Marc Teyssier

@inproceedings{parilusyan_2251,

title = {Local Layer Splitting: An Additive Manufacturing Method to Define the Mechanical Properties of Soft Pneumatic Actuators During Fabrication},

author = {Brice Parilusyan and Marc Teyssier and Zacharie Guillaume and Thibault Charlet and Clément Duhart and Marcos Serrano},

url = {icra2023.org},

year  = {2023},

date = {2023-05-01},

booktitle = {IEEE International Conference on Robotics and Automation},

address = {London, UK},

abstract = {Additive manufacturing of silicone is increasingly being explored to complement the traditional molding fabrication technique for Soft Pneumatic Actuators (SPAs). However, the mechanical behavior of SPAs is defined by their 3D form, which leads to prioritizing the SPAs mechanical properties over their aspect. In this paper, we propose a novel SPA fabrication method where the mechanical properties of a silicone part are defined during the fabrication phase rather than the 3D modeling phase, leading to the object's mechanical properties being independent of the object's aspect. This novel SPA fabrication method, named Local Layer Splitting (LLS), consists of local modifications of the printing layer height to integrate stiffness variation, thus generating controlled mechanical deformation when pressured. We discovered that silicone printing layer height impacts the final stiffness of the material, and it could be used to program bending deformation to actuators during printing. We first characterize the effect of the layer height parameters on 3D-printed silicone stiffness with tensile tests. Then, we present a custom slicer we developed to generate G-codes with local layer height variations depending on the x and y positions. We then characterize the bending and force achievable by SPAs made with the LLS process and find that they match those of state-of-the-art SPAs. Finally, we present and discuss how the LLS method impacts the SPAs design by shifting the bending behavior integration from the SPAs 3D conception to their fabrication phase.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{dobinson_2052,

title = {MicroPress: Detecting Pressure and Hover Distance in Thumb-to-Finger Interactions},

author = {Rhett Dobinson and Marc Teyssier and Jürgen Steimle and Bruno Fruchard},

editor = {SIGGRAPH},

url = {https://dl.acm.org/doi/10.1145/3565970.3567698},

issn = {978-1-4503-9948-7},

year  = {2022},

date = {2022-12-01},

booktitle = {Spatial User Interaction},

volume = {4},

pages = {1-10},

publisher = {SIGGRAPH},

address = {online},

abstract = {Thumb-to-finger interactions leverage the thumb for precise, eyes-free input with high sensory bandwidth. While previous research explored gestures based on touch contact and finger movement on the skin, interactions leveraging depth such as pressure and hovering input are still underinvestigated. We present MicroPress, a proof-of-concept device that can detect both, precise thumb pressure applied on the skin and hover distance between the thumb and the index finger. We rely on a wearable IMU sensor array and a bi-directional RNN deep learning approach to enable fine-grained control while preserving the natural tactile feedback and touch of the skin. We demonstrate MicroPress' efficacy with two interactive scenarios that pose challenges for real-time input and we validate its design with a study involving eight participants. With short per user calibration steps, MicroPress is capable of predicting hover distance with 0.57mm accuracy, and on-skin pressure with 6.71% normalized pressure error at 6 locations on the index finger.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{koelle_2050,

title = {Prototyping Soft Devices with Interactive Bioplastics},

author = {Marion Koelle and Madalena Nicolae and Aditya Shekhar Nittala and Marc Teyssier and Jürgen Steimle},

editor = {ACM},

url = {https://dl.acm.org/doi/abs/10.1145/3526113.3545623},

issn = {978-1-4503-9320-1},

year  = {2022},

date = {2022-10-01},

booktitle = {35th Annual ACM Symposium on User Interface Software and Technology},

address = {Bend OR, USA},

abstract = {Designers and makers are increasingly interested in leveraging bio-based and bio-degradable ?do-it-yourself' (DIY) materials for sustainable prototyping. Their self-produced bioplastics possess compelling properties such as self-adhesion but have so far not been functionalized to create soft interactive devices, due to a lack of DIY techniques for the fabrication of functional electronic circuits and sensors. In this paper, we contribute a DIY approach for creating Interactive Bioplastics that is accessible to a wide audience, making use of easy-to-obtain bio-based raw materials and familiar tools. We present three types of conductive bioplastic materials and their formulation: sheets, pastes and foams. Our materials enable additive and subtractive fabrication of soft circuits and sensors. Furthermore, we demonstrate how these materials can substitute conventional prototyping materials, be combined with off-the-shelf materials.},

note = {Best Paper and Best Demo},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{teyssier_1813,

title = {Human-Like Artificial Skin Sensor for Physical Human-Robot Interaction},

author = {Marc Teyssier and Brice Parilusyan and Anne Roudaut and Jürgen Steimle},

editor = {IEEE},

url = {https://ieeexplore.ieee.org/document/9561152},

issn = {9781728190785},

year  = {2021},

date = {2021-04-01},

booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},

pages = {3626-3633},

publisher = {Institute of Electrical and Electronics Engineers (IEEE)},

address = {Xi'an, China},

edition = {2021},

abstract = {Physical Human-Robot-Interaction (pHRI) is beneficial for communication in social interaction or to perform collaborative tasks but is also crucial for safety. While robotic devices embed sensors for this sole purpose, their design often is the results of a trade-off between technical capabilities and rarely considers human factors. We propose a novel approach to design and fabricate compliant Human-like artificial skin sensors for robots, with similar mechanical properties as human skin and capable of precisely detecting touch. Our artificial skin relies on the use of different silicone elastomers to replicate the human skin layers and comprises an embedded electrode matrix to perform mutual capacitance sensing. We present the sensor and describe its fabrication process which is scalable, low-cost and ensures flexibility, compliance and robustness. We introduce Muca, an open-source sensing development board and then evaluate the performance of the sensor.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}