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Ashish D. Deshpande

22 accepted papers

2026

Characterizing Expectation Mismatch in a Brain-Controlled Upper-Body Rehabilitation Exoskeleton

Satyam Kumar, Kanishka Mitra, Deland Hu Liu, Hussein Alawieh, Frigyes Samuel Racz, Stefano Dalla Gasperina +2
RA-L 2026

Robot-assisted therapy has long promised to advance stroke rehabilitation by delivering intensive and personalized training, yet its clinical impact remains limited. Closing the sensorimotor loop with brain-computer interfaces offers a better strategy than passive mobilization, directly linking user

Cited by 1Source ↗Scholar ↗
2026

Human-Exoskeleton Kinematic Calibration to Improve Hand Tracking for Dexterous Teleoperation

Haiyun Zhang, Stefano Dalla Gasperina, Saad N. Yousaf, Job D. Ramirez, Toshimitsu Tsuboi, Tetsuya Narita +1
RA-L 2026

Hand exoskeletons are critical tools for dexterous teleoperation and immersive manipulation interfaces, but achieving accurate hand tracking remains a challenge due to user-specific anatomical variability and donning inconsistencies. These issues lead to kinematic misalignments that degrade tracking

Cited by 1Source ↗Scholar ↗
2024

BaRiFlex: A Robotic Gripper with Versatility and Collision Robustness for Robot Learning

Gu-Cheol Jeong, Arpit Bahety, Gabriel Pedraza, Ashish D. Deshpande, Roberto Martín-Martín
IROS 2024poster

We present a new approach to robot hand design specifically suited to enable robot learning methods and daily tasks in human environments. We introduce BaRiFlex, an innovative gripper design that alleviates the issues caused by unexpected contact and collisions during robot learning, offering collis…

Cited by 3Source ↗Scholar ↗
2024

Experimental and Simulation-Based Estimation of Interface Power During Physical Human-Robot Interaction in Hand Exoskeletons

Saad N. Yousaf, Gaurav Mukherjee, Raymond J. King, Ashish D. Deshpande
RA-L 2024

Even the best wearable robots face challenges with power losses in the system, especially at the physical attachment interface. While some sources for power loss are inherent to the system, such as human soft tissue or musculoskeletal joint damping, other sources such as soft padding materials and b

Cited by 5Source ↗Scholar ↗
2023

A Novel Control Law for Multi-Joint Human-Robot Interaction Tasks While Maintaining Postural Coordination

Keya Ghonasgi, Reuth Mirsky, Adrian M. Haith, Peter Stone, Ashish D. Deshpande
IROS 2023poster

Exoskeleton robots are capable of safe torque-controlled interactions with a wearer while moving their limbs through predefined trajectories. However, affecting and assisting the wearer's movements while incorporating their inputs (effort and movements) effectively during an interaction re-mains an…

Cited by 1Source ↗Scholar ↗
2023

Characterizing the Onset and Offset of Motor Imagery During Passive Arm Movements Induced by an Upper-Body Exoskeleton

Kanishka Mitra, Frigyes Samuel Racz, Satyam Kumar, Ashish D. Deshpande, José Del R. Millán
IROS 2023poster

Two distinct technologies have gained attention lately due to their prospects for motor rehabilitation: robotics and brain-machine interfaces (BMIs). Harnessing their combined efforts is a largely uncharted and promising direction that has immense clinical potential. However, a significant challenge…

Cited by 5Source ↗Scholar ↗
2022

Quantifying Changes in Kinematic Behavior of a Human-Exoskeleton Interactive System

Keya Ghonasgi, Reuth Mirsky, Adrian M. Haith, Peter Stone, Ashish D. Deshpande
IROS 2022poster

While human-robot interaction studies are becoming more common, quantification of the effects of repeated interaction with an exoskeleton remains unexplored. We draw upon existing literature in human skill assessment and present extrinsic and intrinsic performance metrics that quantify how the human…

Cited by 3Source ↗Scholar ↗
2021

Analytical Design of a Pneumatic Elastomer Robot With Deterministically Adjusted Stiffness

Uksang Yoo, Yang Liu, Ashish D. Deshpande, Farshid Alambeigi
RA-L 2021

This paper presents a novel Pneumatic Elastomer Robot (PER), called Deterministically Adjusted Stiffness-Pneumatic Elasotmer Robot (DAS-PER), that can concurrently display preprogrammed elongation and bending behaviors. Our design methodology integrates a comprehensive analytical modeling and additi

Cited by 11Source ↗Scholar ↗
2021

Capturing Skill State in Curriculum Learning for Human Skill Acquisition

Keya Ghonasgi, Reuth Mirsky, Sanmit Narvekar, Bharath Masetty, Adrian M. Haith, Peter Stone +1
IROS 2021poster

Humans learn complex motor skills with practice and training. Though the learning process is not fully understood, several theories from motor learning, neuroscience, education, and game design suggest that curriculum-based training may be the key to efficient skill acquisition. However, designing s…

Cited by 6Source ↗Scholar ↗
2021

Design and Validation of a Novel Exoskeleton Hand Interface: The Eminence Grip

Keya Ghonasgi, Chad G. Rose, Ana C. De Oliveira, Rohit John Varghese, Ashish D. Deshpande
ICRA 2021poster

How best to attach exoskeletons to human limbs is an open and understudied problem. In the case of upperbody exoskeletons, cylindrical handles are commonly used attachments due to ease of use and cost effectiveness. However, handles require active grip strength from the user and may result in undesi…

Cited by 6Source ↗Scholar ↗
2021

Monitoring Fatigue-Induced Changes in Performance during Robot-Mediated Dynamic Movement

Kaci E. Madden, Dragan Djurdjanovic, Ashish D. Deshpande
ICRA 2021poster

Robotic exoskeletons are promising devices capable of both administering therapeutic exercises and assessing human movement quality. Although assessing fatigue is crucial to informing effective strategies for rehabilitation, existing metrics for evaluating fatigue during robot-mediated exercise rema…

Cited by 0Source ↗Scholar ↗
2019

A Framework for Adaptation of Training Task, Assistance and Feedback for Optimizing Motor (Re)-Learning With a Robotic Exoskeleton

Priyanshu Agarwal, Ashish D. Deshpande
RA-L 2019

Motor (re)-learning using a robotic exoskeleton can be improved by understanding what constitutes the optimal training environment for a subject that can maximize motor learning. We present a framework for motor (re)-learning using a robotic exoskeleton that provides subject-specific training by ada

Cited by 18Source ↗Scholar ↗
2019

Effort Estimation in Robot-aided Training with a Neural Network

Ana C. de Oliveira, Kevin Warburton, James S. Sulzer, Ashish D. Deshpande
ICRA 2019poster

Robotic exoskeletons open up promising interventions during post-stroke rehabilitation by assisting individuals with sensorimotor impairments to complete therapy tasks. These devices have the ability to provide variable assistance tailored to individual-specific needs and, additionally, can measure…

Cited by 5Source ↗Scholar ↗
2018

Analyzing and Improving Cartesian Stiffness Control Stability of Series Elastic Tendon-Driven Robotic Hands

Prashant Rao, Ashish D. Deshpande
ICRA 2018poster

Robust and dexterous manipulation is identified as one of the critical challenges in the field of robotic hand design and control. A key requirement of dexterous manipulation is the ability to modulate fingertip force directions and magnitudes. Cartesian stiffness control is a strategy to generate p…

Cited by 11Source ↗Scholar ↗
2018

Human-Inspired Object Manipulation Control with the Anatomically Correct Testbed Hand

Taylor D. Niehues, Ashish D. Deshpande
ICRA 2018poster

Dexterous manipulation with robotic hands can be achieved using object-level impedance control strategies, which allow intuitive regulation of object position, external environmental interactions, and grasp forces. However, for grasp stability, object stiffness gains are limited by the inherent comp…

Cited by 2Source ↗Scholar ↗
2017

Analyzing achievable stiffness control bounds of robotic hands with coupled finger joints

Prashant Rao, Gray C. Thomas, Luis Sentis, Ashish D. Deshpande
ICRA 2017poster

The mechanical design of robotic hands has been converging towards low-inertia, tendon-driven strategies. As tendon driven robotic fingers are serial chain systems, routing strategies with compliant tendons lead to multi-articular coupling between the degrees of freedom. We propose a generalized ana…

Cited by 18Source ↗Scholar ↗
2017

Development and validation of modeling framework for interconnected tendon networks in robotic and human fingers

Taylor D. Niehues, Raymond J. King, Ashish D. Deshpande, Sean Keller
ICRA 2017poster

The primary contribution of this work is the development of a generalized modeling methodology for complex tendon systems toward a long-term goal of modeling the mechanical structure of the human finger. The key feature of this model is its ability to predict how muscle forces will transmit through…

Cited by 11Source ↗Scholar ↗
2017

Maestro: An EMG-driven assistive hand exoskeleton for spinal cord injury patients

Youngmok Yun, Sarah Dancausse, Paria Esmatloo, Alfredo Serrato, Curtis A. Merring, Priyanshu Agarwal +1
ICRA 2017poster

In this paper, we present an electromyography (EMG)-driven assistive hand exoskeleton for spinal-cord-injury (SCI) patients. We developed an active assistive orthosis, called Maestro, which is light, comfortable, compliant, and capable of providing various hand poses. The EMG signals are obtained fr…

Cited by 107Source ↗Scholar ↗
2016

Accurate torque control of finger joints with UT hand exoskeleton through Bowden cable SEA

Youngmok Yun, Priyanshu Agarwal, Jonas Fox, Kaci E. Madden, Ashish D. Deshpande
IROS 2016poster

The torque control of finger joints is important for effective hand rehabilitation after neural disorders such as stroke. This paper presents an approach for accurate torque control of finger joints with UT hand exoskeleton. We present (1) how we obtained an accurate kinematics model, (2) how we bui…

Cited by 56Source ↗Scholar ↗
2015

Design of robotic fingers with human-like passive parallel compliance

Pei-Hsin Kuo, James DeBacker, Ashish D. Deshpande
ICRA 2015poster

While human-like series passive compliance has been used in previous robotic hand designs, little attention has been paid to parallel passive compliance due to the lack of understanding of its importance in grasping and manipulation. In this paper, we present a novel design of compliant finger inspi…

Cited by 14Source ↗Scholar ↗