intermediate Result” image stream shows the edges of the left image that were used to search for matches in light blue. The chosen region of interest is shown as bold petrol rectangle. A shaded blue area on the left visualizes the region of the left camera image which does not overlap with the right image, and in which no objects can be detected. If
object_plane_detection
was used, this image stream also shows the detected planar clusters in the scene. Clusters that were not used for matching, because they were too small or too tilted, are visualized with a stripe pattern.The “Intermediate Result Right” image stream shows the edges of the right image that were used to search for matches in light blue. The chosen region of interest is shown as bold petrol rectangle. A shaded blue area on the right visualizes the region of the right camera image which does not overlap with the left image, and in which no objects can be detected.
The “Result” image shows the detection result. The image edges that were used to refine the match poses are shown in light blue and the matches (
instances
) with the template edges are shown in red. The blue circles are the origins of the detected objects as defined in the template and the green circles are the collision-free grasp points. Colliding grasp points are visualized as red dots and grasp points that were not checked for collisions are drawn in yellow.
The poses of the object origins in the chosen
coordinate frame are returned as results in a list of instances
.
In case the calibrated base plane was used for the detection (object_plane_detection
not set or false),
the orientations of the detected objects are aligned with the normal of the base plane.
Otherwise, the orientations of the detected objects are aligned with the normal of a plane fitted to the
object points in the 3D point cloud.
If the chosen template also has grasp points attached,
a list of grasps
for all objects is returned in addition to the list of detected objects.
The grasp poses are given in the desired coordinate frame and
the grasps are sorted according to the selected sorting strategy
(see Setting the sorting strategies).
There are references between the detected object instances and the grasps via their uuids
.
In case the templates have a continuous rotational symmetry (e.g. cylindrical objects), all returned object poses will have the same orientation. Furthermore, all grasps symmetric to each grasp point on an object are checked for reachability and collisions, and only the best one according to the given sorting strategy is returned.
For objects with a discrete symmetry (e.g. prismatic objects), all collision-free symmetries of each grasp point which are reachable according to the given preferred TCP orientation are returned, ordered by the given sorting strategy.
The detection results and run times are affected by several run-time parameters which are listed and explained further down. Improper parameters can lead to timeouts of the SilhouetteMatch module’s detection process.
Interaction with other modules¶
Internally, the SilhouetteMatch module depends on, and interacts with other on-board modules as listed below.
Note
All changes and configuration updates to these modules will affect the performance of the SilhouetteMatch module.
Stereo camera and stereo matching¶
The SilhouetteMatch module makes internally use of the rectified images from the
Camera module (rc_camera
).
Thus, the exposure time should be set properly to achieve the optimal performance of the module.
For base-plane calibration in stereo mode, for load carrier detection, for automatic object plane detection and for collision checking
with the point cloud, the disparity images from the Stereo matching module
(rc_stereomatching
) are used.
For detecting objects with a calibrated base plane, without load carrier and without collision checking with the point cloud, the stereo-matching module should not be run in parallel to the SilhouetteMatch module, because the detection runtime increases.
For best results it is recommended to enable smoothing for Stereo matching.
IO and Projector Control¶
In case the rc_cube is used in conjunction with an external random dot projector and
the IO and Projector Control module (rc_iocontrol
),
the projector should be used for the stereo-based base-plane calibration, for automatic object plane detection and for collision checking
with the point cloud.
The projected pattern must not be visible in the left and right camera images during object detection
as it interferes with the matching process.
Therefore, it is recommended to connect the projector to GPIO Out 1 and set
the stereo-camera module’s acquisition mode to SingleFrameOut1
(see Stereo matching parameters), so that
on each image acquisition trigger an image with and without projector pattern is acquired.
Alternatively, the output mode for the GPIO output in use should be set to ExposureAlternateActive
(see Description of run-time parameters).
In either case,
the Auto Exposure Mode exp_auto_mode
should be set to AdaptiveOut1
to optimize the exposure
of both images (see Stereo camera parameters).
Hand-eye calibration¶
In case the camera has been calibrated to a robot, the SilhouetteMatch module can automatically provide
poses in the robot coordinate frame.
For the SilhouetteMatch node’s Services, the frame of the
input and output poses and plane coordinates can be controlled with the pose_frame
argument.
Two different pose_frame
values can be chosen:
- Camera frame (
camera
). All poses and plane coordinates provided to and by the module are in the camera frame. - External frame (
external
). All poses and plane coordinates provided to and by the module are in the external frame, configured by the user during the hand-eye calibration process. The module relies on the on-board Hand-eye calibration module to retrieve the camera mounting (static or robot mounted) and the hand-eye transformation. If the sensor mounting is static, no further information is needed. If the sensor is robot-mounted, therobot_pose
is required to transform poses to and from theexternal
frame.
All pose_frame
values that are not camera
or external
are rejected.
Note
If no hand-eye calibration is available, all pose_frame
values should be set to camera
.
Note
If the hand-eye calibration has changed after base-plane calibration, the base-plane calibration will be marked as invalid and must be renewed.
If the sensor is robot-mounted, the current robot_pose
has to be provided depending on the value of pose_frame
,
the definition of the preferred TCP orientation and the sorting direction:
- If
pose_frame
is set toexternal
, providing the robot pose is obligatory. - If the preferred TCP orientation is defined in
external
, providing the robot pose is obligatory. - If the sorting direction is defined in
external
, providing the robot pose is obligatory. - In all other cases, providing the robot pose is optional.
If the current robot pose is provided during calibration, it is stored persistently on the rc_cube.
If the updated robot pose is later provided during get_base_plane_calibration
or detect_object
as well, the base-plane calibration will be transformed automatically to this new robot pose.
This enables the user to change the robot pose (and thus camera position)
between base-plane calibration and object detection.
Note
Object detection can only be performed if the limit of 10 degrees angle offset between the base plane normal and the camera’s line of sight is not exceeded.
LoadCarrier¶
The SilhouetteMatch module uses the load carrier detection functionality provided by the
LoadCarrier module (rc_load_carrier
),
with the run-time parameters specified for this module. However, only one load carrier will be
returned and used in case multiple matching load carriers could be found in the scene. In case multiple
load carriers of the same type are visible, a region of interest should be set to ensure that always the
same load carrier is used for the SilhouetteMatch module.
CollisionCheck¶
Collision checking can be easily enabled for
grasp computation of the SilhouetteMatch module by passing a collision_detection
argument to the
detect_object
service call. It contains the ID of the used gripper and
optionally a pre-grasp offset. The gripper has to be
defined in the GripperDB module
(see Setting a gripper)
and details about collision checking are given in Collision checking within other modules.
Alternatively, grasp points can be assigned individual gripper IDs, and collision checking can be enabled for all
grasp points with gripper IDs by enabling the run-time parameter check_collisions
.
In addition to collision checking between the gripper and the detected load carrier, collisions
between the gripper and the calibrated base plane will be checked, if the run-time parameter check_collisions_with_base_plane
is true.
If the selected SilhouetteMatch template contains a collision model and the run-time parameter check_collisions_with_matches
is true,
also collisions between the gripper and all other detected objects (not limited to max_number_of_detected_objects
) will be checked. The object
on which the grasp point to be checked is located, is excluded from the collision check.
If the run-time parameter check_collisions_with_point_cloud
is true,
also collisions between the gripper and a watertight version of the point cloud are checked.
If this feature is used with suctions grippers, it should be ensured that the TCP is defined
to be outside the gripper geometry, or that the grasp points are defined above the object surface.
Otherwise every grasp will result in a collision between the gripper and the point cloud.
If the run-time parameter check_collisions_during_retraction
is true and a load carrier and a pre-grasp offset are given,
each grasp point will be checked for collisions between the object in the gripper and the load carrier walls during retraction.
This collision check is performed along the full linear trajectory from the grasp point back to the pre-grasp position.
If collision checking is enabled, only grasps which are collision free or could not be checked for collisions (e.g. because no gripper was given) will be returned. The visualization images on the SilhouetteMatch page of the Web GUI shows collision-free grasps in green, unchecked grasps in yellow and colliding grasp points in red. The detected objects which are considered in the collision check are also visualized with their edges in red.
The CollisionCheck module’s run-time parameters affect the collision detection as described in CollisionCheck Parameters.
Parameters¶
The SilhouetteMatch software module is called rc_silhouettematch
in the REST-API and is represented in the
Web GUIin the desired pipeline under
.
The user can explore and configure the rc_silhouettematch
module’s run-time parameters, e.g. for development and testing, using the Web GUI or the
REST-API interface.
Parameter overview¶
This module offers the following run-time parameters:
Name | Type | Min | Max | Default | Description |
---|---|---|---|---|---|
check_collisions |
bool | false | true | false | Whether to check for collisions when a gripper is defined for a grasp |
check_collisions_ -during_retraction |
bool | false | true | false | Whether to check for collisions between the object in the gripper and the load carrier during retraction |
check_collisions_with_ -base_plane |
bool | false | true | true | Whether to check for collisions between gripper and base plane |
check_collisions_with_matches |
bool | false | true | true | Whether to check for collisions between gripper and detected matches |
check_collisions_with_ -point_cloud |
bool | false | true | false | Whether to check for collisions between gripper and the point cloud |
edge_sensitivity |
float64 | 0.1 | 1.0 | 0.7 | Sensitivity of the edge detector |
match_max_distance |
float64 | 0.1 | 10.0 | 3.0 | Maximum allowed distance in pixels between the template and the detected edges in the image |
match_percentile |
float64 | 0.7 | 1.0 | 0.8 | Percentage of template pixels that must be within the maximum distance to successfully match the template |
max_number_of_detected_objects |
int32 | 1 | 20 | 10 | Maximum number of detected objects |
only_highest_priority_grasps |
bool | false | true | false | Whether to return only the highest priority level grasps |
point_cloud_enhancement |
string | - | - | Off | Type of enhancement of the point cloud using the base plane: [Off, ReplaceBright] |
quality |
string | - | - | High | Quality: [Low, Medium, High] |
Description of run-time parameters¶
Each run-time parameter is represented by a row on the Web GUI’s SilhouetteMatch page. The name in the Web GUI is given in brackets behind the parameter name and the parameters are listed in the order they appear in the Web GUI:
max_number_of_detected_objects
(Maximum Object Number)¶
This parameter gives the maximum number of objects to detect in the scene. If more than the given number of objects can be detected in the scene, only the objects matching best to the given sorting strategy are returned.
Via the REST-API, this parameter can be set as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/parameters?max_number_of_detected_objects=<value>PUT http://<host>/api/v1/nodes/rc_silhouettematch/parameters?max_number_of_detected_objects=<value>
quality
(Quality)¶
Object detection can be performed on images with different resolutions:
High
(full image resolution),Medium
(half image resolution) andLow
(quarter image resolution). The lower the resolution, the lower the detection time, but the fewer details of the objects are visible.Via the REST-API, this parameter can be set as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/parameters?quality=<value>PUT http://<host>/api/v1/nodes/rc_silhouettematch/parameters?quality=<value>
match_max_distance
(Maximum Matching Distance)¶
This parameter gives the maximum allowed pixel distance of an image edge pixel from the object edge pixel in the template to be still considered as matching. If the object is not perfectly represented in the template, it might not be detected when this parameter is low. High values, however, might lead to false detections in case of a cluttered scene or the presence of similar objects, and also increase runtime.
Via the REST-API, this parameter can be set as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/parameters?match_max_distance=<value>PUT http://<host>/api/v1/nodes/rc_silhouettematch/parameters?match_max_distance=<value>
match_percentile
(Matching Percentile)¶
This parameter indicates how strict the matching process should be. The matching percentile is the ratio of template pixels that must be within the Maximum Matching Distance to successfully match the template. The higher this number, the more accurate the match must be to be considered as valid.
Via the REST-API, this parameter can be set as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/parameters?match_percentile=<value>PUT http://<host>/api/v1/nodes/rc_silhouettematch/parameters?match_percentile=<value>
edge_sensitivity
(Edge Sensitivity)¶
This parameter influences how many edges are detected in the left and right camera images. The higher this number, the more edges are found in the intensity images. That means, for lower numbers, only the most significant edges are considered for template matching. A large number of edges in the image might increase the detection time. It must be ensured that the edges of the objects to be detected are detected in both, the left and the right camera images.
Via the REST-API, this parameter can be set as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/parameters?edge_sensitivity=<value>PUT http://<host>/api/v1/nodes/rc_silhouettematch/parameters?edge_sensitivity=<value>
only_highest_priority_grasps
(Only Highest Priority Grasps)¶
If set to true, only grasps with the highest priority will be returned. If collision checking is enabled, only the collision-free grasps among the group of grasps with the highest priority are returned. This can save computation time and reduce the number of grasps to be parsed on the application side.
Without collision checking, only grasps of highest priority are returned.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/parameters?only_highest_priority_grasps=<value>PUT http://<host>/api/v1/nodes/rc_silhouettematch/parameters?only_highest_priority_grasps=<value>
check_collisions
(Check Collisions)¶
If this parameter is enabled, collision checking will be performed for all grasps which have a gripper ID assigned, even when no default gripper is given in the
detect_object
service call. If a load carrier is used, the collision check will always be performed between the gripper and the load carrier. Collision checking with the point cloud and other matches is only performed when the corresponding runtime parameters are enabled.Via the REST-API, this parameter can be set as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/parameters?check_collisions=<value>PUT http://<host>/api/v1/nodes/rc_silhouettematch/parameters?check_collisions=<value>
check_collisions_with_base_plane
(Check Collisions with Base Plane)¶
This parameter is only used when collision checking is enabled by passing a gripper to the
detect_object
service call or by enabling thecheck_collisions
runtime parameter. Ifcheck_collisions_with_base_plane
is set to true, all grasp points will be checked for collisions between the gripper and the calibrated base plane, and only grasp points at which the gripper would not collide with the base plane will be returned.Via the REST-API, this parameter can be set as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/parameters?check_collisions_with_base_plane=<value>PUT http://<host>/api/v1/nodes/rc_silhouettematch/parameters?check_collisions_with_base_plane=<value>
check_collisions_with_matches
(Check Collisions with Matches)¶
This parameter is only used when collision checking is enabled by passing a gripper to the
detect_object
service call or by enabling thecheck_collisions
runtime parameter. Ifcheck_collisions_with_matches
is set to true, all grasp points will be checked for collisions between the gripper and all other detected objects (not limited tomax_number_of_detected_objects
), and only grasp points at which the gripper would not collide with any other detected object will be returned.Via the REST-API, this parameter can be set as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/parameters?check_collisions_with_matches=<value>PUT http://<host>/api/v1/nodes/rc_silhouettematch/parameters?check_collisions_with_matches=<value>
check_collisions_with_point_cloud
(Check Collisions with Point Cloud)¶
This parameter is only used when collision checking is enabled by passing a gripper to the
detect_object
service call or by enabling thecheck_collisions
runtime parameter. Ifcheck_collisions_with_point_cloud
set to true, all grasp points will be checked for collisions between the gripper a watertight version of the point cloud, and only grasp points at which the gripper would not collide with this point cloud will be returned.Via the REST-API, this parameter can be set as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/parameters?check_collisions_with_point_cloud=<value>PUT http://<host>/api/v1/nodes/rc_silhouettematch/parameters?check_collisions_with_point_cloud=<value>
point_cloud_enhancement
(Enhance with Base Plane)¶
This parameter is only considered when
check_collisions_with_point_cloud
is true and the object detection was triggered withoutobject_plane_detection
. By default,point_cloud_enhancement
is set toOff
(Off). Ifpoint_cloud_enhancement
is set toReplaceBright
(Replace Bright Image Pixels), the calibrated base plane will be used to enhance the point cloud that is used for collision checking. For this, the depth values of all bright image pixels inside the image or, if set, the 2D region of interest will be set to the depth of the calibrated base plane. This parameter should be used when dark objects are placed on an untextured bright background, e.g. on a light table.Via the REST-API, this parameter can be set as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/parameters?point_cloud_enhancement=<value>PUT http://<host>/api/v1/nodes/rc_silhouettematch/parameters?point_cloud_enhancement=<value>
check_collisions_during_retraction
(Check Collisions during Retraction)¶
This parameter is only used when collision checking is enabled by passing a gripper to the
detect_object
service call or by enabling thecheck_collisions
runtime parameter. Whencheck_collisions_during_retraction
is enabled and a load carrier and a pre-grasp offset are given, each grasp point will be checked for collisions between the object in the gripper and the load carrier walls during retraction. This collision checking is performed along the full linear trajectory from the grasp point back to the pre-grasp position. Only collision-free grasp points will be returned.Via the REST-API, this parameter can be set as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/parameters?check_collisions_during_retraction=<value>PUT http://<host>/api/v1/nodes/rc_silhouettematch/parameters?check_collisions_during_retraction=<value>
Status values¶
This module reports the following status values:
Name | Description |
---|---|
data_acquisition_time |
Time in seconds required by the last active service to acquire images |
last_timestamp_processed |
The timestamp of the last processed dataset |
load_carrier_detection_time |
Processing time of the last load carrier detection in seconds |
processing_time |
Processing time of the last detection (including load carrier detection) in seconds |
Services¶
The user can explore and call the rc_silhouettematch
module’s services,
e.g. for development and testing, using the
REST-API interface or
the rc_cube
Web GUI.
The SilhouetteMatch module offers the following services.
detect_object
¶
Triggers an object detection as described in Detection of objects and returns the pose of all found object instances.
Details
All images used by the service are guaranteed to be newer than the service trigger time.
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/detect_object
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/detect_objectRequired arguments:
object_id
inobject_to_detect
: ID of the template which should be detected.
pose_frame
: see Hand-eye calibration.Potentially required arguments:
robot_pose
: see Hand-eye calibration.Optional arguments:
object_plane_detection
: false if the objects are placed on a calibrated base plane, true if the objects’ surfaces are planar and the base plane is unknown or the objects are located on multiple different planes, e.g. stacks.
offset
: offset in meters by which the base-plane calibration will be shifted towards the camera.
load_carrier_id
: ID of the load carrier which contains the items to be detected.
collision_detection
: see Collision checking within other modules.The definition for the request arguments with corresponding datatypes is:
{ "args": { "collision_detection": { "gripper_id": "string", "pre_grasp_offset": { "x": "float64", "y": "float64", "z": "float64" } }, "load_carrier_id": "string", "object_plane_detection": "bool", "object_to_detect": { "object_id": "string", "region_of_interest_2d_id": "string" }, "offset": "float64", "pose_frame": "string", "robot_pose": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } } } }The maximum number of returned instances can be controlled with the
max_number_of_detected_objects
parameter.
object_id
: ID of the detected template.
instances
: list of detected object instances, ordered according to the chosen sorting strategy.
grasps
: list of grasps on the detected objects, ordered according to the chosen sorting strategy. Theinstance_uuid
gives the reference to the detected object ininstances
this grasp belongs to. The list of returned grasps will be trimmed to the 100 best grasps if more reachable grasps are found. Each grasp contains a flagcollision_checked
and agripper_id
(see Collision checking within other modules).
load_carriers
: list of detected load carriers.
timestamp
: timestamp of the image set the detection ran on.
return_code
: holds possible warnings or error codes and messages.The definition for the response with corresponding datatypes is:
{ "name": "detect_object", "response": { "grasps": [ { "collision_checked": "bool", "gripper_id": "string", "id": "string", "instance_uuid": "string", "pose": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "pose_frame": "string", "priority": "int8", "timestamp": { "nsec": "int32", "sec": "int32" }, "uuid": "string" } ], "instances": [ { "grasp_uuids": [ "string" ], "id": "string", "object_id": "string", "pose": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "pose_frame": "string", "timestamp": { "nsec": "int32", "sec": "int32" }, "uuid": "string" } ], "load_carriers": [ { "height_open_side": "float64", "id": "string", "inner_dimensions": { "x": "float64", "y": "float64", "z": "float64" }, "outer_dimensions": { "x": "float64", "y": "float64", "z": "float64" }, "overfilled": "bool", "pose": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "pose_frame": "string", "rim_ledge": { "x": "float64", "y": "float64" }, "rim_step_height": "float64", "rim_thickness": { "x": "float64", "y": "float64" }, "type": "string" } ], "object_id": "string", "return_code": { "message": "string", "value": "int16" }, "timestamp": { "nsec": "int32", "sec": "int32" } } }
calibrate_base_plane
¶
Triggers the calibration of the base plane, as described in Base-plane calibration.
Details
A successful base-plane calibration is stored persistently on the rc_cube and returned by this service. The base-plane calibration is persistent over firmware updates and rollbacks.
All images used by the service are guaranteed to be newer than the service trigger time.
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/calibrate_base_plane
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/calibrate_base_planeRequired arguments:
plane_estimation_method
: method to use for base-plane calibration. Valid values areSTEREO
,APRILTAG
,MANUAL
.
pose_frame
: see Hand-eye calibration.Potentially required arguments:
plane
ifplane_estimation_method
isMANUAL
: plane that will be set as base-plane calibration.
robot_pose
: see Hand-eye calibration.
region_of_interest_2d_id
: ID of the region of interest for base-plane calibration.Optional arguments:
offset
: offset in meters by which the estimated plane will be shifted towards the camera.
plane_preference
instereo
: whether the plane closest to or farthest from the camera should be used as base plane. This option can be set only ifplane_estimation_method
isSTEREO
. Valid values areCLOSEST
andFARTHEST
. If not set, the default isFARTHEST
.The definition for the request arguments with corresponding datatypes is:
{ "args": { "offset": "float64", "plane": { "distance": "float64", "normal": { "x": "float64", "y": "float64", "z": "float64" } }, "plane_estimation_method": "string", "pose_frame": "string", "region_of_interest_2d_id": "string", "robot_pose": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "stereo": { "plane_preference": "string" } } }
plane
: calibrated base plane.
timestamp
: timestamp of the image set the calibration ran on.
return_code
: holds possible warnings or error codes and messages.The definition for the response with corresponding datatypes is:
{ "name": "calibrate_base_plane", "response": { "plane": { "distance": "float64", "normal": { "x": "float64", "y": "float64", "z": "float64" }, "pose_frame": "string" }, "return_code": { "message": "string", "value": "int16" }, "timestamp": { "nsec": "int32", "sec": "int32" } } }
get_base_plane_calibration
¶
Returns the configured base-plane calibration.
Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/get_base_plane_calibration
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/get_base_plane_calibrationRequired arguments:
pose_frame
: see Hand-eye calibration.Potentially required arguments:
robot_pose
: see Hand-eye calibration.The definition for the request arguments with corresponding datatypes is:
{ "args": { "pose_frame": "string", "robot_pose": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } } } }The definition for the response with corresponding datatypes is:
{ "name": "get_base_plane_calibration", "response": { "plane": { "distance": "float64", "normal": { "x": "float64", "y": "float64", "z": "float64" }, "pose_frame": "string" }, "return_code": { "message": "string", "value": "int16" } } }
delete_base_plane_calibration
¶
Deletes the configured base-plane calibration.
Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/delete_base_plane_calibration
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/delete_base_plane_calibrationThis service has no arguments.The definition for the response with corresponding datatypes is:
{ "name": "delete_base_plane_calibration", "response": { "return_code": { "message": "string", "value": "int16" } } }
set_preferred_orientation
¶
Persistently stores the preferred orientation of the gripper to compute the reachability of the grasps, which is used for filtering and, optionally, sorting the grasps returned by the
detect_object
service (see Setting the preferred orientation of the TCP).Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/set_preferred_orientation
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/set_preferred_orientationThe definition for the request arguments with corresponding datatypes is:
{ "args": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "pose_frame": "string" } }The definition for the response with corresponding datatypes is:
{ "name": "set_preferred_orientation", "response": { "return_code": { "message": "string", "value": "int16" } } }
get_preferred_orientation
¶
Returns the preferred orientation of the gripper to compute the reachability of the grasps, which is used for filtering and, optionally, sorting the grasps returned by the
detect_object
service (see Setting the preferred orientation of the TCP).Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/get_preferred_orientation
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/get_preferred_orientationThis service has no arguments.The definition for the response with corresponding datatypes is:
{ "name": "get_preferred_orientation", "response": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "pose_frame": "string", "return_code": { "message": "string", "value": "int16" } } }
set_sorting_strategies
¶
Persistently stores the sorting strategy for sorting the grasps and detected objects returned by the
detect_object
service (see Detection of objects).Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/set_sorting_strategies
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/set_sorting_strategiesOnly one strategy may have a
weight
greater than 0. If allweight
values are set to 0, the module will use the default sorting strategy.If the weight for
direction
is set, thevector
must contain the direction vector andpose_frame
must be eithercamera
orexternal
.The definition for the request arguments with corresponding datatypes is:
{ "args": { "direction": { "pose_frame": "string", "vector": { "x": "float64", "y": "float64", "z": "float64" }, "weight": "float64" }, "preferred_orientation": { "weight": "float64" } } }The definition for the response with corresponding datatypes is:
{ "name": "set_sorting_strategies", "response": { "return_code": { "message": "string", "value": "int16" } } }
get_sorting_strategies
¶
Returns the sorting strategy for sorting the grasps and detected objects returned by the
detect_object
service (see Detection of objects).Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/get_sorting_strategies
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/get_sorting_strategiesThis service has no arguments.All
weight
values are 0 when the module uses the default sorting strategy.The definition for the response with corresponding datatypes is:
{ "name": "get_sorting_strategies", "response": { "direction": { "pose_frame": "string", "vector": { "x": "float64", "y": "float64", "z": "float64" }, "weight": "float64" }, "preferred_orientation": { "weight": "float64" }, "return_code": { "message": "string", "value": "int16" } } }
trigger_dump
¶
Triggers dumping of the detection that corresponds to the given timestamp, or the latest detection, if no timestamp is given. The dumps are saved to the connected USB drive.
Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/trigger_dump
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/trigger_dumpThe definition for the request arguments with corresponding datatypes is:
{ "args": { "comment": "string", "timestamp": { "nsec": "int32", "sec": "int32" } } }The definition for the response with corresponding datatypes is:
{ "name": "trigger_dump", "response": { "return_code": { "message": "string", "value": "int16" } } }
reset_defaults
¶
Resets all parameters of the module to its default values, as listed in above table. Also resets preferred orientation and sorting strategies. The reset does not apply to templates and base-plane calibration.
Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/reset_defaults
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/reset_defaultsThis service has no arguments.The definition for the response with corresponding datatypes is:
{ "name": "reset_defaults", "response": { "return_code": { "message": "string", "value": "int16" } } }
set_region_of_interest_2d
(deprecated)¶
Persistently stores a 2D region of interest on the rc_cube.
Details
This service can be called as follows.
This service is not available in API version 2. Use set_region_of_interest_2d inrc_roi_db
instead.PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/set_region_of_interest_2d
get_regions_of_interest_2d
(deprecated)¶
Returns the configured 2D regions of interest with the requested
region_of_interest_2d_ids
.Details
This service can be called as follows.
This service is not available in API version 2. Use get_regions_of_interest_2d inrc_roi_db
instead.PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/get_regions_of_interest_2d
delete_regions_of_interest_2d
(deprecated)¶
Deletes the configured 2D regions of interest with the requested
region_of_interest_2d_ids
.Details
This service can be called as follows.
This service is not available in API version 2. Use delete_regions_of_interest_2d inrc_roi_db
instead.PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/delete_regions_of_interest_2d
Internal services¶
The following services for configuring grasps can change in future without notice. Setting, retrieving and deleting grasps is recommend to be done via the Web GUI.
Note
Configuring grasps is global for all templates on the rc_cube and affects all camera pipelines.
set_grasp
¶
Persistently stores a grasp for the given object template on the rc_cube. All configured grasps are persistent over firmware updates and rollbacks.
Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/set_grasp
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/set_graspDetails for the definition of the
grasp
type are given in Setting of grasp points.The definition for the request arguments with corresponding datatypes is:
{ "args": { "grasp": { "gripper_id": "string", "id": "string", "pose": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "priority": "int8", "replication": { "max_x_deg": "float64", "min_x_deg": "float64", "origin": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "step_x_deg": "float64" }, "template_id": "string" } } }The definition for the response with corresponding datatypes is:
{ "name": "set_grasp", "response": { "return_code": { "message": "string", "value": "int16" } } }
set_all_grasps
¶
Replaces the list of grasps for the given object template on the rc_cube.
Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/set_all_grasps
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/set_all_graspsDetails for the definition of the
grasp
type are given in Setting of grasp points.The definition for the request arguments with corresponding datatypes is:
{ "args": { "grasps": [ { "gripper_id": "string", "id": "string", "pose": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "priority": "int8", "replication": { "max_x_deg": "float64", "min_x_deg": "float64", "origin": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "step_x_deg": "float64" }, "template_id": "string" } ], "template_id": "string" } }The definition for the response with corresponding datatypes is:
{ "name": "set_all_grasps", "response": { "return_code": { "message": "string", "value": "int16" } } }
get_grasps
¶
Returns all configured grasps which have the requested
grasp_ids
and belong to the requestedtemplate_ids
.Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/get_grasps
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/get_graspsIf no
grasp_ids
are provided, all grasps belonging to the requestedtemplate_ids
are returned. If notemplate_ids
are provided, all grasps with the requestedgrasp_ids
are returned. If neither IDs are provided, all configured grasps are returned.The definition for the request arguments with corresponding datatypes is:
{ "args": { "grasp_ids": [ "string" ], "template_ids": [ "string" ] } }The definition for the response with corresponding datatypes is:
{ "name": "get_grasps", "response": { "grasps": [ { "gripper_id": "string", "id": "string", "pose": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "priority": "int8", "replication": { "max_x_deg": "float64", "min_x_deg": "float64", "origin": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "step_x_deg": "float64" }, "template_id": "string" } ], "return_code": { "message": "string", "value": "int16" } } }
delete_grasps
¶
Deletes all grasps with the requested
grasp_ids
that belong to the requestedtemplate_ids
.Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/delete_grasps
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/delete_graspsIf no
grasp_ids
are provided, all grasps belonging to the requestedtemplate_ids
are deleted. Thetemplate_ids
list must not be empty.The definition for the request arguments with corresponding datatypes is:
{ "args": { "grasp_ids": [ "string" ], "template_ids": [ "string" ] } }The definition for the response with corresponding datatypes is:
{ "name": "delete_grasps", "response": { "return_code": { "message": "string", "value": "int16" } } }
get_symmetric_grasps
¶
Returns all grasps that are symmetric to the given grasp.
Details
This service can be called as follows.
PUT http://<host>/api/v2/pipelines/<0,1,2,3>/nodes/rc_silhouettematch/services/get_symmetric_grasps
PUT http://<host>/api/v1/nodes/rc_silhouettematch/services/get_symmetric_graspsDetails for the definition of the
grasp
type are given in Setting of grasp points.The definition for the request arguments with corresponding datatypes is:
{ "args": { "grasp": { "pose": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "replication": { "max_x_deg": "float64", "min_x_deg": "float64", "origin": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "step_x_deg": "float64" }, "template_id": "string" } } }The first grasp in the returned list is the one that was passed with the service call. If the object template does not have an exact symmetry, only the grasp passed with the service call will be returned. If the object template has a continuous symmetry (e.g. a cylindrical object), only 12 equally spaced sample grasps will be returned.
Details for the definition of the
grasp
type are given in Setting of grasp points.The definition for the response with corresponding datatypes is:
{ "name": "get_symmetric_grasps", "response": { "grasps": [ { "pose": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "replication": { "max_x_deg": "float64", "min_x_deg": "float64", "origin": { "orientation": { "w": "float64", "x": "float64", "y": "float64", "z": "float64" }, "position": { "x": "float64", "y": "float64", "z": "float64" } }, "step_x_deg": "float64" }, "template_id": "string" } ], "return_code": { "message": "string", "value": "int16" } } }
Return codes¶
Each service response contains a return_code
,
which consists of a value
plus an optional message
.
A successful service returns with a return_code
value of 0
.
Negative return_code
values indicate that the service failed.
Positive return_code
values indicate that the service succeeded with additional information.
Code | Description |
---|---|
0 | Success |
-1 | An invalid argument was provided. |
-3 | An internal timeout occurred, e.g. during object detection. |
-4 | Data acquisition took longer than allowed. |
-7 | Data could not be read or written to persistent storage. |
-8 | Module is not in a state in which this service can be called. E.g. detect_object cannot be called if there is no base-plane calibration. |
-10 | New element could not be added as the maximum storage capacity of regions of interest or templates has been exceeded. |
-100 | An internal error occurred. |
-101 | Detection of the base plane failed. |
-102 | The hand-eye calibration changed since the last base-plane calibration. |
-104 | Offset between the base plane normal and the camera’s line of sight exceeds 10 degrees. |
10 | The maximum storage capacity of regions of interest or templates has been reached. |
11 | An existing element was overwritten. |
100 | The requested load carrier was not detected in the scene. |
101 | None of the detected grasps is reachable. |
102 | The detected load carrier is empty. |
103 | All detected grasps are in collision. |
107 | The base plane was not transformed to the current camera pose, e.g. because no robot pose was provided during base-plane calibration. |
108 | The template is deprecated. |
109 | The plane for object detection does not fit to the load carrier, e.g. objects are below the load carrier floor. |
111 | The detection result’s pose could not be refined with the point cloud because the template’s outer contour is not closed. |
113 | No gripper was found for collision checking. |
114 | Collision checking during retraction was skipped, e.g. because no load carrier or no pre-grasp offset were given. |
151 | The object template has a continuous symmetry. |
999 | Additional hints for application development |
Template API¶
For template upload, download, listing and removal, special REST-API endpoints are provided. Templates can also be uploaded, downloaded and removed via the Web GUI. The templates include the grasp points, if grasp points have been configured. Up to 50 templates can be stored persistently on the rc_cube.
-
GET
/templates/rc_silhouettematch
¶ Get list of all rc_silhouettematch templates.
Template request
GET /api/v2/templates/rc_silhouettematch HTTP/1.1
Template response
HTTP/1.1 200 OK Content-Type: application/json [ { "id": "string" } ]
Response Headers: - Content-Type – application/json application/ubjson
Status Codes: - 200 OK – successful operation (returns array of Template)
- 404 Not Found – node not found
Referenced Data Models:
-
GET
/templates/rc_silhouettematch/{id}
¶ Get a rc_silhouettematch template. If the requested content-type is application/octet-stream, the template is returned as file.
Template request
GET /api/v2/templates/rc_silhouettematch/<id> HTTP/1.1
Template response
HTTP/1.1 200 OK Content-Type: application/json { "id": "string" }
Parameters: - id (string) – id of the template (required)
Response Headers: - Content-Type – application/json application/ubjson application/octet-stream
Status Codes: - 200 OK – successful operation (returns Template)
- 404 Not Found – node or template not found
Referenced Data Models:
-
PUT
/templates/rc_silhouettematch/{id}
¶ Create or update a rc_silhouettematch template.
Template request
PUT /api/v2/templates/rc_silhouettematch/<id> HTTP/1.1 Accept: multipart/form-data application/json
Template response
HTTP/1.1 200 OK Content-Type: application/json { "id": "string" }
Parameters: - id (string) – id of the template (required)
Form Parameters: - file – template or dxf file (required)
- object_height – object height in meters, required when uploading dxf (optional)
- units – Units for dxf file if not embedded in dxf (one of
mm
,cm
,m
,in
,ft
) (optional)
Request Headers: - Accept – multipart/form-data application/json
Response Headers: - Content-Type – application/json application/ubjson
Status Codes: - 200 OK – successful operation (returns Template)
- 400 Bad Request – Template is not valid or max number of templates reached
- 403 Forbidden – forbidden, e.g. because there is no valid license for this module.
- 404 Not Found – node or template not found
- 413 Request Entity Too Large – Template too large
Referenced Data Models:
-
DELETE
/templates/rc_silhouettematch/{id}
¶ Remove a rc_silhouettematch template.
Template request
DELETE /api/v2/templates/rc_silhouettematch/<id> HTTP/1.1 Accept: application/json application/ubjson
Parameters: - id (string) – id of the template (required)
Request Headers: - Accept – application/json application/ubjson
Response Headers: - Content-Type – application/json application/ubjson
Status Codes: - 200 OK – successful operation
- 403 Forbidden – forbidden, e.g. because there is no valid license for this module.
- 404 Not Found – node or template not found