About

Michael A. Peshkin is a Professor of Mechanical Engineering and the Allen K. and Johnnie Cordell Breed Senior Professor in Design at Northwestern University. His research interests include robotics, cobots, surface haptics, human-machine interfaces, bioinspired electrosense, sensors, and actuators. He has received significant recognition for his contributions to engineering education and research, including the ASEE Ralph Coats Roe National Educator Award in 2017 and being named a Fellow of the National Academy of Inventors in 2014. Professor Peshkin has also been honored as the Charles Deering McCormick Professor of Teaching Excellence from 2011 to 2014. His educational background includes a Ph.D. in Physics from Carnegie Mellon University, an M.S. in Experimental Solid State Physics from Cornell University, and a B.A. in Physics from the University of Chicago. He is involved with the Center for Robotics and Biosystems at Northwestern and has contributed to the development of innovative courses such as Electronics Design and Engineering Analysis 3: System Dynamics, which are integral to Northwestern's engineering curriculum.

Research topics

• Artificial Intelligence
• Computer Science
• Embedded system
• Computer vision
• Materials science
• Acoustics
• Physics

Selected publications

• Strong yet backdrivable robots through capstan-amplified electroadhesive clutches

  npj Robotics · 2026-03-30

  articleOpen access

  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.

  PublisherOA PDFDOI

• Demonstrating Eyes-Free Object Retrieval via Fingertip Deflection Guidance Using the NURing

  2026-04-13

  articleOpen access

  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.

  PublisherDOI

• Camera-Based Closed-Loop Fingertip Deflection Guidance: Pilot Demonstrations in Target Acquisition and Object Retrieval

  2026-04-13

  articleOpen access

  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.

  PublisherDOI

• Toward human-resolution haptics: A high-bandwidth, high-density, wearable tactile display

  Science Advances · 2025-11-19 · 1 citations

  articleOpen access

  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.

  PublisherDOI

• NURing: A Tendon-Driven Wearable Ring for On-Demand Kinesthetic Haptic Feedback

  2025-07-08 · 2 citations

  article

  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.

  PublisherDOI

• High-performance electroadhesive clutches with multilayered architecture

  Science Advances · 2025-02-14 · 3 citations

  articleOpen access

  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.

  PublisherDOI

• Decoding roughness perception in distributed haptic devices

  PNAS Nexus · 2024-10-01 · 3 citations

  articleOpen access

  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.

  PublisherOA PDFDOI

• The Single-Pitch Texel: A flexible and practical texture-rendering algorithm

  PNAS Nexus · 2023-12-21 · 1 citations

  articleOpen access

  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.

  PublisherOA PDFDOI

• PixeLite: A Thin and Wearable High Bandwidth Electroadhesive Haptic Array

  IEEE Transactions on Haptics · 2023-05-03 · 11 citations

  articleOpen access

  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.

  PublisherOA PDFDOI

• Comparison of wide-band vibrotactile and friction modulation surface\n gratings

  arXiv (Cornell University) · 2021-03-30

  preprintOpen access

  This study seeks to understand conditions under which virtual gratings\nproduced via vibrotaction and friction modulation are perceived as similar and\nto find physical origins in the results. To accomplish this, we developed two\nsingle-axis devices, one based on electroadhesion and one based on out-of-plane\nvibration. The two devices had identical touch surfaces, and the vibrotactile\ndevice used a novel closed-loop controller to achieve precise control of\nout-of-plane plate displacement under varying load conditions across a wide\nrange of frequencies. A first study measured the perceptual intensity\nequivalence curve of gratings generated under electroadhesion and vibrotaction\nacross the 20-400Hz frequency range. A second study assessed the perceptual\nsimilarity between two forms of skin excitation given the same driving\nfrequency and same perceived intensity. Our results indicate that it is largely\nthe out-of-plane velocity that predicts vibrotactile intensity relative to\nshear forces generated by friction modulation. A high degree of perceptual\nsimilarity between gratings generated through friction modulation and through\nvibrotaction is apparent and tends to scale with actuation frequency suggesting\nperceptual indifference to the manner of fingerpad actuation in the upper\nfrequency range.\n

  PublisherOA PDFDOI

Recent grants

• HSD/DHB: Emergent Social Behaviors in Sensorimotor Control

  NSF · $534k · 2004–2008

Frequent coauthors

• J. Edward Colgate

  Northwestern University

  129 shared

• James L. Patton

  University of Illinois Chicago

  29 shared

• Arthur C. Sanderson

  Rensselaer Polytechnic Institute

  20 shared

• Roberta L. Klatzky

  Carnegie Mellon University

  19 shared

• James Sulzer

  MetroHealth Medical Center

  18 shared

• Ambarish Goswami

  15 shared

• Harry J. Lipkin

  Argonne National Laboratory

  14 shared

• János Gertler

  George Mason University

  13 shared

Awards & honors

• ASEE Ralph Coats Roe National Educator Award (2017)
• Fellow, National Academy of Inventors (2014)
• Charles Deering McCormick Professor of Teaching Excellence,…