Pregled bibliografske jedinice broj: 1057782
Human Intention Recognition for Human Aware Planning in Integrated Warehouse Systems
Human Intention Recognition for Human Aware Planning in Integrated Warehouse Systems // 28th Mediterranean Conference on Control and Automation (MED 2020)
Saint-Raphaël, Francuska, 2020. str. 1-6 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1057782 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Human Intention Recognition for Human Aware Planning in Integrated Warehouse Systems
Autori
Petković, Tomislav ; Hvezda, Jakub ; Rybecky, Tomas ; Marković, Ivan ; Kulich, Miroslav ; Preucil, Libor ; Petrović, Ivan
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
28th Mediterranean Conference on Control and Automation (MED 2020)
/ - , 2020, 1-6
Skup
28th Mediterranean Conference on Control and Automation (MED 2020)
Mjesto i datum
Saint-Raphaël, Francuska, 15.09.2020. - 18.09.2020
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Human Intention Recognition ; Human Aware Planning
Sažetak
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.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo, Temeljne tehničke znanosti
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb