Abstract
This work proposes a highly parallelized and efficient optimization procedure for finding the globally optimal robot base placement in industrial assembly tasks. This procedure fully embeds a point-to-point (P2P) trajectory planner to evaluate the placements, considering kinodynamic robot limits, collisions, robot configuration changes, and a cyclic constraint. The investigated optimization goals are cycle-time optimality, time-energy optimality, and adaptivity to dynamically changing throughput. The latter uses an optimization-based method to scale the cycle-time-optimal trajectory in low-throughput situations to reduce energy consumption. The approach is used to optimize the base placement in two robotic work cells, showing a reduction in the cycle time of up to 44% and a reduction of energy consumption of up to 53% in a best-to-worst comparison.
Originalsprache | Englisch |
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Titel | IFAC PapersOnLine |
Seiten | 19-24 |
Band | 58 |
Auflage | 19 |
DOIs | |
Publikationsstatus | Veröffentlicht - 2024 |
Veranstaltung | 18th IFAC Symposium on Information Control Problems in Manufacturing - , Österreich Dauer: 28 Aug. 2024 → 30 Aug. 2024 https://www.incom2024.org/ |
Konferenz
Konferenz | 18th IFAC Symposium on Information Control Problems in Manufacturing |
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Kurztitel | INCOM 2024 |
Land/Gebiet | Österreich |
Zeitraum | 28/08/24 → 30/08/24 |
Internetadresse |
Research Field
- Complex Dynamical Systems