Dataset Open Access

Dataset of EU SPIRIT Project

EU SPIRIT Consortium

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  <identifier identifierType="DOI">10.5281/zenodo.4767861</identifier>
      <creatorName>EU SPIRIT Consortium</creatorName>
    <title>Dataset of EU SPIRIT Project</title>
    <date dateType="Issued">2021-05-17</date>
  <resourceType resourceTypeGeneral="Dataset"/>
    <alternateIdentifier alternateIdentifierType="url"></alternateIdentifier>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.4730442</relatedIdentifier>
    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;The data available for future research are 14 kind of files, files are organized in different category based on the usage that can be carried out with the data. Below the information for each kind of data is reported:&lt;/p&gt;

	&lt;li&gt;To develop and test calibration methods for hand-eye calibration with image-based sensors
		&lt;li&gt;Acquired images - This data set contains either images of a calibration pattern like a checkerboard, or in case of the GridSense sensor, point clouds that can be matched without knowledge of the sensor positions. Hence they can be used to compute the sensor motion in the point cloud frame.&lt;/li&gt;
		&lt;li&gt;Pose information per image &amp;ndash; For each of the acquired image, a .txt file containing the referenced pose is provided. This file contains the position (roto-translation 4x4 matrix) of the robot TCP in the robot base frame. This data can be used for recovering the position of the sensor when applying the desired hand-eye transformation.&lt;/li&gt;
		&lt;li&gt;Calibration result &amp;ndash; optional &amp;ndash; When provided, this data contains the optimized hand-eye transformation, i.e. computed with the calibration procedure developed in the SPIRIT project.&lt;/li&gt;
		&lt;li&gt;Initial guess of calibration (by design) &amp;ndash; This data contains the roto-translation 4x4 matrix that can be used as initial guess for the actual hand-eye transform computation. This is retrieved by design from CAD drawings.&lt;/li&gt;
	&lt;li&gt;To perform trajectory planning for robotic inspection tasks
		&lt;li&gt;3D model of object &amp;ndash; This data contains the file CAD of the object. It is available on request.&lt;/li&gt;
		&lt;li&gt;3D model of workcell (at least robot + part); stp file - This data contains the file CAD of the workcell&lt;/li&gt;
		&lt;li&gt;kinematic model of robot &amp;ndash; This file contains the kinematic model of the robot&lt;/li&gt;
		&lt;li&gt;Part calibration, hand-eye calibration &amp;ndash; This file contains a 4x4 transformation matrix that defines the position and the orientation of the part within the workcell.&lt;/li&gt;
		&lt;li&gt;Resulting trajectory, position of camera relative to part &amp;ndash; This data contains the trajectory of the robot stored in binary table in the HDF5 format. In each file there are four tables:
			&lt;li&gt;Timestamp: 1 column x N rows table, where N is the number of position in the trajectory and each row contains the time expressed as seconds.&lt;/li&gt;
			&lt;li&gt;Component 0: contains 6 columns x N rows table, the 6 columns contains the robot joint position (rad) at the corresponding timestamp&lt;/li&gt;
			&lt;li&gt;Component 1: this table exists only if there are two moving components. For test case 1, it contains the position of the conveyor belt. For test case 2 it contains the joint position of the second robot.&lt;/li&gt;
			&lt;li&gt;ID: 1 column x N rows table , used internally by the SPIRIT SW to turn on or off the laser or to know the viewpoints associated to the joint position&lt;/li&gt;
		&lt;li&gt;Video of full scanning process &amp;ndash; This file is a video of the scanning process.&lt;/li&gt;
	&lt;li&gt;To develop image mapping/stitching algorithms for 3D objects
		&lt;li&gt;3D model of object &amp;ndash; This data contains the file CAD of the object. It is available on request.&lt;/li&gt;
		&lt;li&gt;acquired image data - Images/ point clouds that were acquired at a scan of the test parts&lt;/li&gt;
		&lt;li&gt;pose information per image &amp;ndash; A Cartesian sensor position for each image/ point cloud.&amp;nbsp;&lt;/li&gt;
		&lt;li&gt;calibration data - Information about the intrinsic sensor parameters.&lt;/li&gt;
	&lt;li&gt;Defect data &amp;amp; detection results
		&lt;li&gt;Defect documentation &amp;ndash; This file contains a report about the defect monitored during the scanning process&lt;/li&gt;
		&lt;li&gt;Performance data &amp;ndash; This file contains an evaluation of the results obtained referring to the KPI of the project.&lt;/li&gt;
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/779431/">779431</awardNumber>
      <awardTitle>A software framework for the efficient setup of industrial inspection robots</awardTitle>
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