Print Email Facebook Twitter Planning and Control of Multiple Mobile Robots for Intralogistics Title Planning and Control of Multiple Mobile Robots for Intralogistics: an optimization-based reordering strategy Author Berndt, Alexander (TU Delft Mechanical, Maritime and Materials Engineering; TU Delft Delft Center for Systems and Control) Contributor Keviczky, T. (mentor) de Albuquerque Gleizer, G. (graduation committee) Ferrari, Riccardo M.G. (graduation committee) van Duijkeren, N.J. (graduation committee) Degree granting institution Delft University of Technology Programme Mechanical Engineering | Systems and Control Date 2020-07-08 Abstract In this thesis we consider multiple Automated Guided Vehicles (AGVs) navigating a common workspace to fulfill intralogistics tasks, typically formulated as the Multi-Agent Path Finding (MAPF) problem. To keep plan execution deadlock-free, one approach is to construct an Action Dependency Graph (ADG) which encodes the ordering of AGVs as they proceed along their routes. Using this method, delayed AGVs occasionally require others to wait for them at intersections, thereby affecting the plan execution efficiency. If the workspace is shared by dynamic obstacles such as humans or third party robots, AGVs can experience large delays. A common mitigation approach is to re-solve the MAPF using the current, delayed AGV positions. However, due to its inherent complexity, solving the MAPF is time-consuming, making this approach inefficient, especially for large AGV teams. To address this challenge, we present a novel concept called a Switchable Action Dependency Graph (SADG) which is used as the basis for a shrinking and receding horizon control scheme to repeatedly modify an acyclic ADG to minimize route completion times of each AGV using an optimization based approach. Our control strategies persistently maintain an acyclic ADG, necessary for deadlock-free plan execution. The proposed control strategies are evaluated in a simulation environment and show a reduc- tion in route completion times when a fleet of AGVs is subjected to random delays. Finally, the methods are also implemented using ROS and validated in the Gazebo simulation envi- ronment to illustrate practical feasibility when applied to real systems. Subject Robust Plan ExecutionScheduling and CoordinationMixed Integer ProgrammingMulti-Agent Path FindingFactory AutomationReceding Horizon Control To reference this document use: http://resolver.tudelft.nl/uuid:d70c13ac-a992-4408-a7db-30033eec987d Part of collection Student theses Document type master thesis Rights © 2020 Alexander Berndt Files PDF BERNDT_MSc_Thesis.pdf 2.29 MB Close viewer /islandora/object/uuid:d70c13ac-a992-4408-a7db-30033eec987d/datastream/OBJ/view