Human Intention Recognition for Human Aware Planning in Integrated Warehouse Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F20%3A00346441" target="_blank" >RIV/68407700:21730/20:00346441 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/MED48518.2020.9183266" target="_blank" >https://doi.org/10.1109/MED48518.2020.9183266</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/MED48518.2020.9183266" target="_blank" >10.1109/MED48518.2020.9183266</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Human Intention Recognition for Human Aware Planning in Integrated Warehouse Systems

Popis výsledku v původním jazyce

With the substantial growth of logistics businesses the need for larger and more automated warehouses increases, thus giving rise to fully robotized shop-floors with mobile robots in charge of transporting and distributing goods. However, even in fully automatized warehouse systems the need for human intervention frequently arises, whether because of maintenance or because of fulfilling specific orders, thus bringing mobile robots and humans ever closer in an integrated warehouse environment. In order to ensure smooth and efficient operation of such a warehouse, paths of both robots and humans need to be carefully planned; however, due to the possibility of humans deviating from the assigned path, this becomes an even more challenging task. Given that, the supervising system should be able to recognize human intentions and its alternative paths in real-time. In this paper, we propose a framework for human deviation detection and intention recognition which outputs the most probable paths of the humans workers and the planner that acts accordingly by replanning for robots to move out of the human's path. Experimental results demonstrate that the proposed framework increases total number of deliveries, especially human deliveries, and reduces human-robot encounters.

Název v anglickém jazyce

Human Intention Recognition for Human Aware Planning in Integrated Warehouse Systems

Popis výsledku anglicky

With the substantial growth of logistics businesses the need for larger and more automated warehouses increases, thus giving rise to fully robotized shop-floors with mobile robots in charge of transporting and distributing goods. However, even in fully automatized warehouse systems the need for human intervention frequently arises, whether because of maintenance or because of fulfilling specific orders, thus bringing mobile robots and humans ever closer in an integrated warehouse environment. In order to ensure smooth and efficient operation of such a warehouse, paths of both robots and humans need to be carefully planned; however, due to the possibility of humans deviating from the assigned path, this becomes an even more challenging task. Given that, the supervising system should be able to recognize human intentions and its alternative paths in real-time. In this paper, we propose a framework for human deviation detection and intention recognition which outputs the most probable paths of the humans workers and the planner that acts accordingly by replanning for robots to move out of the human's path. Experimental results demonstrate that the proposed framework increases total number of deliveries, especially human deliveries, and reduces human-robot encounters.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20204 - Robotics and automatic control

Projekt

—

Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2020

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of 2020 28th Mediterranean Conference on Control and Automation

ISBN

978-1-7281-5742-9

ISSN

2325-369X

e-ISSN

2473-3504

Počet stran výsledku

6

Strana od-do

586-591

Název nakladatele

IEEE Xplore

Místo vydání

—

Místo konání akce

Saint-Raphael, France

Datum konání akce

16. 9. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000612207700096