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5. Bipedal locomotion using variable stiffness actuation

Author

Visser, Ludo C., Stramigioli, Stefano, and Carloni, Raffaella

Subjects
Computer Science - Robotics
Abstract

Robust and energy-efficient bipedal locomotion in robotics is still a challenging topic. In order to address issues in this field, we can take inspiration from nature, by studying human locomotion. The Spring-Loaded Inverted Pendulum (SLIP) model has shown to be a good model for this purpose. However, the human musculoskeletal system enables us to actively modulate leg stiffness, for example when walking in rough terrain with irregular and unexpected height variations of the walking surface. This ability of varying leg stiffness is not considered in conventional SLIP-based models, and therefore this paper explores the potential role of active leg stiffness variation in bipedal locomotion. It is shown that the conceptual SLIP model can be iteratively extended to more closely resemble a realistic (i.e., non-ideal) walker, and that feedback control strategies can be designed that reproduce the SLIP behavior in these extended models. We show that these extended models realize a cost of transport comparable to human walking, which indicates that active leg stiffness variation plays an important role in human locomotion that was previously not captured by the SLIP model. The results of this study show that active leg stiffness adaptation is a promising approach for realizing more energy-efficient and robust bipedal walking robots.

Published
2017

14. A Hybrid Control Strategy for Robust Contact Detection and Force Regulation* *Research partially supported by the Army Research Office under Grant no. DAAD 19-03-1-0144, the National Science Foundation under Grant no. CCR-0311084 and Grant no. ECS-0622253, and by the Air Force Office of Scientific Research under Grant no. F9550-06-1-0134.

Author

Carloni, Raffaella, Sanfelice, Ricardo G, Teel, Andrew R, and Melchiorri, Claudio

Subjects
Bioengineering
Abstract

We present an innovative hybrid control strategy for contact detection and force regulation of robotic manipulators. This hybrid architecture controls the robotic manipulator during the following stages of interaction with the work environment: the free motion, the transition phase, and the constrained motion. The proposed control strategy is to switch between a position and a force controller with hysteresis relying only on contact force measurements. We implement this strategy in a hybrid controller and provide a design procedure which depends on the viscoelastic parameters of the work environment. Our controller guarantees contact detection and force regulation without bounce-off effects between the robotic manipulator and the work environment from compact sets of initial conditions. Additionally, the resulting closed-loop system is robust to measurement noise. We include simulations that show how the proposed hybrid control strategy guarantees good performance in the cases of stiff and compliant work environments, and in the presence of measurement noise. © 2007 IEEE.

Published
2007

15. Guest Editorial Focused Section on the Third Edition of TMECH/AIM Emerging Topics

Author

Chen, Xiang, Tsuji, Toshiaki, Carloni, Raffaella, Chen, Xinkai, Chen, Zheng, Choi, Jongeun, Clayton, Garrett, Clévy, Cédric, Grebenstein, Markus, Grossard, Mathieu, Ito, Kazuaki, Jeon, Soo, Lan, Chao Chieh, Liu, Guangjun, Liu, Huaping, Liu, Hugh H., Manzie, Chris, Oldham, Kenn, Pan, Ya Jun, Shyrokau, Barys, Shi, Dawei, Shimono, Tomoyuki, Tavakoli, Mahdi, Wan, Yan, Wollherr, Dirk, Yao, Jianyong, Yi, Jingang, Yu, Haoyong, Zhu, G., and Artificial Intelligence

Subjects
Control and Systems Engineering, Electrical and Electronic Engineering, Computer Science Applications
Published
2022

16. Self-Sensing Soft Skin Based on Piezoelectric Nanofibers

Author

Selleri, Giacomo, primary, Mongioì, Francesco, additional, Maccaferri, Emanuele, additional, D’Anniballe, Riccardo, additional, Mazzocchetti, Laura, additional, Carloni, Raffaella, additional, Fabiani, Davide, additional, Zucchelli, Andrea, additional, and Brugo, Tommaso Maria, additional

Published
2023
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21. The Functionality Verification through Pilot Human Subject Testing of MyFlex-delta: An ESR Foot Prosthesis with Spherical Ankle Joint

Author

Tabucol, Johnnidel, Kooiman, Vera G.M., Leopaldi, Marco, Brugo, Tommaso Maria, Leijendekkers, R.A., Tagliabue, Gregorio, Verdonschot, N.J.J., Carloni, Raffaella, Zucchelli, Andrea, Tabucol, Johnnidel, Kooiman, Vera G.M., Leopaldi, Marco, Brugo, Tommaso Maria, Leijendekkers, R.A., Tagliabue, Gregorio, Verdonschot, N.J.J., Carloni, Raffaella, and Zucchelli, Andrea

Abstract

Contains fulltext : 250279.pdf (Publisher’s version ) (Open Access)

Published
2022

22. The Functionality Verification through Pilot Human Subject Testing of MyFlex-δ: An ESR Foot Prosthesis with Spherical Ankle Joint

Author

Tabucol, Johnnidel, primary, Kooiman, Vera Geertruida Maria, additional, Leopaldi, Marco, additional, Brugo, Tommaso Maria, additional, Leijendekkers, Ruud Adrianus, additional, Tagliabue, Gregorio, additional, Raveendranathan, Vishal, additional, Sotgiu, Eleonora, additional, Benincasa, Pietro, additional, Oddsson, Magnus, additional, Verdonschot, Nico, additional, Carloni, Raffaella, additional, and Zucchelli, Andrea, additional

Published
2022
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34. Quadratic Tracking Control of Photopolymerization for Additive Manufacturing

Author

Classens, K.H.J., Hafkamp, Thomas M., Westbeek, Steyn, Remmers, Joris J.C., Weiland, Siep, Carloni, Raffaella, Jayawardhana, Bayu, Lefeber, Erjen, Control Systems Technology, Group Van Dommelen, Group Remmers, Mechanics of Materials, Group Geers, Control of high-precision mechatronic systems, Control Systems, Spatial-Temporal Systems for Control, EAISI High Tech Systems, EAISI Foundational, and Cyber-Physical Systems Center Eindhoven

Published
2020

35. Comparison of Deep Learning Methods for System Identification

Author

Beintema, G.I., Tóth, Roland, Schoukens, Maarten, Carloni, Raffaella, Jayawardhana, Bayu, Lefeber, Erjen, Control Systems, Machine Learning for Modelling and Control, Autonomous Motion Control Lab, Control of high-precision mechatronic systems, Cyber-Physical Systems Center Eindhoven, Dynamic Networks: Data-Driven Modeling and Control, and EAISI High Tech Systems

Published
2020

37. LPV Modeling Using the Koopman Operator

Author

Iacob, L.C., Tóth, Roland, Schoukens, Maarten, Carloni, Raffaella, Jayawardhana, Bayu, Lefeber, Erjen, Control Systems, Machine Learning for Modelling and Control, Autonomous Motion Control Lab, Control of high-precision mechatronic systems, Cyber-Physical Systems Center Eindhoven, Dynamic Networks: Data-Driven Modeling and Control, and EAISI High Tech Systems

Subjects
Computer Science::Systems and Control
Abstract

Linear parameter-varying (LPV) models have been introduced to describe nonlinear (NL) and time-varying (TV) systems and make use of powerful results of linear control theory. LPV systems extend the notion of linear time invariant (LTI) systems, with the difference that the input/output relations change depending on a scheduling parameter. The goal is to efficiently convert a nonlinear model to an LPV representation with minimal complexity and conservativeness and preserving the system properties. A novel approach for modeling nonlinear systems in terms of a quasi-linear representation is based on the Koopman operator theory. Typically, an infinite-dimensional operator is obtained that requires an approximation for practical applications. Based on the resulting model, an LPV description can be obtained using a velocity-based linearization, which is valid at every operating point.

Published
2020

38. Optimal control and approximations

Author

Zwart, H. J., Morris, Kirsten, Iftime, Orest, Carloni, Raffaella, Jayawardhana, Bayu, Lefeber, Erjen, and SOM EEF

Published
2020

43. Model Order Selection for Robust-Control-Relevant Identification

Author

Tacx, P.J.M.M., de Rozario, Robin, Oomen, Tom A.E., Carloni, Raffaella, Jayawardhana, Bayu, Lefeber, Erjen, Control Systems Technology, Mechanical Engineering, and EAISI High Tech Systems

Subjects
Identification for Control, Order Selection
Abstract

Next-generation motion systems are envisioned to be lightweight due to increasing demands regarding throughput and precision. Typically, lightweight motion systems exhibit flexible dynamic behavior within the control bandwidth. In general, flexible dynamic behavior is not aligned with the degrees of freedom. As a result, next-generation motion systems are envisioned to be inherently multivariable. Hence, designing controllers through loop-shapingbased techniques becomes practically infeasible.

Published
2020

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