Robot Base Placement Optimization for Pick-and-Place Sequences in Industrial Environments

Alexander Wachter, Christian Hartl-Nesic, Andreas Kugi

Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in TagungsbandBegutachtung

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.
OriginalspracheEnglisch
TitelIFAC PapersOnLine
Seiten19-24
Band58
Auflage19
DOIs
PublikationsstatusVeröffentlicht - 2024
Veranstaltung18th IFAC Symposium on Information Control Problems in Manufacturing - , Österreich
Dauer: 28 Aug. 202430 Aug. 2024
https://www.incom2024.org/

Konferenz

Konferenz18th IFAC Symposium on Information Control Problems in Manufacturing
KurztitelINCOM 2024
Land/GebietÖsterreich
Zeitraum28/08/2430/08/24
Internetadresse

Research Field

  • Complex Dynamical Systems

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