Transfer of Inter-Robotic Inductive Classifier

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00346395" target="_blank" >RIV/68407700:21230/20:00346395 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/ICACR51161.2020.9265509" target="_blank" >https://doi.org/10.1109/ICACR51161.2020.9265509</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICACR51161.2020.9265509" target="_blank" >10.1109/ICACR51161.2020.9265509</a>

Result language

angličtina

Original language name

Transfer of Inter-Robotic Inductive Classifier

Original language description

In multi-robot deployments, the robots need to share and integrate their own experience and perform transfer learning. Under the assumption that the robots have the same morphology and carry equivalent sensory equipment, the problem of transfer learning can be considered incremental learning. Thus, the transfer learning problem inherits the challenges of incremental learning, such as catastrophic forgetting and concept drift. In catastrophic forgetting, the model abruptly forgets the previously learned knowledge during the learning process. The concept drift arises with different experiences between consecutively sampled models. However, state-of-the-art robotic transfer learning approaches do not address both challenges at once. In this paper, we propose to use an incremental classifier on a transfer learning problem. The feasibility of the proposed approach is demonstrated in a real deployment. The robot consistently merges two classifiers learned on two different tasks into a classifier that performs well on both tasks.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

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

Project

<a href="/en/project/GA18-18858S" target="_blank" >GA18-18858S: Robotic Lifelong Learning of Multi-legged Robot Locomotion Control in Autonomous Data Collection Missions</a><br>

Continuities

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

Publication year

2020

Confidentiality

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

Article name in the collection

Proceedings of the 2020 4 th International Conference on Automation, Control and Robots

ISBN

978-1-7281-9207-9

ISSN

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e-ISSN

—

Number of pages

5

Pages from-to

32-36

Publisher name

IEEE Service Center

Place of publication

Piscataway

Event location

Rome

Event date

Nov 11, 2020

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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