2024-03-29T09:19:33Z
https://zenodo.org/oai2d
oai:zenodo.org:1209203
2020-01-21T07:23:05Z
user-sarafun
openaire_data
user-eu
Stefanos Doltsinis
Marios Krestenitis
Zoe Doulgeri
2018-03-28
<p>The Dataset is used for training and testing a machine learning classifier in order to achieve real-time detection of successful snap-fit assemblies.</p>
<p>The Dataset contains force profiles on the axis of motion (assembly), captured during a robotic and a human assembly process of two different snap-fit assembly types, namely cantilever and annular. In robotic assembly, the process is done automatically where a robot holds one of the two parts and pushes it against the other, until the process is characterized as successful or failed. In the human assembly process, a human assembles the two parts while the robot acts as a smart sensor and captures the developed forces in the axis of assembly.</p>
<p>The data set is split into 8 files, 4 for each snap fit type. One containing force profiles from the human based process (50 assembly cases) and one containing force profiles from the robot based process (60 assembly cases). Their labels (successful or failure) are also included in separate files.</p>
https://doi.org/10.5281/zenodo.1209203
oai:zenodo.org:1209203
Zenodo
https://zenodo.org/communities/sarafun
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.1209202
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
DS.04.CERTH.SnapFitForceProfiles
info:eu-repo/semantics/other
oai:zenodo.org:1209134
2020-01-24T19:22:06Z
user-sarafun
openaire_data
user-eu
Andreas Doumanoglou
2018-03-28
<p>Dataset of RGB and depth images reflecting two usage scenarios, one representing domestic<br>
environments and the other a bin-picking scenario found in industrial settings.</p>
https://doi.org/10.5281/zenodo.1209134
oai:zenodo.org:1209134
Zenodo
https://zenodo.org/communities/sarafun
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.1209130
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
DS.03.CERTH.CVPR2016Dataset
info:eu-repo/semantics/other
oai:zenodo.org:1209131
2020-01-24T19:22:05Z
user-sarafun
openaire_data
user-eu
Andreas Doumanoglou
2018-03-28
<p>Dataset of RGB and depth images reflecting two usage scenarios, one representing domestic<br>
environments and the other a bin-picking scenario found in industrial settings.</p>
https://doi.org/10.5281/zenodo.1209131
oai:zenodo.org:1209131
Zenodo
https://zenodo.org/communities/sarafun
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.1209130
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
DS.03.CERTH.CVPR2016Dataset
info:eu-repo/semantics/other
oai:zenodo.org:1209145
2020-01-21T07:22:18Z
user-sarafun
openaire_data
user-eu
Christos Papadopoulos
2018-03-28
<p>Dataset generated by logging wrench forces of the robot’s F/T sensor in various contact configurations between the assembly parts.</p>
https://doi.org/10.5281/zenodo.1209145
oai:zenodo.org:1209145
Zenodo
https://zenodo.org/communities/sarafun
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.1209144
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
DS.05.CERTH.ContactEvaluationData
info:eu-repo/semantics/other
oai:zenodo.org:1209272
2020-01-24T19:22:54Z
user-sarafun
openaire_data
McIntyre, Joseph
Remazeilles, Anthony
Fernandez, Asier
Racines, Irati
2018-03-28
<p>Recording of experiments in which volunteer human subjects performed a sliding insertion task using instrumented objects to measure the kinematics and interaction forces during unimanual and bimanual manipulation. </p>
<p>Data were acquired using custom instrumented objects that included infrared markers for 3D motion tracking by a CodaMotion tracking system and interaction forces measured by OptoForce 6 d.o.f. force/torque sensors. </p>
https://doi.org/10.5281/zenodo.1209272
oai:zenodo.org:1209272
Zenodo
https://zenodo.org/communities/sarafun
https://doi.org/10.5281/zenodo.1209271
info:eu-repo/semantics/restrictedAccess
DS.01.TECNALIA .Human_Performance_of_Bimanual_Assembly
info:eu-repo/semantics/other
oai:zenodo.org:1169254
2020-01-24T19:24:19Z
user-sarafun
openaire_data
user-eu
Papadopoulos Christos
2018-02-08
<p>In this dataset we include the questionnaire ratings and time to completion (teaching an assembly) for each test subject that we used in the journal article “An Advanced Human-Robot Interaction Interface for Collaborative Robotic Assembly Tasks”.</p>
https://doi.org/10.5281/zenodo.1169254
oai:zenodo.org:1169254
Zenodo
https://zenodo.org/communities/sarafun
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.1169253
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
An Advanced Human-Robot Interaction Interface for Collaborative Robotic Assembly Tasks, (2018-02-08)
DS.02.CERTH.IJERTCS2018Dataset
info:eu-repo/semantics/other
oai:zenodo.org:1171979
2020-01-24T19:25:32Z
user-sarafun
openaire_data
user-eu
Ioannis Mariolis
2018-02-12
<p>Dataset used for keyframe extraction in laboratory environment. An instructor person will pick up two small objects and, afterwards will assembly them. This dataset was used in the conference paper "Assembly by Demonstration using Advanced Human Robot Interaction and a Knowledge Integration Framework".</p>
https://doi.org/10.5281/zenodo.1171979
oai:zenodo.org:1171979
Zenodo
https://zenodo.org/communities/sarafun
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.1171978
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
FAIM2017, 27th International Conference on Flexible Automation and Intelligent Manufacturing, Modena, Italy, 27-30 June, 2017
DS.01.CERTH.FAIM2017Dataset
info:eu-repo/semantics/other
oai:zenodo.org:1172600
2020-01-24T19:24:39Z
user-sarafun
openaire_data
user-eu
Martin Karlsson, Anders Robertsson, Rolf Johansson
2018-02-13
<p>Dataset used for evaluation of a recurrent neural network (RNN) for recognition of transients, in order to detect events during robotic assembly. Inputs are robot joint torque data. Outputs are probabilities that the event is occurring, as estimated by the RNN. Possible to use for detection models other than RNNs.</p>
<p>Used as experimental results in the paper Martin Karlsson, Anders Robertsson, Rolf Johansson, <em>Detection and Control of Contact Force Transientsin Robotic Manipulation without a Force Sensor, </em>by to be presented at ICRA, Brisbane, May 2018.</p>
https://doi.org/10.5281/zenodo.1172600
oai:zenodo.org:1172600
Zenodo
https://zenodo.org/communities/sarafun
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.1172599
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Industrial Robotics, Machine Learning, Transient Detection, Sequential Data
DS.01.ULUND.TransientDetection
info:eu-repo/semantics/other
oai:zenodo.org:1172620
2020-01-24T19:23:21Z
user-sarafun
openaire_data
user-eu
Meier, Martin
2018-02-13
<p>Raw data recorded for the publication "Tactile Convolutional Networks for Online Slip and Rotation Detection" in rosbag format. Each .bag file contains recordings of two tactile sensors sampled with 1kHz as "sensor_msgs/Image" and a third channel for data labeling in the format "sr_robot_msgs/UBI0All". Detailed informations about the preprocessing and labeling are in the publication.</p>
https://doi.org/10.5281/zenodo.1172620
oai:zenodo.org:1172620
Zenodo
https://doi.org/10.1007/978-3-319-44781-0_2
https://zenodo.org/communities/sarafun
https://zenodo.org/communities/eu
https://doi.org/10.5281/zenodo.1172619
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
tactile sensing
Dataset for the publication: Tactile Convolutional Networks for Online Slip and Rotation Detection
info:eu-repo/semantics/other