TY - GEN
T1 - An Approach to Global and Behavioral Planning for Automated Forklifts in Structured Environments
AU - Matute, Jose A.
AU - Diaz, Sergio
AU - Zubizarreta, Asier
AU - Karimoddini, Ali
AU - Perez, Joshue
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Nowadays, automation solutions for material handling in confined areas are flourishing due to the repetitive nature of the tasks, helping to improve efficiency, lower costs, and smooth operations. Although current automated forklift technologies are available, most solutions focus on path planning and tracking at the local level, leaving the higher levels of planning to a secondary role. In this work, a novel approach for global and behavioral planning for automated forklifts is presented. First, the global planner explores a graph to find and refine a path to the desired destination. Second, the behavioral planner uses a finite state machine that handles the transitions among driving maneuvers. The approach is verified in a virtual framework considering UDP communication protocols for future real implementation. Results demonstrate the applicability, using two origin-to-destination driving scenarios.
AB - Nowadays, automation solutions for material handling in confined areas are flourishing due to the repetitive nature of the tasks, helping to improve efficiency, lower costs, and smooth operations. Although current automated forklift technologies are available, most solutions focus on path planning and tracking at the local level, leaving the higher levels of planning to a secondary role. In this work, a novel approach for global and behavioral planning for automated forklifts is presented. First, the global planner explores a graph to find and refine a path to the desired destination. Second, the behavioral planner uses a finite state machine that handles the transitions among driving maneuvers. The approach is verified in a virtual framework considering UDP communication protocols for future real implementation. Results demonstrate the applicability, using two origin-to-destination driving scenarios.
UR - http://www.scopus.com/inward/record.url?scp=85141877406&partnerID=8YFLogxK
U2 - 10.1109/ITSC55140.2022.9921844
DO - 10.1109/ITSC55140.2022.9921844
M3 - Conference contribution
AN - SCOPUS:85141877406
T3 - IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
SP - 3423
EP - 3428
BT - 2022 IEEE 25th International Conference on Intelligent Transportation Systems, ITSC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 25th IEEE International Conference on Intelligent Transportation Systems, ITSC 2022
Y2 - 8 October 2022 through 12 October 2022
ER -