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Towards Autonomous Robotic Valve Turning

In this paper an autonomous intervention robotic task to learn the skill of grasping and turning a valve is described. To resolve this challenge a set of different techniques are proposed, each one realizing a specific task and sending information to the others in a Hardware-In-Loop (HIL) simulation. To improve the estimation of the valve position, an Extended Kalman Filter is designed. Also to learn the trajectory to follow with the robotic arm, Imitation Learning approach is used. In addition, to perform safely the task a fuzzy system is developed which generates appropriate decisions. Although the achievement of this task will be used in an Autonomous Underwater Vehicle, for the first step this idea has been tested in a laboratory environment with an available robot and a sensor

This research was sponsored by PANDORA EU FP7-Project under Grant agreement No ICT-288273

Bulgarian Academy of Sciences

Autor: Carrera Viñas, Arnau
Ahmadzadeh, S.R.
Ajoudani, A.
Kormushev, Petar
Carreras Pérez, Marc
Caldwell, D.G.
Data: 15 febrer 2020
Resum: In this paper an autonomous intervention robotic task to learn the skill of grasping and turning a valve is described. To resolve this challenge a set of different techniques are proposed, each one realizing a specific task and sending information to the others in a Hardware-In-Loop (HIL) simulation. To improve the estimation of the valve position, an Extended Kalman Filter is designed. Also to learn the trajectory to follow with the robotic arm, Imitation Learning approach is used. In addition, to perform safely the task a fuzzy system is developed which generates appropriate decisions. Although the achievement of this task will be used in an Autonomous Underwater Vehicle, for the first step this idea has been tested in a laboratory environment with an available robot and a sensor
This research was sponsored by PANDORA EU FP7-Project under Grant agreement No ICT-288273
Accés al document: http://hdl.handle.net/2072/372399
Llenguatge: eng
Editor: Bulgarian Academy of Sciences
Drets: Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
URI Drets: http://creativecommons.org/licenses/by-nc-nd/3.0/es/deed.ca
Matèria: Vehicles submergibles
Submersibles
Robots autònoms
Autonomous robots
Aprenentatge automàtic
Machine learning
Intel·ligència artificial
Artificial intelligence
Títol: Towards Autonomous Robotic Valve Turning
Tipus: info:eu-repo/semantics/article
Repositori: Recercat

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