Modular Robot Composition Optimization for Task-Tailored Automation

MCML Authors

Jonathan Külz

* Former Member

→ Group Matthias Althoff
 Cyber Physical Systems

Abstract

Industrial manipulators are general-purpose machines, but inflexible in dynamic environments. Modular Reconfigurable Robots promise adaptable, cost-efficient automation, yet deployment is limited due to simulation gaps and combinatorial complexity. This thesis presents a modeling framework, a composable benchmark, and a genetic optimization algorithm, enabling efficient design exploration and real-world deployment, validated through automated drilling in construction.

phdthesis Kue26

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Dissertation

TU München. Apr. 2026

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Authors

J. Külz

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Links

URL

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Research Area

 B3 | Multimodal Perception