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Modeling, sensing, and control for agile trajectory tracking of soft robots
Citation Link: https://doi.org/10.15480/882.16343
Publikationstyp
Doctoral Thesis
Date Issued
2026
Sprache
English
Author(s)
Advisor
Referee
Title Granting Institution
Technische Universität Hamburg
Place of Title Granting Institution
Hamburg
Examination Date
2025-12-09
Institute
TORE-DOI
First published in
Number in series
13
Citation
MuM notes in mechanics and dynamics 13: (2026)
Accurate, agile trajectory tracking is important for modern soft robotic applications. This requires models that accurately represent dynamic behavior, soft sensors for state estimation, and dynamic controllers. In this work, first, different model-based and data-driven modeling approaches for soft robots are presented and evaluated in terms of accuracy and efficiency. Second, curvature sensors that can be integrated into the soft robot body to measure its configuration are presented and evaluated experimentally. Third, feedforward and feedback control approaches for soft robots are presented and evaluated in simulations and experiments.
Subjects
Soft Robotics
Data-Driven Modeling
Control
Beam Models
Soft Sensors
DDC Class
629.892: Robot
621.38: Electronics, Communications Engineering
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Grube_Malte_Dissertation.pdf
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35.14 MB
Format
Adobe PDF