Universität Stuttgart
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Item Open Access Manipulating wetting and pore filling by wall transparency(2025) Kondrat, Svyatoslav; Schimmele, Lothar; Giacomello, Alberto; Tasinkevych, Mykola; Dietrich, S.Atomically thin walls become increasingly prevalent in modern technologies. Exhibiting a unique property-transparency to interparticle interactions-such walls influence processes as diverse as capacitive energy storage, electron transfer, and wetting. However, the impact of wall transparency on wetting and capillary phenomena remains poorly understood. Herein, we employ classical density functional theory to explore how van der Waals interactions across thin solid walls affect capillarity and substrate wetting. Our findings demonstrate that a fluid-filled, sidewise-open channel beneath a thin wall can drastically enhance the lyophobicity of the wall (hydrophobicity if fluid is water), up to the point of effectively transforming lyophilic surfaces into lyophobic ones. Conversely, a fluid covering a thin wall can convert capillary condensation to drying and induce unusual capillary phases within the channel. These findings highlight the potential of wall transparency as a tool for manipulating channel filling and wetting behaviors, emphasizing its significance for interfacial phenomena and fluid adsorption in porous materials.Item Open Access Endowing a NAO robot with practical social-touch perception(2022) Burns, Rachael Bevill; Lee, Hyosang; Seifi, Hasti; Faulkner, Robert; Kuchenbecker, Katherine J.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.Item Open Access Passive advection of fractional Brownian motion by random layered flows(2020) Squarcini, Alessio; Marinari, Enzo; Oshanin, GlebWe study statistical properties of the process Y(t) of a passive advection by quenched random layered flows in situations when the inter-layer transfer is governed by a fractional Brownian motion X(t) with the Hurst index H ∈ (0,1). We show that the disorder-averaged mean-squared displacement of the passive advection grows in the large time t limit in proportion to t 2-H, which defines a family of anomalous super-diffusions. We evaluate the disorder-averaged Wigner-Ville spectrum of the advection process Y(t) and demonstrate that it has a rather unusual power-lawform1 f 3-H with a characteristic exponent which exceed the value 2. Our results also suggest that sample-to-sample fluctuations of the spectrum can be very important.Item Open Access Novel X-ray lenses for direct and coherent imaging(2019) Sanli, Umut Tunca; Schütz, Gisela (Prof. Dr.)Item Open Access Soft urinary bladder phantom for endoscopic training(2021) Choi, Eunjin; Waldbillig, Frank; Jeong, Moonkwang; Li, Dandan; Goyal, Rahul; Weber, Patricia; Miernik, Arkadiusz; Grüne, Britta; Hein, Simon; Suarez-Ibarrola, Rodrigo; Kriegmair, Maximilian Christian; Qiu, TianBladder cancer (BC) is the main disease in the urinary tract with a high recurrence rate and it is diagnosed by cystoscopy (CY). To train the CY procedures, a realistic bladder phantom with correct anatomy and physiological properties is highly required. Here, we report a soft bladder phantom (FlexBlad) that mimics many important features of a human bladder. Under filling, it shows a large volume expansion of more than 300% with a tunable compliance in the range of 12.2 ± 2.8 - 32.7 ± 5.4 mL cmH2O-1 by engineering the thickness of the bladder wall. By 3D printing and multi-step molding, detailed anatomical structures are represented on the inner bladder wall, including sub-millimeter blood vessels and reconfigurable bladder tumors. Endoscopic inspection and tumor biopsy were successfully performed. A multi-center study was carried out, where two groups of urologists with different experience levels executed consecutive CYs in the phantom and filled in questionnaires. The learning curves reveal that the FlexBlad has a positive effect in the endourological training across different skill levels. The statistical results validate the usability of the phantom as a valuable educational tool, and the dynamic feature expands its use as a versatile endoscopic training platform.Item Open Access Engineering and evaluating naturalistic vibrotactile feedback for telerobotic assembly(2024) Gong, Yijie; Kuchenbecker, Katherine J. (Hon.-Prof. Dr.)Teleoperation allows workers on a construction site to assemble pre-fabricated building components by controlling powerful machines from a safe distance. However, teleoperation's primary reliance on visual feedback limits the operator's efficiency in situations with stiff contact or poor visibility, compromising their situational awareness and thus increasing the difficulty of the task; it also makes construction machines more difficult to learn to operate. To bridge this gap, we propose that reliable, economical, and easy-to-implement naturalistic vibrotactile feedback could improve telerobotic control interfaces in construction and other application areas such as surgery. This type of feedback enables the operator to feel the natural vibrations experienced by the robot, which contain crucial information about its motions and its physical interactions with the environment. This dissertation explores how to deliver naturalistic vibrotactile feedback from a robot's end-effector to the hand of an operator performing telerobotic assembly tasks; furthermore, it seeks to understand the effects of such haptic cues. The presented research can be divided into four parts. We first describe the engineering of AiroTouch, a naturalistic vibrotactile feedback system tailored for use on construction sites but suitable for many other applications of telerobotics. Then we evaluate AiroTouch and explore the effects of the naturalistic vibrotactile feedback it delivers in three user studies conducted either in laboratory settings or on a construction site. The primary contribution of this dissertation is the clear explanation of details that are essential for the effective implementation of naturalistic vibrotactile feedback. We demonstrate that our accessible, audio-based approach can enhance user performance and experience during telerobotic assembly in construction and other application domains. These findings lay the foundation for further exploration of the potential benefits of incorporating haptic cues to enhance user experience during teleoperation.Item Open Access Frequency-frequency correlations of single-trajectory spectral densities of Gaussian processes(2022) Squarcini, Alessio; Marinari, Enzo; Oshanin, Gleb; Peliti, Luca; Rondoni, LambertoWe investigate the stochastic behavior of the single-trajectory spectral density S(ω,T) of several Gaussian stochastic processes, i.e., Brownian motion, the Ornstein-Uhlenbeck process, the Brownian gyrator model and fractional Brownian motion, as a function of the frequency ω and the observation time T. We evaluate in particular the variance and the frequency-frequency correlation of S(ω,T) for different values of ω. We show that these properties exhibit different behaviors for different physical cases and can therefore be used as a sensitive probe discriminating between different kinds of random motion. These results may prove quite useful in the analysis of experimental and numerical data.Item Open Access Ultralight soft electrostatic actuators based on solid-liquid-gas architectures(2026) Joo, Hyeong-Joon; Fukushima, Toshihiko; Li, Xiying; Shagan Shomron, Alona; Koh, Soo Jin Adrian; Rothemund, Philipp; Keplinger, ChristophSoft actuators enable versatile and adaptable robots capable of operating in unstructured environments and close to humans. Soft electrostatic actuators utilizing electrohydraulic principles are particularly promising, combining all-around actuation performance with portable driving electronics. These electrohydraulic actuators harness liquid dielectrics enclosed in solid dielectric shells to sustain high electric fields; the liquid dielectric however constitutes most of the actuator mass, limiting power-to-weight ratio. Here, we present ultralight soft electrostatic actuators based on solid-liquid-gas architectures: the introduction of gaseous dielectrics as a third phase substantially improves power-to-weight ratio by reducing actuator mass and increasing actuation speed. Through theoretical and experimental analyses, we pinpoint the fundamental performance limit as the electrical breakdown in the gas, governed by Paschen’s law, thereby providing a guideline for selection of gaseous dielectrics. Using the Peano-HASEL (hydraulically amplified self-healing electrostatic) actuator as a model system, we identify a gas mixture of C4F7N and CO2 that enables outstanding specific energy of 51.4 J kg-1 (a nine-fold improvement over conventional Peano-HASELs); using ambient air as gaseous dielectric we still achieve 33.5 J kg-1 and a power-to-weight ratio of 1600 W kg-1 (a five- and eleven-fold improvement). We illustrate these enhanced performance metrics in a jumping robot, showing a 60% increase in jump height, highlighting the wide potential of ultralight soft electrostatic actuators for adaptable and agile robotic systems.Item Open Access Engineered bioinspired natural dynamics and their synergy with control and learning in legged robots(2022) Ruppert, Felix; Schmitt, Syn (Prof. Dr.)The performance of legged locomotion relies on the successful mitigation of unstructured, rough terrain in the presence of sparse information and neurosensory delays. Bioinspired walking systems benefit from carefully engineered passive compliant behavior that models the inherent elastic behavior of muscle-tendon structures in animals. To leverage the passive behavior that provides energy efficiency, passive stability as well as simplified control and learning tasks to the system, locomotion control and learning algorithms have to be designed and coordinated with the natural system dynamics in mind to achieve similar locomotion behavior we see in animals. The major contribution of this thesis is the synergy of a bio-inspired leg design with biarticular muscle-tendon structures, a wearable force and pressure sensor design for closed-loop control in legged locomotion, a biologically inspired closed-loop central pattern generator with reflex-like feedback and a learning approach that enables the locomotion controller to leverage the carefully engineered natural dynamics of the robot to learn convincing locomotion skills and increase energy efficiency. The first contribution is a biologically inspired leg design focusing on the biarticular lower leg muscle-tendon structure in vertebrate animals. The biarticular elasticity provides two-dimensional passive impedance to the leg and allows the storage of energy orthogonal to the leg axis direction. The leg blueprint is characterized in its capability to store and release elastic energy in the biarticular structure. The stored energy can be recuperated back into the system and increases the energy efficiency of the leg. This leg design achieves the lowest relative cost of transport documented for all dynamically hopping and running robots. The second contribution introduces the concept of training wheels, temporary mechanical modifications to the system dynamics that shape the learning reward landscape and simplify learning locomotion directly in hardware. Through deliberate changes to the system dynamics, in this case, reduced gravity, the reward landscape can be shaped to simplify the learning process. Learning with this training wheel is safer due to smoother reward landscapes with shallower gradients. Also, the initial guess for initiating the machine learning algorithm is simplified, because the salient gradient set of viable reward signals is bigger. During the learning process, the training wheel influence can be gradually reduced and the learning algorithm converges to the solution of the initial learning problem without training wheels. The third contribution presents a rugged, lightweight force and pressure sensor for feedback information and biomechanical analysis. The sensor can be mounted on a robotic foot and provides continuous force and pressure feedback during locomotion in unstructured and soft terrain. The sensor is based on a pressure sensor, encapsulated in a polyurethane dome with an air cavity around the pressure sensor. External forces deform the sensor dome and the rising pressure in the air cavity is measured by the pressure sensor. Based on the dome geometry and material, the sensor range can be adjusted for different load cases. The sensor can be used in arrays to measure pressure distributions as well as a wearable force sensor in wet or granular media where classical force plates can not be utilized. The final contribution synergizes the individual contributions into a neuroinspired learning approach that matches a bioinspired closed-loop central pattern generator with reflex-like neuroelastic feedback to the natural dynamics of a quadruped robot with biarticular legs. Through sparse contact feedback from the foot sensor, the bioinspired central pattern generator can neuroelastically mitigate short-term perturbations to adapt the robot to its environment. Because the robot dynamics and the control task dynamics initially do not match, the controller uses the neuroelastic feedback to minimize the discrepancy between commanded and measured robot behavior. The amount of feedback activity during level walking can be used as a proxy to estimate the amount of dynamics mismatching. By minimizing the amount of required neuroelastic feedback the robot learns to neuroplastically match its control task dynamics to its natural dynamics through Bayesian optimization. Through the synergy of mechanics and control the biomechatronic system benefits from both the individual functionality of its components as well as their interplay during locomotion. The designed natural dynamics provide advantageous passive behavior to the robot and the bioinspired controller learns to leverage the natural dynamics to achieve convincing locomotion.Item Open Access Magnetic putty as a reconfigurable, recyclable, and accessible soft robotic material(2023) Li, Meng; Pal, Aniket; Byun, Junghwan; Gardi, Gaurav; Sitti, MetinMagnetically hard materials are widely used to build soft magnetic robots, providing large magnetic force/torque and macrodomain programmability. However, their high magnetic coercivity often presents practical challenges when attempting to reconfigure magnetization patterns, requiring a large magnetic field or heating. In this study, magnetic putty is introduced as a magnetically hard and soft material with large remanence and low coercivity. It is shown that the magnetization of magnetic putty can be easily reoriented with maximum magnitude using an external field that is only one‐tenth of its coercivity. Additionally, magnetic putty is a malleable, autonomous self‐healing material that can be recycled and repurposed. The authors anticipate magnetic putty could provide a versatile and accessible tool for various magnetic robotics applications for fast prototyping and explorations for research and educational purposes.