The sensation of tactile slip is ubiquitous to dexterous in-hand manipulation and plays a central role in grip control and surface perception. Replicating these sensations artificially is a valuable tool for increasing embodiment and immersion in robotic teleoperation and virtual reality applications. Existing slip-rendering devices span a wide range of designs, including vibrotactile, belt-, platform-, and tactor-based systems, each involving varying degrees of mechanical complexity. The present device elicits vivid tactile slip illusions through a minimalist architecture of only two independently actuated interleaved pin arrays [1], [2]. When driven in anti-phase, the arrays produce a differential motion mode that reliably evokes the sensation of a surface slipping beneath the finger. Building on this platform, the present work investigates whether vibration frequency can serve as an independent control parameter for perceived slip speed, independent of amplitude. A two-alternative forced-choice psychophysical experiment was conducted with 30 participants. In the motion detection part of the experiment, participants reliably identified the anti-phase stimulus as motion at 70 Hz and 90 Hz (both p < .001), while performance at 50 Hz did not exceed chance, attributed to hardware resonance. In the speed discrimination part of the experiment, participants consistently perceived frequencies above the 70 Hz reference as faster (p < .001 at 80 and 90 Hz), while four participants showed an inverted frequency–speed relationship. These results support frequency variation as a viable encoding strategy for perceived slip speed in dual-array tactile displays. ... Read more

Reliable robotic manipulation in everyday environments remains difficult because robots must interact with objects that differ in shape, weight, and frictional properties.
Manipulation tasks in such unstructured environments often require more than stable grasping, including reorientation of the object within the grasp.
A common example is pivoting, a reorientation task in which the object rotates within the fingers while translation is prevented.
This requires information about contact forces and proximity to slip at the fingertip, which can be provided by tactile sensing.
Recent work has shown that tactile data can be used to predict a frictional safety margin for slip caused by shear force.
However, in tasks involving rotation, such as pivoting, slip depends on both shear force and torque.
In this thesis, a generalized safety margin is introduced for pivoting by extending the safety margin estimation to also account for torque.
This is done using the Limit Surface, which describes the boundary between sticking and slipping under combined force and torque.
An experimental setup was built to measure slip under different force and torque combinations, from which the Limit Surface curves were fitted.
Using those curves and the displacement field from the tactile sensor, deep learning models were then trained to predict the contact forces and the generalized safety margin.
Validation on unseen data and experiments on grasp control and pivoting showed that tactile sensing can be used to predict and regulate friction during pivoting.
This thesis extends the frictional safety margin approaches of previous studies from translational loading to pivoting.
Estimating and regulating friction during pivoting could help robots perform a wider range of manipulation tasks in unstructured environments. ... Read more

Affective touch is a well-established regulator of emotional well-being, and there is growing interest in designing robotic devices that can replicate its benefits. Yet, most affective touch systems developed so far rely on simple linear stroking patterns, even though natural human touch is rarely so uniform. Specifically, the role of stroking trajectory in shaping affective experience has remained unexplored. This study investigated how the predictability of stroking touch influences pleasantness, subjective affect, and physiological arousal when delivered by a robot to the forearm. 22 healthy adults experienced three stroking trajectories (straight, sine, and sawtooth) at a constant CT-optimal velocity for two minutes each. The trajectories were each administered twice in randomized order. Perceived pleasantness, subjective valence and arousal, and heart rate variability (HRV) were measured for each trial. Statistical analyses showed that the straight trajectory was more pleasant than the sawtooth, while both the straight and sine trajectories resulted in lower subjective arousal than the sawtooth. No significant differences were found for valence or physiological arousal. These findings suggest that stroking predictability modulates subjective arousal, though the subtle trajectory differences were insufficient to produce measurable HRV changes under low-arousal conditions. In addition, a strong positive correlation between perceived pleasantness and valence was observed, raising the theoretical question of whether pleasantness in affective touch studies may be functionally equivalent to valence. The present study argues that stroking trajectory is a meaningful design parameter for robotic affective touch systems, with practical implications for the development of wearable haptic devices and companion robots seeking to modulate human affect.
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We present a low-cost, camera-based tactile sensor that leverages the photoelastic effect—interference fringes that appear under stress—to estimate contact force, position, and shape. Each fringe image is recorded at 50 Hz and processed by a multi-task neural network that predicts (i) the normal force (Fz ), (ii) the 2D contact location (x, y), and (iii) the shape class of the object. Two sensor variants were developed: Sensor 1, a layered design with fewer visible fringes, and Sensor 2, an integrated structure with improved fringe clarity. Both were evaluated using a ResNet-18 and a lightweight custom CNN, under three augmentation pipelines: grayscale images with 10 noisy augmented samples each, RGB images with 3 noisy augmentations, and RGB images with 3 clean (noise-free) augmentations. The base dataset includes nearly 15,000 synchronised samples of high-frequency fringe images and force signals. With augmentation, this was expanded to around 45,000 or 150,000 samples depending on the pipeline. The best results were achieved using Sensor 1 and ResNet-18 trained on grayscale images with 10 augmentations per input image. This configuration yielded a force MSE of 0.0213 N2, a contactpoint RMSE of 0.4462 mm, and 96.24% shape classification accuracy. Notably, even RGB images with only three augmentations per sample reached similar performance levels. These findings highlight that full-colour input and lightweight augmentation remain effective for accurate, scalable tactile sensing. Our modular learning pipeline generalises across sensor variants and data regimes, enabling robust, highfrequency tactile inference suitable for real-world deployment. ... Read more

Quadrupedal robots have great potential for deployment in challenging environments. However, one of the most significant challenges these robots face is maintaining stability on slippery surfaces due to inaccurate friction estimation. This thesis investigates the role of accurate friction estimation in improving locomotion and reducing slip in quadrupedal robots. A Model Predictive Controller (MPC) with a friction-aware constraint update is proposed and evaluated in a simulation environment using a physics-based simulation with Open Dynamics Engine (ODE).

The experimental results demonstrate that incorporating real-time friction measurement and constraint in the MPC framework significantly reduces slip occurrences, decreases energy consumption, and improves overall locomotion stability. Statistical hypothesis tests, including paired t-tests and Bonferroni corrections, confirm the significance of these improvements. The findings suggest that integrating real-time friction estimation into quadrupedal robot controllers can enhance their robustness and reduce the need for explicit slip recovery strategies. Future work should focus on extending this approach to real-world scenarios, incorporating actual friction sensors, and testing in diverse terrains. ... Read more

The absence of haptic feedback on touchscreens creates a big reliance on visual attention, leading to reduced focus and increased cognitive load, especially in dynamic real-world scenarios like driving or using interactive media. While previous research has extensively explored static pointing tasks, a significant gap exists in understanding interactions with moving targets. This thesis investigates the effect of active lateral force feedback, generated specifically by the Ultraloop haptic device, on user performance in dynamic point-following-tasks.
An experiment with 11 participants was carried out to separate the effect of vision and compare different types of haptic feedback across four conditions: Vision Only, Vision with Active Force, No Vision with Friction Modulation, and No Vision with Active Force. In this task, participants moved their finger on the Ultraloop to track a target that moved along a one-dimensional randomized multi-sine path. Then, their performance for each condition was evaluated by measuring the mean tracking error during their experimental trials. Then, their performance was evaluated with a McRuer crossover model analysis to measure human control behavior during the continuous pointing task by estimating parameters such as crossover frequency, lead and lag for each experimental condition.
The results demonstrate that active lateral force feedback significantly minimizes tracking error. It served as an additional cue in visual conditions, reducing the average tracking error by 24.1%, and acted as an effective sensory substitute in non-visual conditions, drastically outperforming friction modulation feedback by reducing the average tracking error by 34.8%. The McRuer analysis showed that it is possible to identify a human control behavior for visual conditions, but becomes quite complicated for non-visual conditions. Also, participants employed predictive control in visual conditions but reverted to reactive, heavily filtered strategies when relying solely on haptic feedback.
In conclusion, this experiment demonstrated that programmable active lateral force feedback is an effective tool for improving touch-enabled interactions in dynamic tasks. These findings expand the usability of active surface haptics, thereby advancing the development of more intuitive and efficient haptic touch interfaces in the future. ... Read more

Touch is fundamental to our perception of the world and to interaction with our physical surroundings. With touch we can intuitively and effortlessly move and shape objects and control complex machines. In most modern machines, the part that interfaces with user often integrate touchscreens or touchpads, owing to their ease of use. However, these interfaces often deliver very poor tactile feedback, which limits the usability in contexts such as driving, low-light environments, and for users with visual impairments. Existing solutions like vibrotactile feedback, are poor substitute to the richness of natural touch and offer only transient sensations. Surface haptic devices offer more complexity, but since they rely on friction modulation, they require continuous movement and cannot nudge the user to arbitrary directions. These limitations highlight the need for active lateral force devices that can guide users in an arbitrary direction. This thesis introduces the Ultra loop, an active surface haptic device that generates net lateral forces using resonant traveling waves. Built around an oblong ring-shaped structure, the Ultra loop provides a large and flat interaction area with uniform force generation. Unlike existing active haptic devices, it operates at resonance, achieving a high vibration amplitude-to-input ratio, resulting in a more salient force feedback. Additionally, this thesis introduces a planar adaptation of the Ultra loop, the flat Loop, which is more compact with a height of just 5 mm, facilitating integration into consumer electronics. These devices can guide users via their sense of touch and render complex forces fields by modulating the wave amplitude and phase control as a function of the position and velocity of the user. To evaluate their effectiveness, this thesis investigates two types of rendered haptic environments: position-based elastic potential fields and velocity based viscous damping. Experimental user studies show that participants could perceive virtual 3D shapes (e.g., bumps and holes) and stepwise force fields that enhance their target-search performance. Moreover, directional cues provided by the force feedback enabled users to navigate toward a target without visual feedback, while viscous damping environments, where lateral force is a function of finger speed, reduced oscillations during selection, and improved overall targeting performance. This doctoral work systematically explores the benefits of active force feedback in touch interactions by introducing resonant traveling wave-based haptic displays and performing user studies. By advancing surface-haptic technology, this research paves the way for next-generation touch interfaces that support eye-free interaction and effortless control of complex machines. ... Read more

The accurate prediction of object softness is crucial in many fields, from agriculture to medical care. Vision-based tactile sensors, which capture high-resolution images of contact interactions, have shown great potential in determining this material property. Many existing approaches, particularly those using end-to-end models, suffer from a 'black-box' problem where it is difficult to understand which features the models use to make their predictions. This lack of transparency makes it challenging to determine and correct errors. To overcome this, this paper shows a data-driven method that can decode information from acquired tactile images to extract pressure distributions and assign softness levels to different objects. A novel approach is explored, integrating a Convolutional Neural Network (CNN) to predict the pressure distribution and a Long Short-Term Memory (LSTM) network to assess material softness. It is demonstrated that the CNN model effectively learns necessary features from the tactile images, enabling precise pressure distribution predictions. Concurrently, the LSTM model analyzes temporal sequences of tactile data, accurately predicting material softness and differentiating ripe from overripe fruits. By utilizing the spatiotemporal pressure distribution, this method improves on existing methods by enabling the efficient use of tactile data and providing additional information that can be used to further enhance the model. This paper can be used as a stepping stone to a more complex system in which robotic control can be implemented based on the sensed material properties, allowing for better control loop mechanisms and expanding the applications of tactile sensing technologies. ... Read more

Minimally invasive medical procedures often require catheters, endoscopes and other devices to maintain position at a specific site in the body, to cut and remove tissue or for diagnostic purposes. Due to tool force exerted by the surgeon or the natural processes of the body, such as the activity of the heart or the lungs, the inserted device can dislodge or migrate from its intended location. Existing solution focus on stabilizing the tip, following high localized pressure, this can create tissue damage or even perforation. Hence, it can be beneficial to create stabilization over the full length of the catheter. I investigated the use of electroadhesion i.e. using electricity to adhere to the tissue wall. I created a scaled-up, flexible, electroadhesion stabilization proof of concept, consisting of two opposite-charged electrodes in a helical pattern, embedded in silicone rubber. Friction experiments were performed on the catheter proof of concept on two copper half-tube substrates. One of the three flexible scaled-up catheter samples showed an increase in the average dynamic friction coefficient of 10.2% between 0 and 2500 V for the 22 mm diameter substrate. The two other samples showed no or limited increase in friction, attributable to manufacturing differences. Predicting coating thickness is essential, as the coating is the determining factor for the performance of the electroadhesion device. The catheter showed potential, however, improved adhesion performance is required for feasibility on a smaller scale. ... Read more

Incipient slip detection plays an important role in human and robotic grasping. With the growing use of deep learning in vision-based tactile sensing, the black-box nature of these deep neural networks (DNNs) makes it difficult to analyze, debug, and validate their behavior and learned patterns. To fill this gap, eXplainable AI (XAI) methods have been introduced to shed light into the DNN’s reasoning regarding incipient slip detection. These methods generate saliency maps, highlighting the relevant regions in the input tactile image that resulted in the predicted degree of incipient slip. Temporal difference images have been
used to enhance the visualization of incipient slip and make saliency maps easier for human viewers to understand. Additionally, this research evaluates several XAI methods based on criteria such as high-resolution, smoothness, and faithfulness. The experiment examined 42 samples from the ChromaTouch tactile dataset, focusing on contact interactions with a flat object. The results showed that Poly-CAM satisfies all three criteria by accurately highlighting markers while emphasizing their relative importance in the DNN’s decision-making process. Overall, through visual analysis of saliency maps, our findings confirm that DNNs have successfully learned to localize crucial deformation features for detecting incipient slip. ... Read more

Creating a lateral force on a finger touching a touch- screen can provide the sensation of a bump in the surface, and generate a pulling sensation, which could enhance the experience of operating a touchscreen. The Ultraloop, a device built to generate such a lateral force on a finger in contact, works by producing flexural traveling waves that push the finger. However, its shape is not simple to manufacture. Moreover, its shape is inconvenient to place in most touch input interfaces, which often appear in flat devices. A flat UltraLoop is proposed providing similar traveling wave force feedback, fitting the form factor of flat human-machine touch interfaces better. Furthermore, the new shape allows for manufacturing from a sheet of aluminum, using a cnc. The flat Ultraloop works by actuating two orthogonal modes at around 38k Hz, with a phase shift of 90 degrees, similarly to the Ultraloop. To validate the performance, force measurements have been conducted showing a maximum lateral force of 0.3N. Also, the influence of the normal force, phase, and finger motion on the lateral force is investigated. Lastly, we present a demo showing application of the flat Ultraloop, simulating a spring and a bump. ... Read more

Humans perceive a pulling or pushing sensation when subjected to an asymmetric vibration. This so-called pseudo force has great potential to guide human movement. Previous research has exclusively focused on the effect of pseudo forces in open-loop environments, in which the user’s joint angular velocity cannot be corrected. As the latter is essential for providing movement guidance, this paper proposes the first closed-loop system in the field of pseudo forces, using amplitude-modulated pseudo forces as haptic feedback. With this feedback, the user was assisted in moving towards a specific target angular velocity. In a human factors experiment, the amplitude-modulated stimuli were compared to constant-amplitude stimuli. The results showed that amplitude-modulated pseudo forces significantly decreased the error between the user’s and the target angular velocity when continuous movement in the desired direction was achieved. Therefore, the study demonstrated that amplitude-modulated pseudo forces can effectively guide human movement, representing an essential step towards developing a wearable movement guidance device. ... Read more

In dangerous environments, teleoperation is needed to enable humans to execute tasks remotely. To assist in these tasks, haptic teleoperation systems provide the human operator with the sense of touch of the telerobot. One way to provide this sense of touch is through high-frequency vibration feedback. State-of-the-art solutions generally rely on integrated hardware, which limits their application to specific telerobots and master devices.
The aim of this study is to develop a deployable high-frequency vibration feedback method through an add-on setup. In the presented system, both the vibration recording device and vibration feedback display run on a single microcontroller. Furthermore, all components are small in size and portable by the robotic or human hand.
Spectral analysis of the replicated vibrations shows that the presented system is capable of mimicking textures. To evaluate the effectiveness of the texture imitations, a human factors experiment is conducted. Twenty participants executed a texture identification task for two conditions: a manual condition with direct tactile feedback and a teleoperated condition with tactile feedback displayed by the presented system.
Results show that 75-85% of the textures were correctly identified in the teleoperated condition. These correctness rates are close to the results of the manual condition (96% correct) and outperform the chances of random guessing by a factor three. In the teleoperated condition, participants took on average 67% longer than in the manual feedback condition.
Based on these results, it is concluded that the presented add-on system enables humans to accurately feel high-frequency vibrations in teleoperation. ... Read more

While defusing a bomb or performing a rescue mission with a teleoperated robot, grasping various objects is crucial. Despite being a routine activity, remote grasping is still challenging. It is difficult to apply an adequate grip force to avoid slippage and damage to an object. An additional challenge is controlling both motion and force at the same time during remote robot control (teleoperation). Therefore, this research presents a teleoperated semi-autonomous controller which assists the user with remote grasping by relieving the user from controlling the grip force. Our design enables the user (1) to control the position of the remote gripper while (2) the system controls the grip force autonomously. When the user grasps an object, the semi-autonomous controller maintains the grip force based on tactile feedback to prevent object slippage. For tactile feedback, our system uses a tactile sensor that can detect incipient slippage from deformations at the location of the contact. With two experiments, we show that the system can maintain an adequate grip force while being robust to external perturbations and input changes. Since this controller stably grasps objects while the user maintains control over the position of the remote robot, our method relieves the user and prevents object slippage ... Read more

In the field of soft robotics, rigid joints and links are replaced by soft, deformable elements, This causes soft continuum robot arms to excel in unpredictable environments, but to face challenges during control and shape reconstruction. The sensing ability present in octopus suckers provides inspiration for solutions. Octopuses employ their suckers not only to strengthen their grasp but also as tactile sensors to control the shape and position of their soft arms. This has motivated researchers to integrate artificial sensorized suckers in soft continuum robot arms Although various sensorized suckers have already been developed, their employed sensing methods tend to be low in resolution and are often poorly embedded into the overall sucker architecture. In this work, these limits are overcome by presenting an octopus-inspired suction cup with integrated high-resolution tactile sensing abilities. This is achieved by utilizing the Chromatouch Principle, which relies on embedding colored markers in the suction cup membrane. Tracking these markers with a camera produced tactile images containing useful information about forces, deformations and interactions with objects. Fabrication with multi-material additive manufacturing enabled direct integration of these markers into the suction cup membranes. We demonstrated the design’s basic functionality by conducting pull-off and pickup tests. The design exhibited a normal pull-off force of 9.53 N and a shear pull-off force of 5.28 N. It was also able to successfully pick up both flat and curved objects. The sensing ability was showcased by training a Convolutional Neural Network to learn the relationship between the camera images and the orientation of the suction cup with respect to a touching substrate. Using a spherical coordinate system, the orientation could be predicted with an error of less than 2 degrees for latitude and less than 9 degrees for longitude. This performance was validated by using the trained network to successfully correct the orientation when picking up objects under an angle. For a single suction cup, this ability can be utilized to correct the orientation and achieve perpendicular contact with an object, crucial for achieving a seal. On a larger scale, the integration of multiple suction cups in soft continuum robot arms has the potential to form a representation of the arm shape as a whole. It can thereby contribute to overcoming the control challenges faced in the field of soft robotics. ... Read more

When we manipulate objects in our day-to-day life, we perceive information on the object via force feedback that we sense with our sensorimotor system. However, in virtual reality, we lack these forces, which makes it more challenging to interact with the digital world. Wearables, such as hand exoskeletons, can provide force feedback in VR. Nonetheless, as the devices’ actuation or brake system is often bulky or heavy, users typically do not enjoy wearing them. In this study, we investigate the potential of a new friction-based mechanism that can address the existing issues. Our design adopts ultrasonic vibrations to generate a squeeze film, which is a well-studied phenomenon to decrease friction significantly. In literature, the phenomenon has only been investigated with vibrations from one side, with the goal of friction reduction. However, we show that by adding a vibrating surface opposite to the original one, we can extend the possibilities of squeeze films, enabling us to both decrease and increase friction. Since ultrasonic transducers can be miniaturized, our mechanism brings us closer to solving the size and weight issues of existing devices. ... Read more

It is impossible to imagine modern day interaction with technology without the use of touchscreens. It is a go-to interface to use for many applications, because of the high stimuli-response compatibility and adaptability of the graphical user interface. But the haptic feedback one would have with physical buttons and dials, is lost with the use of touchscreens. High potential to improve the interaction with high resolution haptic feedback is often ignored. In this paper, the use of a haptic pseudo-potential field rendering method on a friction modulated touchscreen is proposed. With this method, the user is assisted in moving towards a target by lowering the friction and impeded in moving away by increasing the friction coefficient. In a human factors experiment, this rendering method is compared to a position-based friction modulation method. Subjects are instructed to find a target path, based on the haptic feedback. The results show that the position-based rendering method has a higher hit-rate and lower movement times. This demonstrates that the pseudo-potential field method is difficult to perceive, however it is expected that advancements in rendering larger friction coefficient ranges or even active lateral force feedback will improve this rendering method. ... Read more

Our remarkable sense of touch provides us the feedback that is crucial for successfully manipulating a wide range of objects.
The unconscious synergy between touch and the precision grip is particularly astonishing.
During precision manipulation, humans constantly control their grip force to maintain a safety margin of approximately 25 percent above the minimum force required to prevent held objects from slipping.
The ability to accurately control this safety margin heavily relies on tactile feedback founded on sensed deformations of our fingertips.
Previous studies have demonstrated that, by using this feedback, humans even manage to maintain this safety margin independently of the weight or friction of a lifted object, and when the weight of a held object is perturbed.
However, it is still unknown whether the sense of touch can help us to maintain this safety margin when the friction of a statically held object is perturbed.
As previous methods could not deliver these friction perturbations, we demonstrated the viability of a new friction perturbation method that we employed to fill this knowledge gap.
Here we show that humans in fact do not adapt their grip force in response to an abrupt increase of friction, but do increase their grip force in response to an abrupt decrease of friction.
The asymmetry of these grip adaptations is consistent with current hypotheses on the limitations of our sense of friction.
Our results support the existence of the hypothesized inability of our sense of touch to directly sense an increase of friction.
These findings can help to enhance the haptic interaction between humans and machines, and may inspire the design of an artificial sense of touch that can greatly improve the manipulation dexterity of robotic grippers. ... Read more

Vibrotactile wearable devices are a non-intrusive and inexpensive means to provide haptic feedback directly on the user’s skin. These devices utilize one or multiple vibrotactile actuators to generate vibrations across the skin and into the tissue. Combining these vibrations in amplitude can create the illusion of a funneled sensation on the skin at another location than at the actual sites of stimulation. This allows for the placement of virtual actuators on the skin, such that fewer actuators need to be deployed. However, the illusion does not take into account that the waves originating from the actuator attenuate and disperse due to the viscoelastic properties of the skin. We hypothesize that this diffusion of the elastic energy in the skin is affecting the perception of this illusion. Therefore, if we correct for the wave propagation speed, and temporally focus the stimulation, we hypothesized that the specificity of the stimulation on the skin could be drastically improved. In this paper, a novel technique, which is named the inverse filter technique, was introduced that enables to focus the amplitude, frequency and phase of vibrations to one location while cancelling them at the remaining nearby positions. We developed a wearable device for the volar surface of the forearm on which we could independently control arbitrary waveforms at any position between a set of four physical actuators. A human-subject study found that the performance in terms of localization confidence was improved significantly, whereas the precision and accuracy of the task did not improve compared to when we did not correct for the wave attenuation and dispersion. These results show that focusing waves towards a target location has a direct influence on our confidence of localizing vibrotactile stimuli on the arm. Therefore, we anticipate that our findings can benefit industries interested in including localized vibrotactile feedback on the human body surface. ... Read more

Tactile sensing provides crucial information about the stability of a grasped object by a robotic gripper. Tactile feedback can be used to predict slip, allowing for timely response to perturbations and to avoid dropping objects. Tactile sensors, included in robotic grippers, measure vibrations, strain or shearing forces which are produced by the movement of the grasped object. With sufficient spatial resolution, tactile sensors can even classify slip or estimate the 3d force displacement field. However, current tactile sensors fail to preemptively detect slippage, requiring fast reaction times during applications in real-time control. Here we show a perception framework that can predict slippage before it occurs by estimating the frictional safety margin. The safety margin indicates the margin to the frictional strength of a grasp, which decreases for reduced friction or increased load force. An accurate safety margin estimate allows for more efficient robot grip force control while providing robustness against object uncertainty and frictional conditions. We developed a high resolution tactile sensor, on which we trained a convolutional neural network to learn the relationship between tactile images and the safety margin. The network’s performance is evaluated on unseen test data, showing robustness to variations in environmental conditions. The results demonstrate that the tactile images contain the information needed to produce accurate safety margin estimates. These estimates can be used for control up to 20% of the minimum required grip force, mimicking human grasping behavior. This approach can drive new grasp control methods and enable robotic grasping of fragile objects in highly dynamic environments. Applications can be found in harvesting, parcel sorting, or improving human-robot interaction. ... Read more