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Cited by 185

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Improved modelling and assessment of pneumatic muscle actuators

Tsagarakis, N., Caldwell, D.G.·2002·Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065)

Abstract

Traditional robotic/mechatronic design has successfully exploited the attributes of heavy mechanical systems engineering, but future scientific trends suggest a need for technology that will emulate natural systems. Among the most pressing of the requirements are actuation systems that can interact in a safer and more natural way. Pneumatic technology has many of the compliance forms needed for this softer interaction and a number of new systems based on McKibben muscles have been developed in recent years. In this paper a new model of operation of pneumatic muscle systems is developed. In particular, the model considers the distortion effects at the termination nodes and the radial pressure loss due to rubber elasticity. The new model is compared experimentation on a very large actuator and shows how this new model improves the assessment of forces and displacement that can be achieved by the actuator. The new model is compared against previous systems models.

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Metadata

Authors
Tsagarakis, N., & Caldwell, D. G.
Venue
Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065)
Publisher
IEEE
Published
2002-11-07
Volume
4
Pages
3641-3646
ISSN
1050-4729 (ISSN-L)
OpenAlex
W2158435142
Cited by
185
References
1
FWCI
7.61
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Improved modelling and assessment of pneumatic muscle actuators. https://app.cochat.ai/papers/10.1109/robot.2000.845299
The paper
Tsagarakis, N., & Caldwell, D. G. (2002). Improved modelling and assessment of pneumatic muscle actuators. Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065). https://doi.org/10.1109/robot.2000.845299

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.