Adaptive Multi-Robot Timber Construction Dataset
收藏DataCite Commons2024-03-22 更新2024-07-13 收录
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https://datacommons.princeton.edu/discovery/doi/10.34770/0w80-p436
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资源简介:
The deposit contains data related to the adaptive multi-robotic assembly
of timber structures. This data was collected across two experiments; the
first experiment utilizes a pose-based adaptive fabrication method applied
to a nail-laminated timber module, and the second experiment utilizes a
topology-based adaptive fabrication method applied to a spatial wall frame
module. The first experiment data contains the pose measurements for each
element in the assembly structure and overall point cloud scans of the
final as-built assemblies. Pose measurements were derived from a defined
set of profile scans using a profile scanner attached to the end of an
industrial robot arm, using the methods detailed in the corresponding
paper. This scanner has a profile resolution of 0.150 mm, a depth
resolution of 0.019 mm, and a linearity of ±0.01% of the measurement
range. These pose measurements were used as inputs to the adaptive control
loop, and also served as measures of deviation when compared to a
benchmark case assembly with no adaptation. The point cloud scans were
likewise obtained using the profile scanner by controlling the industrial
robot to perform a linear sweep across the final structure, capturing a
profile of points every 2 mm. Since the field of view of the sensor was
insufficient to scan the entire structure in a single pass, multiple
passes were made with a slight overlap, and these point cloud segments
were stitched together using the calibrated end-effector position of the
industrial robot. The point clouds were manually filtered to remove
background elements, such as the assembly platform and clamping elements.
These point clouds were utilized to compute surface deviations of the
adaptive and benchmark assembly cases against an idealized digital model.
The deviation data corresponds to the order of points in their
corresponding point cloud files. The second experiment did not utilize
pose measurements, and, therefore, the database only includes the point
cloud scan and deviation calculations of the as-built wall module. For
more details, please see the corresponding paper.
提供机构:
Princeton University
创建时间:
2024-03-13



