The Effects of Selected Object Features on a Pick-and-Place Task: a Human Multimodal Dataset
July 18, 2024 Β· Entered Twilight Β· π Int. J. Robotics Res.
"No code URL or promise found in abstract"
"Code repo scraped from project page (backfill)"
Evidence collected by the PWNC Scanner
Repo contents: README.md, animatedPlot.m, createVideo.m, loadInertial.m, loadMocap.m, loadTimestampsCameras.m, trialSequence.xlsx, visualizeHandTrajectory.m
Authors
Linda Lastrico, Valerio Belcamino, Alessandro Carfì, Alessia Vignolo, Alessandra Sciutti, Fulvio Mastrogiovanni, Francesco Rea
arXiv ID
2407.13425
Category
cs.RO: Robotics
Citations
5
Venue
Int. J. Robotics Res.
Repository
https://github.com/lindalastrico/objectsManipulationDataset
β 3
Last Checked
2 months ago
Abstract
We propose a dataset to study the influence of object-specific characteristics on human pick-and-place movements and compare the quality of the motion kinematics extracted by various sensors. This dataset is also suitable for promoting a broader discussion on general learning problems in the hand-object interaction domain, such as intention recognition or motion generation with applications in the Robotics field. The dataset consists of the recordings of 15 subjects performing 80 repetitions of a pick-and-place action under various experimental conditions, for a total of 1200 pick-and-places. The data has been collected thanks to a multimodal setup composed of multiple cameras, observing the actions from different perspectives, a motion capture system, and a wrist-worn inertial measurement unit. All the objects manipulated in the experiments are identical in shape, size, and appearance but differ in weight and liquid filling, which influences the carefulness required for their handling.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Robotics
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles
π
π
The Cartographer
A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles
π
π
The Cartographer
Unmanned Aerial Vehicles: A Survey on Civil Applications and Key Research Challenges
π
π
The Cartographer
A Survey of Autonomous Driving: Common Practices and Emerging Technologies
R.I.P.
π»
Ghosted