Stuttgarter Beiträge zur Produktionsforschung, Band 106
Julian Ricardo Diaz Posada
Hrsg.: Fraunhofer IPA, Stuttgart
2020, 218 S., num., mostly col. illus. and tab., Softcover
Sprache: Englisch
Stuttgart, Univ., Diss., 2019
Fraunhofer Verlag
ISBN 978-3-8396-1614-7
Inhalt
Robotic programming is still a challenge in manufacturing. Reasons for this challenge are the time-consuming, complex, primarily manually optimized, and expert-dependent path generation. Therefore, easy and optimized programmable robotic manufacturing systems are required.
To make up for this deficiency, this dissertation raises the following research question: How to automatically generate offline optimized paths for robotic manufacturing processes (RMPs) under constraints and process optimization criteria? This research question is answered with the following evaluated thesis: Robotic paths can be automatically optimized by methodologically configuring and deploying sample-based generation algorithms, based on the procedural interpretation of the Product, Process, and Resource model-based components of the RMP.
The generalized approach and implemented architecture is named Automatic Optimized Offline Programming. Three different use-cases are presented for evaluating the path planning approach: (1) The optimized collision avoidance in robotic welding, (2) the optimized stiffness for robotic milling, and (3) the optimized sensing strategy for robotic deburring.
Verfügbare Formate
Fraunhofer IPA, Fertigungsprozess, Roboter, Roboterprogrammierung, Kleine und mittlere Unternehmen KMU,
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