Explainable Neural Networks for Incipient Slip Sensing in Robot Tactile Learning

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...

Lateral Force on Fingertips by Traveling Waves in a Flat Structure Based on the Ultraloop

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...

Using Amplitude-modulated Pseudo Forces to Control Human Movement

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...

Recording & Rendering High-Frequency Vibrations Through a Deployable System

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...

A semi-autonomous adaptive impedance grip force controller for teleoperated object grasping

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...

Controlling grip force by maintaining a constant frictional safety margin to improve robotic grasping

Manipulating soft and fragile objects is a challenging task in robotic grasping. The key challenge for robotic grasping is to exert enough grip force to prevent slipping while being gentle enough to prevent damage to an object. Existing grippers used for processes like automatic harvesting of fruits, either apply excessive grip force leading to...

Soft Robot Locomotion with Metachronal Waves

Conventional robots adopt wheels or robotic limbs for locomotion. Wheels are simple to control but not suitable for irregular terrains. On the other hand, robotic feet can overcome a wider variety of surfaces but are less desirable due to their complex design and control system. In nature, we find that invertebrate animals, like snails, can go...

Modulating Soft Matter Friction Using Opposable Ultrasonic Vibrations

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....

A Better Grasp on the Asymmetrical Adaptation of Grip Force in Response to Friction Perturbations

Our remarkable sense of touch provides us the feedback that is crucial for successfully manipulating a wide range of objects.<br/>The unconscious synergy between touch and the precision grip is particularly astonishing.<br/>During precision manipulation, humans constantly control their grip force to maintain a safety margin of approximately 25...

Pseudo Potential Fields on Surface-Haptic Touchscreens using Friction Modulation

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...

Focusing waves on skin surfaces to provide localized vibrotactile feedback

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...

Learning to estimate the proximity of slip using high-resolution tactile sensing

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...

Pseudo forces from asymmetric vibrations can provide movement guidance

When a trainee is (re)learning a skilled movement, physical guidance from a trainer is crucial. Yet, providing physical cues to guide movements is highly challenging when training is digitally mediated (e.g.remotely). This work demonstrates the utility of pseudo forces generated by a wearable tactile interface for providing non-intrusive...

Quantifying Feedback Modality Contributions for a Haptic Glove in VR Assembly

An integral part of creating compelling and useful immersive virtual environments is the presence of haptic feedback, where both kinesthetic and cutaneous feedback convey unique information critical to object handling and manipulation. State-of-the-art haptic gloves are broadening the workspace and degrees of freedom for hand motion in VR,...

The effect of variable force field strength on motor adaptation and subsequent generalization: An exploratory study to test the performance of the ARMANDA robot in a motor learning study

Humans continuously adapt to new sensorimotor environments, wherein we create motor commands to execute movements properly, such as picking up the telephone or riding a bike. Generalization of motor commands means that a learned movement, such as grasping a bottle, transfers to similar but new environments, such as grasping a carton of milk....