Michael A. Peshkin

Many eyes-free guidance systems convey direction through symbolic cues that require interpretation, potentially increasing cognitive load and competing with critical sensory channels. This work builds on prior studies of fingertip deflection as a physically-grounded guidance cue previously demonstrated in controlled 1D and 2D settings using an instrumented testbed. Here, a camera is integrated onto the actuation ring to enable object-referenced, closed-loop guidance during free reach. Using ArUco targets, the system estimates target displacement in the camera frame and maps this error into continuous fingertip deflection cues in real time. Two pilot demonstrations illustrate feasibility: (1) a Fitts-style touchscreen target acquisition task with trajectory visualization, and (2) an object-retrieval task with video-based evidence of guided approach and grasp. These vignettes ground a forthcoming study with participants who are blind and vision-impaired, and invite discussion on how ring-mounted sensing can best support embodied, eyes-free guidance in everyday interactions.

Many eyes-free guidance systems convey directional information through symbolic cues requiring interpretation, potentially increasing cognitive load and competing with existing sensory channels. We present an interactive demonstration of fingertip deflection as a continuous, physically-intuitive guidance cue that gently biases the arm during reach. Motivated by a challenge frequently reported by individuals with blindness — that of safely retrieving small objects within arm’s reach — we developed an eyes-free, object-retrieval task. Building on our prior NURing, we extend fingertip deflection beyond instrumented testbeds by integrating a camera on the actuation ring. This allows the NURing to detect ArUco-tagged objects, estimate their pose relative to the camera, and drive continuous closed-loop deflection cues toward the target in real time. This demonstration invites attendees to experience this embodied guidance firsthand and to explore how fingertip deflection could support future assistive and collaborative systems that guide action through physical intuition rather than cognitive translation.

Dexterous manipulation in compact robots requires combining high force output with passive backdrivability; capabilities that conventional geared actuation struggles to deliver. We introduce an electromechanical multiplexing architecture that routes power from a single drive shaft to multiple outputs and mechanically grounds them using capstan-amplified electroadhesive (EA) clutches in a load-transfer configuration. Wrapping thin-film EA clutches on cylindrical counter-surfaces provides exponential gain for EA braking force, while voltage pulse-width modulation yields sub-newton (<0.1 N) force resolution and low reflected impedance from the drive shaft, enabling compliant interaction. Force transmission behavior is explained by a mechanics-based model of curved clutches and supported by strain imaging showing a propagating, load-carrying slip front. Switching measurements under bipolar high-voltage drive demonstrate millisecond-scale release and effective operation near 1 kHz, enabling high-rate force modulation. Leveraging this clutch-level understanding, we realized a well-behaved system: a tendon-driven, two-finger gripper that transitions between highly backdrivable, cooperative grasping and firm, energy-efficient holding. By decoupling pulling from latching, the load-transfer design mechanically grounds the output without sustained motor torque, outlining a scalable route to compact, low-power robotic hands that maintain backdrivability while spanning three orders of magnitude in force.

Despite advances in digitizing vision and hearing, touch still lacks an equivalent digital interface matching the fidelity of human perception. This gap limits the quality of digital tactile information and the realism of virtual experiences. Here, we introduce a step toward human-resolution haptics: a class of wearable tactile displays designed to match the spatial and temporal acuity of the human fingertip. Our device, VoxeLite, is a 0.1-millimeter-thick, 0.19-gram, skin-conformal array of individually addressable soft electroadhesive actuators ("nodes"). As users touch and move across surfaces, VoxeLite delivers high-resolution distributed forces via the nodes. Enabled by scalable microfabrication techniques, the display achieves actuator densities up to 110 nodes per square centimeter, produces stimuli up to 800 hertz, and remains transparent to real-world tactile input. We demonstrate its ability to render small-scale hapticons and virtual textures and transmit physical surfaces, validated through human psychophysics and biomimetic sensing. These findings position VoxeLite as a platform for human-resolution haptics in immersive interfaces, robotics, and digital touch communication.

Generating salient and intuitively understood haptic feedback on the human finger through a non-intrusive wearable remains a challenge in haptic device development. Most existing solutions either restrict the hand and finger's natural range of motion or impede sensory perception, quickly becoming intrusive during dexterous manipulation tasks. Here, we introduce NURing (Non-intrUsive Ring), a tendon-actuated haptic device that provides kinesthetic feedback by deflecting the finger. The NURing is easily donned and doffed, enabling on-demand kinesthetic feedback while leaving the hand and fingers free for dexterous tasks. We demonstrate that the device delivers perceptually salient feedback and evaluate its performance through a series of uniaxial motion guidance tasks. The lightweight NURing device, measuring approximately 220 g, can generate guidance cues at up to 1 Hz, enabling participants to identify target directions in under 3s with a 1.5° steady-state error, corresponding to a fingertip deviation of less than 11mm. Additionally, it can guide users along complex, smooth trajectories with an average trajectory error of 7°. These findings highlight the effectiveness of fingertip deflection as a kinesthetic feedback modality, enabling precise guidance for real-world applications such as sightless touchscreen navigation, assistive technology, and both industrial and consumer augmented/virtual reality systems.

Electroadhesive (EA) clutches are promising for advanced motion and force control in robotics, haptics, and rehabilitation, owing to their compactness and light weight. However, their practical use is limited by the inability to deliver high forces at low voltages, primarily due to a lack of understanding of their mechanics. We introduce a novel deformable body fracture mechanics approach and high-resolution strain field imaging to reveal that nonuniform stress distributions cause EA clutches to fail through delamination and crack propagation. Using this insight, we developed EA clutches sustaining 22 newtons over 1 square centimeter at 100 volts, achieving the highest stress per voltage among similar clutches. This was achieved by incorporating a soft interlayer and peeling stopper for uniform stress distribution and mitigating the failure modes. These EA clutches were integrated into a lightweight ring-based wearable system for finger rehabilitation and haptics. Our findings lay the groundwork for designing low-voltage, high-performance EA clutches for next-generation motion and force control applications.

The ability to render realistic texture perception using haptic devices has been consistently challenging. A key component of texture perception is roughness. When we touch surfaces, mechanoreceptors present under the skin are activated and the information is processed by the nervous system, enabling perception of roughness/smoothness. Several distributed haptic devices capable of producing localized skin stretch have been developed with the aim of rendering realistic roughness perception; however, current state-of-the-art devices rely on device fabrication and psychophysical experimentation to determine whether a device configuration will perform as desired. Predictive models can elucidate physical mechanisms, providing insight and a more effective design iteration process. Since existing models (1, 2) are derived from responses to normal stimuli only, they cannot predict the performance of laterally actuated devices which rely on frictional shear forces to produce localized skin stretch. They are also unable to predict the augmentation of roughness perception when the actuators are spatially dispersed across the contact patch or actuated with a relative phase difference (3). In this study, we have developed a model that can predict the perceived roughness for arbitrary external stimuli and validated it against psychophysical experimental results from different haptic devices reported in the literature. The model elucidates two key mechanisms: (i) the variation in the change of strain across the contact patch can predict roughness perception with strong correlation and (ii) the inclusion of lateral shear forces is essential to correctly predict roughness perception. Using the model can accelerate device optimization by obviating the reliance on trial-and-error approaches.

As the number of applications for tactile feedback technology rapidly increases, so too does the need for efficient, flexible, and extensible representations of virtual textures. The previously introduced Single-Pitch Texel rendering algorithm offers designers the ability to produce textures with perceptually wide-band spectral characteristics while requiring very few input parameters. This paper expands on the capabilities of the rendering algorithm. Diverse families of fine textures, with widely varied spectral characteristics, were shown to be rendered reliably using the Texel algorithm. Furthermore, by leveraging an assistive algorithm, subjects were shown to consistently navigate the Texel parameter space in a matching task. Finally, a psychophysical study was conducted to demonstrate the rendering algorithm's resilience to spectral quantization, further reducing the data required to represent a virtual texture.

We present PixeLite, a novel haptic device that produces distributed lateral forces on the fingerpad. PixeLite is 0.15 mm thick, weighs 1.00 g, and consists of a 4×4 array of electroadhesive brakes ("pucks") that are each 1.5 mm in diameter and spaced 2.5 mm apart. The array is worn on the fingertip and slid across an electrically grounded countersurface. It can produce perceivable excitation up to 500 Hz. When a puck is activated at 150 V at 5 Hz, friction variation against the countersurface causes displacements of 627 ± 59 μm. The displacement amplitude decreases as frequency increases, and at 150 Hz is 47 ± 6 μm. The stiffness of the finger, however, causes a substantial amount of mechanical puck-to-puck coupling, which limits the ability of the array to create spatially localized and distributed effects. A first psychophysical experiment showed that PixeLite's sensations can be localized to an area of about 30% of the total array area. A second experiment, however, showed that exciting neighboring pucks out of phase with one another in a checkerboard pattern did not generate perceived relative motion. Instead, mechanical coupling dominates the motion, resulting in a single frequency felt by the bulk of the finger.