Distributed Planning For Self Organizing Production Systems


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Distributed Planning for Self-Organizing Production Systems


Distributed Planning for Self-Organizing Production Systems

Author: Pfrommer, Julius

language: en

Publisher: KIT Scientific Publishing

Release Date: 2024-06-04


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In dieser Arbeit wird ein Ansatz entwickelt, um eine automatische Anpassung des Verhaltens von Produktionsanlagen an wechselnde Aufträge und Rahmenbedingungen zu erreichen. Dabei kommt das Prinzip der Selbstorganisation durch verteilte Planung zum Einsatz. - Most production processes are rigid not only by way of the physical layout of machines and their integration, but also by the custom programming of the control logic for the integration of components to a production systems. Changes are time- and resource-expensive. This makes the production of small lot sizes of customized products economically challenging. This work develops solutions for the automated adaptation of production systems based on self-organisation and distributed planning.

Distributed Planning for Self-organizing Production Systems


Distributed Planning for Self-organizing Production Systems

Author: Julius Pfrommer

language: en

Publisher:

Release Date: 2021*


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Bio-Inspired Self-Organizing Robotic Systems


Bio-Inspired Self-Organizing Robotic Systems

Author: Yan Meng

language: en

Publisher: Springer Science & Business Media

Release Date: 2011-05-08


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Self-organizing approaches inspired from biological systems, such as social insects, genetic, molecular and cellular systems under morphogenesis, and human mental development, has enjoyed great success in advanced robotic systems that need to work in dynamic and changing environments. Compared with classical control methods for robotic systems, the major advantages of bio-inspired self-organizing robotic systems include robustness, self-repair and self-healing in the presence of system failures and/or malfunctions, high adaptability to environmental changes, and autonomous self-organization and self-reconfiguration without a centralized control. “Bio-inspired Self-organizing Robotic Systems” provides a valuable reference for scientists, practitioners and research students working on developing control algorithms for self-organizing engineered collective systems, such as swarm robotic systems, self-reconfigurable modular robots, smart material based robotic devices, unmanned aerial vehicles, and satellite constellations.