Learning to Manipulate Tools by Aligning Simulation to Video Demonstration

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F22%3A00354057" target="_blank" >RIV/68407700:21460/22:00354057 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21730/22:00354057

Výsledek na webu

<a href="https://doi.org/10.1109/LRA.2021.3127238" target="_blank" >https://doi.org/10.1109/LRA.2021.3127238</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/LRA.2021.3127238" target="_blank" >10.1109/LRA.2021.3127238</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Learning to Manipulate Tools by Aligning Simulation to Video Demonstration

Popis výsledku v původním jazyce

A seamless integration of robots into human environments requires robots to learn how to use existing human tools. Current approaches for learning tool manipulation skills mostly rely on expert demonstrations provided in the target robot environment, for example, by manually guiding the robot manipulator or by teleoperation. In this work, we introduce an automated approach that replaces an expert demonstration with a Youtube video for learning a tool manipulation strategy. The main contributions are twofold. First, we design an alignment procedure that aligns the simulated environment with the real-world scene observed in the video. This is formulated as an optimization problem that finds a spatial alignment of the tool trajectory to maximize the sparse goal reward given by the environment. Second, we describe an imitation learning approach that focuses on the trajectory of the tool rather than the motion of the human. For this we combine reinforcement learning with an optimization procedure to find a control policy and the placement of the robot based on the tool motion in the aligned environment. We demonstrate the proposed approach on spade, scythe and hammer tools in simulation, and show the effectiveness of the trained policy for the spade on a real Franka Emika Panda robot demonstration.

Název v anglickém jazyce

Learning to Manipulate Tools by Aligning Simulation to Video Demonstration

Popis výsledku anglicky

A seamless integration of robots into human environments requires robots to learn how to use existing human tools. Current approaches for learning tool manipulation skills mostly rely on expert demonstrations provided in the target robot environment, for example, by manually guiding the robot manipulator or by teleoperation. In this work, we introduce an automated approach that replaces an expert demonstration with a Youtube video for learning a tool manipulation strategy. The main contributions are twofold. First, we design an alignment procedure that aligns the simulated environment with the real-world scene observed in the video. This is formulated as an optimization problem that finds a spatial alignment of the tool trajectory to maximize the sparse goal reward given by the environment. Second, we describe an imitation learning approach that focuses on the trajectory of the tool rather than the motion of the human. For this we combine reinforcement learning with an optimization procedure to find a control policy and the placement of the robot based on the tool motion in the aligned environment. We demonstrate the proposed approach on spade, scythe and hammer tools in simulation, and show the effectiveness of the trained policy for the spade on a real Franka Emika Panda robot demonstration.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

<a href="/cs/project/EF15_003%2F0000468" target="_blank" >EF15_003/0000468: Inteligentní strojové vnímání</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

IEEE Robotics and Automation Letters

ISSN

2377-3766

e-ISSN

2377-3766

Svazek periodika

7

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

8

Strana od-do

438-445

Kód UT WoS článku

000724477700004

EID výsledku v databázi Scopus

2-s2.0-85119417079