Wearable Robotics

We investigate and develop novel soft wearable robots for natural interactions and symbiosis between humans and robots.
Traditional human-robot interaction often requires funneling rich sensory-motor information through simplified computer interfaces, such as visual displays and joysticks, that demand cognitive effort. We explore new forms of bidirectional and embodied interactions where humans and machines interact and feel with their entire bodies. We are especially interested in human symbiosis with non-anthropomorphic machines that operate at different spatial and temporal scales, such as small flying machines.



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Arm-wrist haptic sleeve for drone teleoperation

V. Ramachandran; M. Macchini; D. Floreano 

IEEE Robotics and Automation Letters. 2022. Vol. 7, num. 4, p. 12054-12061. DOI : 10.1109/LRA.2021.3122107.
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Machine-Learning Based Monitoring of Cognitive Workload in Rescue Missions with Drones

F. Dell’Agnola; P-K. Jao; A. Arza; R. Chavarriaga; J. d. R. Millan et al. 

IEEE Journal of Biomedical and Health Informatics. 2022-06-29.  p. 1-12. DOI : 10.1109/JBHI.2022.3186625.


Wearable Haptic Interfaces for Telerobotics

V. Ramachandran / D. Floreano (Dir.)  

Lausanne, EPFL, 2021. 

Personalized Body-Machine Interfaces for Advanced Human-Robot Interaction

M. Macchini / D. Floreano (Dir.)  

Lausanne, EPFL, 2021. 
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Smart Textiles that Teach: Fabric‐Based Haptic Device Improves the Rate of Motor Learning

V. Ramachandran; F. Schilling; A. R. Wu; D. Floreano 

Advanced Intelligent Systems. 2021-07-10.  p. 2100043. DOI : 10.1002/aisy.202100043.


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Personalized Telerobotics by Fast Machine Learning of Body-Machine Interfaces

M. Macchini; F. Schiano; D. Floreano 

IEEE Robotics and Automation Letters. 2019-10-31.  p. 1-1. DOI : 10.1109/LRA.2019.2950816.

Wearable Technologies for Embodied Human-Robot Interaction

C. Rognon / D. Floreano (Dir.)  

Lausanne, EPFL, 2019. 
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Soft haptic device to render the sensation of flying like a drone

C. Rognon; M. Koehler; C. Duriez; D. Floreano; A. M. Okamura 

IEEE Robotics and Automation Letters. 2019-07-01. Vol. 4, num. 3, p. 2524-2531. DOI : 10.1109/LRA.2019.2907432.


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Haptic Guidance with a Soft Exoskeleton Reduces Error in Drone Teleoperation

C. Rognon; A. R. Wu; S. Mintchev; A. Ijspeert; D. Floreano 

2018-01-01. 11th International Conference on Haptics – Science, Technology, and Applications (EuroHaptics), Pisa, ITALY, Jun 13-16, 2018. p. 404-415. DOI : 10.1007/978-3-319-93399-3_35.
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Variable stiffness strip with strain sensing for wearable robotics

A. Tonazzini; J. Shintake; C. Rognon; V. Ramachandran; S. Mintchev et al. 

2018-07-09. 2018 IEEE International Conference on Soft Robotics (RoboSoft), Livorno, April 24-28, 2018. p. 485-490. DOI : 10.1109/ROBOSOFT.2018.8405373.
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All‐Fabric Wearable Electroadhesive Clutch

V. Ramachandran; J. Shintake; D. Floreano 

Advanced Materials Technologies. 2018-10-23. Vol. 4, num. 2, p. 1800313. DOI : 10.1002/admt.201800313.
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Data-driven body–machine interface for the accurate control of drones

J. C. Miehlbradt; A. T. Cherpillod; S. Mintchev; M. Coscia; F. Artoni et al. 

Proceedings of the National Academy of Sciences. 2018.  p. 201718648. DOI : 10.1073/pnas.1718648115.
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Haptic Guidance with a Soft Exoskeleton Reduces Error in Drone Teleoperation

C. Rognon; A. Wu; S. Mintchev; A. Ijspeert; D. Floreano 

2018. Eurohaptics 2018, Pisa, Italy, June 13-16 2018. p. 404–415. DOI : 10.1007/978-3-319-93399-3_35.
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FlyJacket: An Upper Body Soft Exoskeleton for Immersive Drone Control

C. Rognon; S. Mintchev; F. I. T. Dell’Agnola; A. T. Cherpillod; D. Atienza Alonso et al. 

IEEE Robotics and Automation Letters. 2018. Vol. 3, num. 3, p. 2362-2369. DOI : 10.1109/LRA.2018.2810955.
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Ultra-stretchable strain sensors using carbon black-filled elastomer composites and comparison of capacitive versus resistive sensors

J. Shintake; Y. Piskarev; S. Jeong; D. Floreano 

Advanced Materials Technologies. 2018. Vol. 3, p. 1700284. DOI : 10.1002/admt.201700284.


Variable Stiffness Fiber with Self-Healing Capability

A. Tonazzini; S. Mintchev; B. Schubert; B. Mazzolai; J. Shintake et al. 

Advanced Materials. 2016. Vol. 28, num. 46, p. 10105. DOI : 10.1002/adma.201602580.


Quantifying information transfer through a head attached vibrotactile display: principles for design and control

M. Dobrzynski; S. Mejri; S. Wischmann; D. Floreano 

IEEE Transactions on Biomedical Engineering. 2012. Vol. 59, num. 7, p. 2011-2018. DOI : 10.1109/TBME.2012.2196433.


SleepPic. Hardware Developments for a Wearable On-line Sleep and Wake Discrimination System

W. Karlen; D. Floreano 

2011. BIOSIGNALS 2011 – International Conference on Bio-inspired Systems and Signal Processing, Rome, Italy, January 26-29, 2011. p. 132-137.


Adaptive Sleep-Wake Discrimination for Wearable Devices

W. Karlen; D. Floreano 

IEEE Transactions on Biomedical Engineering. 2010. Vol. 58, num. 4, p. 920-926. DOI : 10.1109/TBME.2010.2097261.

Enhancing Pilot Performance with a SymBodic System

W. Karlen; S. Cardin; D. Thalmann; D. Floreano 

2010. 32nd Annual International IEEE EMBS Conference, Buenos Aires, Argentina, August 31 – September 4, 2010. p. 6599-602. DOI : 10.1109/IEMBS.2010.5627127.


Adaptive wake and sleep detection for wearable systems

W. Karlen / D. Floreano (Dir.)  

Lausanne, EPFL, 2009. 

Evolutionary Selection of Features for Neural Sleep/Wake Discrimination

P. Dürr; W. Karlen; J. Guignard; C. Mattiussi; D. Floreano 

Journal of Artificial Evolution and Applications. 2009. Vol. 2009, p. 1-10. DOI : 10.1155/2009/179680.

Sleep and Wake Classification With ECG and Respiratory Effort Signals

W. Karlen; C. Mattiussi; D. Floreano 

IEEE Transactions on Biomedical Circuits and Systems. 2009. Vol. 3, p. 71-78. DOI : 10.1109/TBCAS.2008.2008817.


An automatic parameter extraction method for the 7x50m Stroke Efficiency Test

M. Baechlin; K. Foerster; J. Schumm; D. Breu; J. Germann et al. 

2008. Third International Conference on Pervasive Computing and Applications, 2008. ICPCA 2008, Alexandria, Egypt, October 6-8, 2008. DOI : 10.1109/ICPCA.2008.4783628.

Improving Actigraph Sleep/Wake Classification with Cardio-Respiratory Signals

W. Karlen; C. Mattiussi; D. Floreano 

2008. 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vancouver, BC, 20.-25.8.2008. p. 5262-5265. DOI : 10.1109/IEMBS.2008.4650401.


Adaptive Sleep/Wake Classification Based on Cardiorespiratory Signals for Wearable Devices

W. Karlen; C. Mattiussi; D. Floreano 

2007. Biomedical Circuits and Systems Conference, BioCAS 2007, Montreal, 27.-30.11.2007. p. 203-206. DOI : 10.1109/BIOCAS.2007.4463344.