Dataset Overview

Dataset Name

Effects of Object Characteristics on Manipulations

Description

The dataset investigates how specific object attributes affect human grasping and placing motions while allowing comparison of kinematics captured by different sensor modalities. It supports broader learning challenges in hand‑object interaction, including intent recognition and motion generation, with direct relevance to robotics. Data were collected from 15 participants performing 80 pick‑and‑place tasks under various experimental conditions, totaling 1,200 instances. The multimodal setup includes multiple cameras, a motion‑capture system, and wrist‑worn inertial measurement units. Objects shared shape, size, and appearance, but differed in weight and liquid fill, requiring varying levels of handling delicacy.

Detailed Description

For full details, see the dataset paper: Lastrico L, Belcamino V, Carfì A, et al. The effects of selected object features on a pick‑and‑place task: A human multimodal dataset. International Journal of Robotics Research. 2024;43(1):98‑109. doi:10.1177/02783649231210965

Software Helper Functions

Helper functions are available on GitHub.

Version

2

Keywords

• Topic: Science & Technology, Computer Science, Artificial Intelligence
• Technology: Neural Networks, LSTM
• Task: Multi‑label Classification
• Data Type: Multimodal Data
• Task: Pose Detection

License

Attribution‑NonCommercial 4.0 International (CC BY‑NC 4.0)

Identifier

2319925

Included in Data Catalogs

Kaggle

Creators

Alessandro Carfì

Distribution

• Format: zip
• Size: 77,427,764,879 bytes
• Download link: Download

Interaction Statistics

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