Teaching robots to imitate a human with no on-teacher sensors. Whatare the key challenges?

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F18%3A00330073" target="_blank" >RIV/68407700:21730/18:00330073 - isvavai.cz</a>

Result on the web

<a href="https://arxiv.org/pdf/1901.08335.pdf" target="_blank" >https://arxiv.org/pdf/1901.08335.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Teaching robots to imitate a human with no on-teacher sensors. Whatare the key challenges?

Original language description

In this paper, we consider the problem of learning object manipulation tasks from human demonstration using RGB or RGB-D cameras. We highlight the key challenges in capturing sufficiently good data with no tracking devices – starting from sensor selection and accurate 6DoF pose estimation to natural language processing. In particular, we focus on two show cases: gluing task with a glue gun and simple block-stacking with variable blocks. Furthermore, we discuss how a linguistic description of the task could help to improve the accuracy of task description. We also present the whole architecture of our transfer of the imitated task to the simulated and real robot environment.

Czech name

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Czech description

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Type

O - Miscellaneous

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2018

Confidentiality

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