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Robot action execution model learning data

  • Short summary This dataset accompanies our paper A. Mitrevski, P. G. Plöger, and G. Lakemeyer, "Representation and Experience-Based Learning of Explainable Models for Robot Action Execution," in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020. Contents There are three zip archives included, each of them a dump of a MongoDB database corresponding to one of the three experiments in the paper: Grasping a drawer handle (handle_drawer_logs.zip) Grasping a fridge handle (handle_fridge_logs.zip) Pulling an object (pull_logs.zip) All three experiments were performed with a Toyota HSR. Only the data necessary for learning the models used in our experiments are included here. Usage After unzipping the archives, each database can be restored with the command mongorestore [directory_name] This will create a MongoDB database with the name of the directory (handle_drawer_logs, handle_fridge_logs, and pull_logs). Code for processing the data and model learning can be found in our <a href="https://github.com/alex-mitrevski/explainable-robot-execution-models">GitHub repository.

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Document Type:Research Data
Author:Alex Mitrevski
Date of first publication:2020/07/31
Departments, institutes and facilities:Fachbereich Informatik
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2022/07/22