Details

Autor(en) / Beteiligte

• Fragapane, Giuseppe
• de Koster, René
• Sgarbossa, Fabio
• Strandhagen, Jan Ola

Titel

Planning and control of autonomous mobile robots for intralogistics: Literature review and research agenda

Ist Teil von

• European journal of operational research, 2021-10, Vol.294 (2), p.405-426

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2021

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• •We define autonomous mobile robots in intralogistics.•We explain the evolution from automated guided vehicles to autonomous mobile robots.•We identify the technological advances affecting the planning and control decisions.•We provide guidance and methods to plan and control autonomous mobile robots.•We identify a research agenda for planning and control of autonomous mobile robots. Autonomous mobile robots (AMR) are currently being introduced in many intralogistics operations, like manufacturing, warehousing, cross-docks, terminals, and hospitals. Their advanced hardware and control software allow autonomous operations in dynamic environments. Compared to an automated guided vehicle (AGV) system in which a central unit takes control of scheduling, routing, and dispatching decisions for all AGVs, AMRs can communicate and negotiate independently with other resources like machines and systems and thus decentralize the decision-making process. Decentralized decision-making allows the system to react dynamically to changes in the system state and environment. These developments have influenced the traditional methods and decision-making processes for planning and control. This study identifies and classifies research related to the planning and control of AMRs in intralogistics. We provide an extended literature review that highlights how AMR technological advances affect planning and control decisions. We contribute to the literature by introducing an AMR planning and control framework to guide managers in the decision-making process, thereby supporting them to achieve optimal performance. Finally, we propose an agenda for future research within this field.