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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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Robot handle grasping failure data

Authors: Mitrevski, Alex;

Robot handle grasping failure data

Abstract

Short summary Accompanying dataset for our paper A. Mitrevski, P. G. Plöger, and G. Lakemeyer, "Robot Action Diagnosis and Experience Correction by Falsifying Parameterised Execution Models," in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2021. Contents The dataset includes a single zip archive, containing data from the experiment described in the paper (conducted with a Toyota HSR). The zip archive contains three subdirectories: handle_grasping_failure_database: A dump of a MongoDB database containing data from the handle grasping experiment, including ground-truth grasping failure annotations pre_arm_motion_images: Images collected from the robot's hand camera before moving the robot's hand towards the handle pregrasp_images: Images collected from the robot's hand camera just before closing the gripper for grasping The image names include the time stamp at which the images were taken; this allows matching each image with the execution data in the database. Database usage After unzipping the archive, the database can be restored with the command mongorestore handle_grasping_failure_database This will create a MongoDB database with the name drawer_handle_grasping_failures. Code for processing the data and failure analysis can be found in our GitHub repository.

Keywords

robotics, toyota hsr, robot execution failures

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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