On Predicting Terrain Changes Induced by Mobile Robot Traversal

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F24%3A00382150" target="_blank" >RIV/68407700:21230/24:00382150 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/IROS58592.2024.10802070" target="_blank" >https://doi.org/10.1109/IROS58592.2024.10802070</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/IROS58592.2024.10802070" target="_blank" >10.1109/IROS58592.2024.10802070</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On Predicting Terrain Changes Induced by Mobile Robot Traversal

Popis výsledku v původním jazyce

Mobile robots operating in convoys have a limited view of the terrain to be traversed if it is occluded by the preceding vehicle. Furthermore, the preceding vehicle might change the terrain geometry and eventually significantly alter its traversability by driving over the terrain. When the following vehicles do not consider such changes, they can use spurious terrain appearance and geometry to decide whether to follow in the tracks of the previous vehicle or to avoid them since the preceding vehicle's tracks can make the terrain untraversable. We propose to predict the terrain changes induced by the robot traversal on the traversed terrain and thus support the decision-making of the following vehicles. The developed model projects the robot wheel footprint along the planned robot path and combines the projection with the terrain appearance and prior terrain elevation. The coupled model is used in a convolutional neural network that predicts the elevation after traversal. The footprint projection component is designed so that learned networks can be transferred to vehicles with different wheel footprints without relearning the model. The proposed model is verified using a dataset captured using a real, one-ton, six-wheel robot traversing rigid roads and vegetated fields.

Název v anglickém jazyce

On Predicting Terrain Changes Induced by Mobile Robot Traversal

Popis výsledku anglicky

Mobile robots operating in convoys have a limited view of the terrain to be traversed if it is occluded by the preceding vehicle. Furthermore, the preceding vehicle might change the terrain geometry and eventually significantly alter its traversability by driving over the terrain. When the following vehicles do not consider such changes, they can use spurious terrain appearance and geometry to decide whether to follow in the tracks of the previous vehicle or to avoid them since the preceding vehicle's tracks can make the terrain untraversable. We propose to predict the terrain changes induced by the robot traversal on the traversed terrain and thus support the decision-making of the following vehicles. The developed model projects the robot wheel footprint along the planned robot path and combines the projection with the terrain appearance and prior terrain elevation. The coupled model is used in a convolutional neural network that predicts the elevation after traversal. The footprint projection component is designed so that learned networks can be transferred to vehicles with different wheel footprints without relearning the model. The proposed model is verified using a dataset captured using a real, one-ton, six-wheel robot traversing rigid roads and vegetated fields.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

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

Projekt

<a href="/cs/project/EH22_008%2F0004590" target="_blank" >EH22_008/0004590: Robotika a pokročilá průmyslová výroba</a><br>

Návaznosti

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

Rok uplatnění

2024

Kód důvěrnosti údajů

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

Název statě ve sborníku

2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2024)

ISBN

979-8-3503-7770-5

ISSN

2153-0858

e-ISSN

2153-0866

Počet stran výsledku

6

Strana od-do

11694-11699

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Abu Dhabi

Datum konání akce

14. 10. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001433985300538