Documentation Index Fetch the complete documentation index at: https://mintlify.com/dfki-ric/uxo-dataset2024/llms.txt
Use this file to discover all available pages before exploring further.
Overview The UXO Dataset uses a hierarchical transform system to define spatial relationships between coordinate frames. The transform tree consists of two main groups:
Setup transforms : Define the sensor mounting configuration (AR3 robot arm, ARIS sonar, GoPro camera)Target transforms : Define the positions of UXO objects in the world frame
All transforms are stored in /calibration/transforms.yaml and can be loaded programmatically using the transform manager.
Each transform consists of:
Translation : 3D position offset (x, y, z) in metersRotation : Quaternion (x, y, z, w) representing orientation
Transforms are defined relative to a parent frame, creating a hierarchical tree structure.
The sensor setup follows this frame hierarchy:
setup/portal_crane └── setup/ar3 ├── setup/aris │ └── setup/sonar ├── setup/gopro_mounting_hole │ └── setup/gopro_mounting_axis │ └── setup/camera
Portal Crane to AR3 Robot Defines the AR3 robot arm base relative to the portal crane frame.
frame_id : "setup/ar3" parent_frame_id : "setup/portal_crane" translation : x : 0.0 y : 0.174 z : -0.338 rotation : x : 0.0 y : 1.0 z : 0.0 w : 0.0
The AR3 is offset 17.4 cm in Y and -33.8 cm in Z from the portal crane, with a 180° rotation around the Y-axis.
AR3 to ARIS Sonar ARIS Base Frame
Sonar Imaging Frame
frame_id : "setup/aris" parent_frame_id : "setup/ar3" translation : x : 0.0 y : 0.0 z : 0.0 rotation : x : 0.0 y : 0.0 z : 0.0 w : 1.0
The ARIS base frame is coincident with the AR3 end-effector. frame_id : "setup/sonar" parent_frame_id : "setup/aris" translation : x : -0.108725 y : 0.0 z : 0.0 rotation : x : 0.5 y : 0.5 z : 0.5 w : 0.5
The sonar imaging frame is offset -10.87 cm in X with a compound rotation. AR3 to GoPro Camera The GoPro camera mount has an intermediate frame hierarchy:
GoPro Mounting Hole Frame
frame_id : "setup/gopro_mounting_hole" parent_frame_id : "setup/ar3" translation : x : 0.1265 y : 0.023 z : -0.1055 rotation : x : 0.0 y : 0.0 z : 0.0 w : 1.0
Reference point for the GoPro mounting bracket.
GoPro Mounting Axis Frame
frame_id : "setup/gopro_mounting_axis" parent_frame_id : "setup/gopro_mounting_hole" translation : x : 0.02125 y : 0.0 z : -0.0075 rotation : x : 0.0 y : 0.0 z : 0.0 w : 1.0
Intermediate frame for mounting axis adjustments.
frame_id : "setup/camera" parent_frame_id : "setup/gopro_mounting_axis" translation : x : 0.01925 y : -0.0195 z : -0.0415 rotation : x : 0.5 y : 0.5 z : 0.5 w : 0.5
Final camera optical center frame with standard camera orientation. All target objects are positioned relative to the world frame. The dataset includes five UXO targets:
100lbs Bomb
Mortar Shell
Incendiary
Cylinder
100lbs Floor
frame_id : "target/100lbs" parent_frame_id : "world" translation : x : 1.251079 y : 1.592704 z : -1.489828 rotation : x : 0.0 y : 0.0 z : 0.0 w : 1.0
Position: (1.25m, 1.59m, -1.49m) frame_id : "target/mortar_shell" parent_frame_id : "world" translation : x : 1.263516 y : 1.4371 z : -1.51891 rotation : x : 0.0 y : 0.0 z : 0.0 w : 1.0
Position: (1.26m, 1.44m, -1.52m) frame_id : "target/incendiary" parent_frame_id : "world" translation : x : 1.2351 y : 1.409233 z : -1.530784 rotation : x : 0.0 y : 0.0 z : 0.0 w : 1.0
Position: (1.24m, 1.41m, -1.53m) frame_id : "target/cylinder" parent_frame_id : "world" translation : x : 1.277832 y : 1.399541 z : -1.461439 rotation : x : 0.0 y : 0.0 z : 0.0 w : 1.0
Position: (1.28m, 1.40m, -1.46m) frame_id : "target/100lbs_floor" parent_frame_id : "world" translation : x : 1.174003 y : 1.227536 z : -2.2411 rotation : x : 0.0 y : 0.0 z : 0.0 w : 1.0
Position: (1.17m, 1.23m, -2.24m) - on the pool floor The dataset provides a Python utility to load and work with transforms using the pytransform3d library.
import numpy as np from pytransform3d.transform_manager import TransformManager # Import from the exported dataset structure from dataset.calibration.tf_demo.transforms import get_tf_manager # Or if working directly with the source repository # from demo.transforms import get_tf_manager # Load the complete transform tree tm = get_tf_manager()
The transform manager automatically computes transformations between any two frames:
# Get transform from camera to a target camera_to_target = tm.get_transform( "setup/camera" , "target/100lbs" ) # Get transform from sonar to a target sonar_to_target = tm.get_transform( "setup/sonar" , "target/mortar_shell" ) # Get transform between sensors camera_to_sonar = tm.get_transform( "setup/camera" , "setup/sonar" )
Transforms are represented as 4x4 homogeneous transformation matrices:
# Transform matrix structure # [[R11, R12, R13, tx], # [R21, R22, R23, ty], # [R31, R32, R33, tz], # [ 0, 0, 0, 1]]
Where the 3x3 rotation matrix is in the upper-left, and the translation vector is in the right column.
Internal Implementation The transform loading process (from /workspace/source/demo/transforms.py:22-28):
for tf in tf_statics[ object ]: transform = pt.transform_from_pq( np.hstack(( np.array([tf[ 'translation' ][ 'x' ], tf[ 'translation' ][ 'y' ], tf[ 'translation' ][ 'z' ]]), np.array([tf[ 'rotation' ][ 'w' ], tf[ 'rotation' ][ 'x' ], tf[ 'rotation' ][ 'y' ], tf[ 'rotation' ][ 'z' ]])))) tm.add_transform(tf[ 'frame_id' ], tf[ 'parent_frame_id' ], transform)
The quaternion order in the YAML file is (x, y, z, w), but pytransform3d expects (w, x, y, z) format.
Coordinate Frame Conventions
World Frame : Fixed reference frame, typically aligned with the pool structureSetup Frames : Moving frames attached to the robotic systemCamera Frame : Follows standard computer vision convention (Z-forward, X-right, Y-down)Sonar Frame : Aligned with the ARIS imaging plane
File Location The transforms are stored in:
/calibration/transforms.yaml
The Python loader utility is located at:
