66. Optimal Trajectory and Route Planning for Free Navigation of Automated Guided Vehicles
Invited abstract in session WF-4: P-graph Applications I., stream P-graph algorithms and applications.
Wednesday, 16:45 - 18:15Room: C105
Authors (first author is the speaker)
| 1. | Marton Frits
|
| University of Pannonia | |
| 2. | Botond Bertok
|
| Széchenyi István University |
Abstract
In traditional industry setups automated guided vehicles (AGV) follows trajectories planned together with the layout of the storage or production facility and supported by fixed markers in the floor or on the walls. In contrast, developments in navigation techniques and the advanced computing, sensor, and communication capabilities of resent AGV makes their free movement safe and manageable. However, fleet management in a cooperative and adaptive working environment requires fast optimization algorithms to calculate and optimal movement. A two level optimization method is to be proposed herein providing a complete solution for integrated planning of optimal trajectories and routes of AGV’s. Trajectory planing aims at minimizing the accelerations, i.e., forces on the vehicle and its cargo while safely reaching its target location in time from its starting location. Due to response time critical computation the multidimensional space, position, speed and acceleration are modeled by their linear approximation with proper accuracy. Route planning is computed on a graph representing interconnections of rooms and corridors. Routes are synthesized as process networks where traffic rules are taken into account as logical constraint. Optimal and alternative routes are calculated by P-graph algorithms involving several logical implications accelerating the search. The overall optimization method is to be illustrated by case studies.
Keywords
- Linear and nonlinear optimization
- Mixed integer nonlinear optimization
- Multilevel optimization
Status: accepted
Back to the list of papers