TY - JOUR
T1 - A dynamic path planning approach for dense, large, grid-based automated guided vehicle systems
AU - Fransen, K.J.C.
AU - van Eekelen, J. A.W.M.
AU - Pogromsky, A.
AU - Boon, M. A.A.
AU - Adan, I. J.B.F.
PY - 2020/11
Y1 - 2020/11
N2 - Real-time path planning for large, dense grid-based automated guided vehicle (AGV) systems, used for example to sort parcels, is challenging. Most approaches described in the literature are not fast enough for real-time control or are not able to avoid congestion. This paper presents a dynamic approach using a graph-representation of the grid system layout with vertex weights that are updated over time. By means of an extensive discrete-event simulation, we show that the proposed path planning approach significantly increases the throughput compared to existing approaches. Furthermore, it enables the recovery from deadlock situations.
AB - Real-time path planning for large, dense grid-based automated guided vehicle (AGV) systems, used for example to sort parcels, is challenging. Most approaches described in the literature are not fast enough for real-time control or are not able to avoid congestion. This paper presents a dynamic approach using a graph-representation of the grid system layout with vertex weights that are updated over time. By means of an extensive discrete-event simulation, we show that the proposed path planning approach significantly increases the throughput compared to existing approaches. Furthermore, it enables the recovery from deadlock situations.
KW - Automated guided vehicle
KW - Centralized control
KW - Deadlock recovery
KW - Discrete event simulation
KW - Dynamic path planning
KW - Real-time control
UR - http://www.scopus.com/inward/record.url?scp=85087991446&partnerID=8YFLogxK
U2 - 10.1016/j.cor.2020.105046
DO - 10.1016/j.cor.2020.105046
M3 - Article
AN - SCOPUS:85087991446
SN - 0305-0548
VL - 123
JO - Computers & Operations Research
JF - Computers & Operations Research
M1 - 105046
ER -