Autonomous Robotic Exploration with Simultaneous Environment and Traversability Models Learning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00362958" target="_blank" >RIV/68407700:21230/22:00362958 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.3389/frobt.2022.910113" target="_blank" >https://doi.org/10.3389/frobt.2022.910113</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3389/frobt.2022.910113" target="_blank" >10.3389/frobt.2022.910113</a>

Result language

angličtina

Original language name

Autonomous Robotic Exploration with Simultaneous Environment and Traversability Models Learning

Original language description

In this study, we address generalized autonomous mobile robot exploration of unknown environments where a robotic agent learns a traversability model and builds a spatial model of the environment. The agent can benefit from the model learned online in distinguishing what terrains are easy to traverse and which should be avoided. The proposed solution enables the learning of multiple traversability models, each associated with a particular locomotion gait, a walking pattern of a multi-legged walking robot. We propose to address the simultaneous learning of the environment and traversability models by a decoupled approach. Thus, navigation waypoints are generated using the current spatial and traversability models to gain the information necessary to improve the particular model during the robot's motion in the environment. From the set of possible waypoints, the decision on where to navigate next is made based on the solution of the generalized traveling salesman problem that allows taking into account a planning horizon longer than a single myopic decision. The proposed approach has been verified in simulated scenarios and experimental deployments with a real hexapod walking robot with two locomotion gaits, suitable for different terrains. Based on the achieved results, the proposed method exploits the online learned traversability models and further supports the selection of the most appropriate locomotion gait for the particular terrain types.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

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

2022

Confidentiality

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

Name of the periodical

Frontiers in Robotics and AI

ISSN

2296-9144

e-ISSN

2296-9144

Volume of the periodical

9

Issue of the periodical within the volume

October

Country of publishing house

CH - SWITZERLAND

Number of pages

24

Pages from-to

1-24

UT code for WoS article

000875592200001

EID of the result in the Scopus database

2-s2.0-85140472521