Robotics

The Robotics Central Scientific Facility supports the institute's research objectives via the design, rapid prototyping, and validation of novel robotic and mechatronic systems.

We recommend that you contact us early on in the development of new projects, when we can discuss how the ZWE could be most useful and formulate a collaborative plan.

Facilities

The Robotics ZWE offices and labs are located in the 3N corridor of the MPI-IS Stuttgart campus, including:

ADDITIVE MANUFACTURING - The field of additive manufacturing (“3D Printing”) continues to evolve and grow at an astonishing rate. The fundamental principle is the layered deposition of material to fabricate given three-dimensional geometry. In an effort to support the diverse prototyping needs of the institute, the Robotics ZWE offers full-service 3D printing using a wide variety of techniques and processes, including fused-deposition modeling (FDM), stereolithography (SLA), multi-jet modeling (MJM), multi-material printing, and more.
CIRCUIT FABRICATION - Recognizing that the majority of embedded electronic systems require the integration of compact, surface-mounted components on either rigid or flexible substrates, we have assembled the equipment and expertise to rapidly design, fabricate, and test advanced circuitry.

Expertise & Capabilities

Mechatronics is the synergistic fusion of mechanical design, electrical engineering, embedded programming, and systems integration. The melding together of these complementary disciplines has made possible the vast majority of the technology that pervades our lives, from modern automobiles to smartphones and surgical robots. Such systems are, by their very nature, rather complex. With over 20 years combined experience in mechatronic design and prototyping, the engineers of the Robotics ZWE are well equipped to assist with the design and realization of a wide range of mechatronic systems

MECHANICAL COMPONENT DESIGN & PROTOTYPING
- SolidWorks 3D CAD
- FEA simulation
- additive manufacturing
- subtractive prototyping
- composite-part design and fabrication
- custom polymer casting fabrication

ELECTRICAL CIRCUIT LAYOUT & PROTOTYPING
- high-density surface mount design
- rigid and flexible printed circuit prototyping and fabrication
- multi-layer circuits

EMBEDDED SOFTWARE DEVELOPMENT
- familiarity with all major microcontroller architectures (AVR, ARM, TI, Freescale, Microchip, etc.)
- proficient in a variety of programming languages (C/C++, Java, Python, Matlab, etc.)
- extensive experience with various communication protocols (I2C, SPI, USB, CAN, etc.)

Members:

Jonathan Fiene

ZWE Robotics Leader

Robert Faulkner

	Stuttgart

Walter Gasparetto

	Stuttgart

Felix Grüninger

	Stuttgart

	0711 - 689 3324 // 07071 - 601 1859

Julian Martus

	Stuttgart

Seyhan Sitti


	+49 711 689-3581

Ruben Werbke

	Stuttgart

Alumni:

Felix Grimminger

Thomas Hartung

Brian Wright

10 results

2024

Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion

Guist, S., Schneider, J., Ma, H., Chen, L., Berenz, V., Martus, J., Ott, H., Grüninger, F., Muehlebach, M., Fiene, J., Schölkopf, B., Büchler, D.

Proceedings of Robotics: Science and Systems, July 2024 (conference)

arXiv Project Page link (url) DOI [BibTex]

2024

Guist, S., Schneider, J., Ma, H., Chen, L., Berenz, V., Martus, J., Ott, H., Grüninger, F., Muehlebach, M., Fiene, J., Schölkopf, B., Büchler, D. Safe & Accurate at Speed with Tendons: A Robot Arm for Exploring Dynamic Motion Proceedings of Robotics: Science and Systems, July 2024 (conference)

arXiv Project Page link (url) DOI [BibTex]

GaitGuide: A Wearable Device for Vibrotactile Motion Guidance

Rokhmanova, N., Martus, J., Faulkner, R., Fiene, J., Kuchenbecker, K. J.

Workshop paper (3 pages) presented at the ICRA Workshop on Advancing Wearable Devices and Applications Through Novel Design, Sensing, Actuation, and AI, Yokohama, Japan, May 2024 (misc)

Abstract

Wearable vibrotactile devices can provide salient sensations that attract the user's attention or guide them to change. The future integration of such feedback into medical or consumer devices would benefit from understanding how vibrotactile cues vary in amplitude and perceived strength across the heterogeneity of human skin. Here, we developed an adhesive vibrotactile device (the GaitGuide) that uses two individually mounted linear resonant actuators to deliver directional motion guidance. By measuring the mechanical vibrations of the actuators via small on-board accelerometers, we compared vibration amplitudes and perceived signal strength across 20 subjects at five signal voltages and four sites around the shank. Vibrations were consistently smallest in amplitude—but perceived to be strongest—at the site located over the tibia. We created a fourth-order linear dynamic model to capture differences in tissue properties across subjects and sites via optimized stiffness and damping parameters. The anterior site had significantly higher skin stiffness and damping; these values also correlate with subject-specific body-fat percentages. Surprisingly, our study shows that the perception of vibrotactile stimuli does not solely depend on the vibration magnitude delivered to the skin. These findings also help to explain the clinical practice of evaluating vibrotactile sensitivity over a bony prominence.

link (url) Project Page [BibTex]

Rokhmanova, N., Martus, J., Faulkner, R., Fiene, J., Kuchenbecker, K. J. GaitGuide: A Wearable Device for Vibrotactile Motion Guidance Workshop paper (3 pages) presented at the ICRA Workshop on Advancing Wearable Devices and Applications Through Novel Design, Sensing, Actuation, and AI, Yokohama, Japan, May 2024 (misc)

link (url) Project Page [BibTex]

2023

A Robust Open-source Tendon-driven Robot Arm for Learning Control of Dynamic Motions

Guist, S., Schneider, J., Ma, H., Berenz, V., Martus, J., Grüninger, F., Muehlebach, M., Fiene, J., Schölkopf, B., Büchler, B.

RoboLetics: Workshop on Robot Learning in Athletics @CoRL 2023, November 2023 (conference)

link (url) [BibTex]

2023

Guist, S., Schneider, J., Ma, H., Berenz, V., Martus, J., Grüninger, F., Muehlebach, M., Fiene, J., Schölkopf, B., Büchler, B. A Robust Open-source Tendon-driven Robot Arm for Learning Control of Dynamic Motions RoboLetics: Workshop on Robot Learning in Athletics @CoRL 2023, November 2023 (conference)

link (url) [BibTex]

2022

The Wheelbot: A Jumping Reaction Wheel Unicycle

Geist, A. R., Fiene, J., Tashiro, N., Jia, Z., Trimpe, S.

IEEE Robotics and Automation Letters, 7(4):9683-9690, IEEE, 2022 (article)

Abstract

Combining off-the-shelf components with 3D- printing, the Wheelbot is a symmetric reaction wheel unicycle that can jump onto its wheels from any initial position. With non-holonomic and under-actuated dynamics, as well as two coupled unstable degrees of freedom, the Wheelbot provides a challenging platform for nonlinear and data-driven control research. This letter presents the Wheelbot's mechanical and electrical design, its estimation and control algorithms, as well as experiments demonstrating both self-erection and disturbance rejection while balancing.

link (url) DOI [BibTex]

2022

Geist, A. R., Fiene, J., Tashiro, N., Jia, Z., Trimpe, S. The Wheelbot: A Jumping Reaction Wheel Unicycle IEEE Robotics and Automation Letters, 7(4):9683-9690, IEEE, 2022 (article)

link (url) DOI [BibTex]

Endowing a NAO Robot with Practical Social-Touch Perception

Burns, R. B., Lee, H., Seifi, H., Faulkner, R., Kuchenbecker, K. J.

Frontiers in Robotics and AI, 9, pages: 840335, April 2022 (article)

Abstract

Social touch is essential to everyday interactions, but current socially assistive robots have limited touch-perception capabilities. Rather than build entirely new robotic systems, we propose to augment existing rigid-bodied robots with an external touch-perception system. This practical approach can enable researchers and caregivers to continue to use robotic technology they have already purchased and learned about, but with a myriad of new social-touch interactions possible. This paper presents a low-cost, easy-to-build, soft tactile-perception system that we created for the NAO robot, as well as participants' feedback on touching this system. We installed four of our fabric-and-foam-based resistive sensors on the curved surfaces of a NAO's left arm, including its hand, lower arm, upper arm, and shoulder. Fifteen adults then performed five types of affective touch-communication gestures (hitting, poking, squeezing, stroking, and tickling) at two force intensities (gentle and energetic) on the four sensor locations; we share this dataset of four time-varying resistances, our sensor patterns, and a characterization of the sensors' physical performance. After training, a gesture-classification algorithm based on a random forest identified the correct combined touch gesture and force intensity on windows of held-out test data with an average accuracy of 74.1%, which is more than eight times better than chance. Participants rated the sensor-equipped arm as pleasant to touch and liked the robot's presence significantly more after touch interactions. Our promising results show that this type of tactile-perception system can detect necessary social-touch communication cues from users, can be tailored to a variety of robot body parts, and can provide HRI researchers with the tools needed to implement social touch in their own systems.

DOI Project Page [BibTex]

Burns, R. B., Lee, H., Seifi, H., Faulkner, R., Kuchenbecker, K. J. Endowing a NAO Robot with Practical Social-Touch Perception Frontiers in Robotics and AI, 9, pages: 840335, April 2022 (article)

DOI Project Page [BibTex]

2021

A Robot Cluster for Reproducible Research in Dexterous Manipulation

Wüthrich*, M., Widmaier*, F., Bauer*, S., Funk, N., Urain, J., Peters, J., Watson, J., Chen, C., Srinivasan, K., Zhang, J., Zhang, J., Walter, M. R., Madan, R., Schaff, C., Maeda, T., Yoneda, T., Yarats, D., Allshire, A., Gordon, E. K., Bhattacharjee, T., Srinivasa, S. S., Garg, A., Buchholz, A., Stark, S., Steinbrenner, T., Akpo, J., Joshi, S., Agrawal, V., Schölkopf, B.

2021, *equal contribution (misc)

arXiv [BibTex]

2021

arXiv [BibTex]

2020

Method for Force Inference of a Sensor Arrangement, Methods for Training Networks, Force Inference Module and Sensor Arrangement

Sun, H., Martius, G., Lee, H., Spiers, A., Fiene, J.

(PCT/EP2020/083261), Max Planck Institute for Intelligent Systems, Max Planck Ring 4, November 2020 (patent)

Abstract

The present invention relates to a method for force inference of a sensor arrangement, to related methods for training of networks, to a force inference module for performing such methods, and to a sensor arrangement for sensing forces. When developing applications such as robots, sensing of forces applied on a robot hand or another part of a robot such as a leg or a manipulation device is crucial in giving robots increased capabilities to move around and/or manipulate objects. Known implementations for sensor arrangements that can be used in robotic applications in order to have feedback with regard to applied forces are quite expensive and do not have sufficient resolution. Sensor arrangements may be used to measure forces. However, known sensor arrangements need a high density of sensors to provide for a high special resolution. It is thus an object of the present invention to provide for a method for force inference of a sensor arrangement and related methods that are different or optimized with regard to the prior art. It is a further object to provide for a force inference module to perform such methods. It is a further object to provide for a sensor arrangement for sensing forces with such a force inference module.

Project Page [BibTex]