Author Organization: Max Planck Institute for Intelligent Systems
Author Name: Kuchenbecker, Katherine J.
1 to 9 of 9 Results
May 6, 2024
Mohan, Mayumi; Nunez, Cara M.; Kuchenbecker, Katherine J., 2024, "Data for “Closing the Loop in Minimally Supervised Human-Robot Interaction: Formative and Summative Feedback"", https://doi.org/10.17617/3.UPWT1Q, Edmond, V1
This Excel file provides the data required to perform the statistical analyses presented in the manuscript: "Closing the Loop in Minimally Supervised Human-Robot Interaction: Formative and Summative Feedback". Each of the nine included sheets contains a different subset of the co... |
Khojasteh, Behnam; Shao, Yitian; Kuchenbecker, Katherine J., 2024, "MPI-10: Haptic-Auditory Measurements from Tool-Surface Interactions", https://doi.org/10.17617/3.PM8R94, Edmond, V1
This dataset consists of haptic-auditory recordings as a human explores 10 surfaces with 3 steel tools, including accelerations of the tool and finger, force and torque applied to the surface, and contact sounds. |
Gong, Yijie; Javot, Bernard; Lauer, Anja Patricia Regina; Sawodny, Oliver; Kuchenbecker, Katherine J., 2023, "User Study Dataset for Understanding On-Site Construction Activities with Haptic Perception", https://doi.org/10.17617/3.PAFGCA, Edmond, V1
We encourage viewers to select the "Tree" view, rather than "Table" view, in order to see the files organized by their respective folders. The dataset includes the following: 1. A readme file explaining our user study and the data, 2. Raw acceleration data, 3. Raw robot data, 4.... |
Richardson, Ben; McMahon, Ian; Chu, Vivian; Martinez Perez-Tejado, Jorge; Arrigo, Michael; Kuchenbecker, Katherine J., 2023, "Penn Haptic Adjective Corpus 2", https://doi.org/10.17617/3.0C79KW, Edmond, V1
Haptic exploratory data of 60 diverse objects, systematically acquired object images, and data parsing code. The file 'phac_train_test_pos_neg_90_10_1_20.h5' contains the raw robot sensor data and binary adjective labels (25 total adjectives). Use processPHAC2.m to parse this h5... |
Jan 13, 2023
Andrussow, Iris; Sun, Huanbo; Kuchenbecker, Katherine J.; Martius, Georg, 2023, "Minsight: a fingertip-sized vision-based tactile sensor for robotic manipulation", https://doi.org/10.17617/3.AEDHD1, Edmond, V1
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Burns, Rachael Bevill; Lee, Hyosang; Seifi, Hasti; Faulkner, Robert; Kuchenbecker, Katherine J., 2022, "Sensor Patterns Dataset for Endowing a NAO Robot with Practical Social-Touch Perception", https://doi.org/10.17617/3.6x, Edmond, V2
Click the "Versions" tab to view the latest version of the database, which will have the most current sensor pattern files and information available. We encourage viewers to select the "Tree" view, rather than "Table" view, in order to see the files organized by their respective... |
Jun 3, 2022
Serhat, Gokhan; Vardar, Yasemin; Kuchenbecker, Katherine J., 2022, "Dataset – Contact evolution of dry and hydrated fingertips at initial touch", https://doi.org/10.17617/3.LF8H2Q, Edmond, V1
Pressing the fingertips into surfaces causes skin deformations that enable humans to grip objects and sense their physical properties. This process involves intricate finger geometry, non-uniform tissue properties, and moisture, complicating the underlying contact mechanics. Here... |
Mar 9, 2022
Burns, Rachael Bevill; Lee, Hyosang; Seifi, Hasti; Faulkner, Robert; Kuchenbecker, Katherine J., 2022, "User Study Dataset for Endowing a NAO Robot with Practical Social-Touch Perception", https://doi.org/10.17617/3.6w, Edmond, V1
We encourage viewers to select the "Tree" view, rather than "Table" view, in order to see the files organized by their respective folders. The User Study Methods section of the manuscript gives detailed explanations of the data collection and process. The dataset includes the fol... |
Lee, Hyosang; Sun, Huanbo; Park, Hyunkyu; Serhat, Gokhan; Javot, Bernard; Martius, Georg; Kuchenbecker, Katherine J., 2021, "Force maps and corresponding voltage measurements of an ERT tactile sensor", https://doi.org/10.17617/3.8p, Edmond, V1
This dataset contains force maps and corresponding voltage measurements obtained from the ERT tactile sensor and its multiphysics model. This dataset was used to train deep neural networks predicting a force map from voltage measurements of the ERT tactile sensor. |
