@conference {548, title = {BaRiFlex: A robotic gripper with versatility and collision robustness for robot learning}, booktitle = {2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year = {2024}, publisher = {IEEE}, organization = {IEEE}, author = {Jeong, Gu-Cheol and Bahety, Arpit and Pedraza, Gabriel and Deshpande, Ashish D and Mart{\'\i}n-Mart{\'\i}n, Roberto} } @article {550, title = {Effect of exoskeleton-based weight support on upper extremities functional tasks}, journal = {Authorea Preprints}, year = {2024}, author = {Bucchieri, Anna and Khair, Alexander and Laffranchi, Matteo and Deshpande, Ashish} } @conference {546, title = {Effects of wearing an upper extremity exoskeleton on measuring joint kinematics during standardized clinical assessment tasks}, booktitle = {2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)}, year = {2024}, publisher = {IEEE}, organization = {IEEE}, author = {Hong, Yoon No Gregory and Kim, Kyoungsoon and Deshpande, Ashish D and Roh, Jinsook} } @article {534, title = {Experimental and Simulation-Based Estimation of Interface Power During Physical Human-Robot Interaction in Hand Exoskeletons}, journal = {IEEE Robotics and Automation Letters}, volume = {9}, year = {2024}, month = {March}, pages = {2575-2581}, abstract = {

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 bias strap forces can be modulated to optimize interface power transmission. Few methods currently exist for estimating power loss at physical human-robot interfaces, especially for upper-body exoskeletons. This letter presents a novel method to estimate interface power from experimental data in a wearable hand device, along with a simulation model for predicting interaction behavior by incorporating viscoelastic properties at the attachment interface. The experimental method is implemented with the Maestro hand exoskeleton, and repeatability of the interface power estimation is confirmed with pilot human testing. Simulation results are compared with experimental estimation of interface power, showing agreement of trends and validating the use of a simulation model to predict physical human-robot interaction behavior. These findings highlight the advantages of multi-body simulations as a tool to perform modular, inexpensive, and predictive investigations in physical human-robot interaction, without affecting the real-world mechatronic system or hindering the subject{\textquoteright}s safety. The proposed tools for experimental estimation of interface power and simulation modeling can optimize the design and control of robots for seamless integration with the human body.

}, keywords = {design and human factors, Estimation, Exoskeletons, human-centered robotics, Physical human-robot interaction, Power measurement, Robots, Sea measurements, Torque, Torque measurement, wearable robotics}, issn = {2377-3766}, doi = {10.1109/LRA.2023.3326679}, author = {Yousaf, Saad N. and Mukherjee, Gaurav and King, Raymond and Deshpande, Ashish D.} } @article {545, title = {Kinematic Performance of a Customizable Single Degree-of-Freedom Gait Trainer for Cost-Effective Therapy Aimed at Neuromuscular Impairments}, journal = {Journal of Medical Devices}, volume = {18}, year = {2024}, pages = {011003}, author = {Jadav, Shail and Karvaje, Karthik Subramanya and Kadam, Sujay D and Vashista, Vineet and Sulzer, James and Deshpande, Ashish and Palanthandalam-Madapusi, Harish J} } @article {549, title = {Novel bio-inspired soft actuators for upper-limb exoskeletons: Design, fabrication and feasibility study}, journal = {Frontiers in Robotics and AI}, volume = {11}, year = {2024}, pages = {1451231}, author = {Zhang, Haiyun and Naquila, Gabrielle and Bae, Junghyun and Wu, Zonghuan and Hingwe, Ashwin and Deshpande, Ashish} } @article {544, title = {A Novel Parameter Estimation Method for Pneumatic Soft Hand Control Applying Logarithmic Decrement for Pseudo-Rigid Body Modeling}, journal = {Advanced Intelligent Systems}, year = {2024}, pages = {2400637}, author = {Zhang, Haiyun and Heung, Kelvin HoLam and Naquila, Gabrielle J and Hingwe, Ashwin and Deshpande, Ashish D} } @conference {547, title = {A Novel Velocity-Based Controller to Avoid Synergistic Movement After Stroke}, booktitle = {2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob)}, year = {2024}, publisher = {IEEE}, organization = {IEEE}, author = {Scott, Isaiah and Rose, Chad G and Deshpande, Ashish D} } @article {537, title = {Assessment of Upper-Body Movement Quality in the Cartesian-Space is Feasible in the Harmony Exoskeleton}, journal = {IEEE Transactions on Human-Machine Systems}, volume = {53}, year = {2023}, month = {Dec}, pages = {985-995}, abstract = {

To determine the most effective interventions for poststroke patients, it is imperative to monitor the recovery process. Robotic exoskeletons{\textquoteright} built-in sensing capabilities enable accurate kinematic measurement with no additional setup time. Although position sensors used in exoskeletons are accurate, a mismatch between the robot{\textquoteright}s and the human{\textquoteright}s joints can lead to inaccurate measurements. In addition, the robot{\textquoteright}s residual dynamics can interfere with human{\textquoteright}s natural movements and the kinematic metrics assessed in the robot would not be representative of the human{\textquoteright}s movement in free-motion. So far, the accuracy of robotic exoskeletons in assessing upper-body kinematics has not been verified. The bilateral upper-body Harmony exoskeleton has features favorable to minimize joint misalignments and the robot{\textquoteright}s residual dynamics. In this study, we examined Harmony{\textquoteright}s ability to accurately assess Cartesian-space kinematic parameters associated with the wearer{\textquoteright}s movement quality. We analyzed data collected from eight healthy participants that executed point-to-point movements with and without the presence of the robot and at fast and slow speeds. Ground truth was acquired with an optical motion capture, and we extracted the kinematic parameters from the measured data. The results suggest that Harmony can accurately measure kinematic parameters associated with movement quality, and these parameters could appropriately reflect wearer{\textquoteright}s natural movements at a slow speed. Therefore, Harmony could aid the evaluation of the effectiveness of different interventions, which is more sensitive and efficient than currently adopted clinical outcomes. This allows for individualization of a treatment plan and a detailed follow-up.

}, keywords = {Assistive robots, Atmospheric measurements, Exoskeletons, Kinematic assessment, Kinematics, Motion capture, Optical variables measurement, Particle measurements, rehabilitation robotics, Robot sensing systems, robotic exoskeleton, Training}, issn = {2168-2305}, doi = {10.1109/THMS.2023.3305391}, author = {De Oliveira, Ana C. and Deshpande, Ashish D.} } @booklet {536, title = {BaRiFlex: A Robotic Gripper with Versatility and Collision Robustness for Robot Learning}, year = {2023}, abstract = {

We present a new approach to robot hand design specifically suited for successfully implementing robot learning methods to accomplish tasks in daily human environments. We introduce BaRiFlex, an innovative gripper design that alleviates the issues caused by unexpected contact and collisions during robot learning, offering robustness, grasping versatility, task versatility, and simplicity to the learning processes. This achievement is enabled by the incorporation of low-inertia actuators, providing high Back-drivability, and the strategic combination of Rigid and Flexible materials which enhances versatility and the gripper{\textquoteright}s resilience against unpredicted collisions. Furthermore, the integration of flexible Fin-Ray linkages and rigid linkages allows the gripper to execute compliant grasping and precise pinching. We conducted rigorous performance tests to characterize the novel gripper{\textquoteright}s compliance, durability, grasping and task versatility, and precision. We also integrated the BaRiFlex with a 7 Degree of Freedom (DoF) Franka Emika{\textquoteright}s Panda robotic arm to evaluate its capacity to support a trial-and-error (reinforcement learning) training procedure. The results of our experimental study are then compared to those obtained using the original rigid Franka Hand and a reference Fin-Ray soft gripper, demonstrating the superior capabilities and advantages of our developed gripper system.

}, url = {https://arxiv.org/abs/2312.05323}, author = {Gu-Cheol Jeong and Arpit Bahety and Gabriel Pedraza and Ashish D. Deshpande and Roberto Mart{\'\i}n-Mart{\'\i}n} } @conference {533, title = {Characterizing the Onset and Offset of Motor Imagery During Passive Arm Movements Induced by an Upper-Body Exoskeleton}, booktitle = {2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year = {2023}, month = {Oct}, abstract = {

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 is whether motor intentions from the user can be accurately detected using non-invasive BMIs in the presence of instrumental noise and passive movements induced by the rehabilitation exoskeleton. As an alternative to the straight-forward continuous control approach, this study instead aims to characterize the onset and offset of motor imagery during passive arm movements induced by an upper-body exoskeleton to allow for the natural control (initiation and termination) of functional movements. Ten participants were recruited to perform kinesthetic motor imagery (MI) of the right arm while attached to the robot, simultaneously cued with LEDs indicating the initiation and termination of a goal-oriented reaching task. Using electroencephalogram signals, we built a decoder to detect the transition between i) rest and beginning MI and ii) maintaining and ending MI. Offline decoder evaluation achieved group average onset accuracy of 60.7\% and 66.6\% for offset accuracy, revealing that the start and stop of MI could be identified while attached to the robot. Furthermore, pseudo-online evaluation could replicate this performance, forecasting reliable online exoskeleton control in the future. Our approach showed that participants could produce quality and reliable sensorimotor rhythms regardless of noise or passive arm movements induced by wearing the exoskeleton, which opens new possibilities for BMI control of assistive devices.

}, keywords = {Decoding, Exoskeletons, Light emitting diodes, Manipulators, Neurorehabilitation, Performance evaluation, Robot sensing systems}, doi = {10.1109/IROS55552.2023.10342492}, author = {Mitra, Kanishka and Racz, Frigyes Samuel and Kumar, Satyam and Deshpande, Ashish D. and Del R. Mill{\'a}n, Jos{\'e}} } @booklet {529, title = {Differential Spiral Joint Mechanism for Coupled Variable Stiffness Actuation}, year = {2023}, abstract = {

In this study, we present the Differential Spiral Joint (DSJ) mechanism for variable stiffness actuation in tendon-driven robots. The DSJ mechanism semi-decouples the modulation of position and mechanical stiffness, allowing independent trajectory tracking in different parameter space. Past studies show that increasing the mechanical stiffness achieves the wider range of renderable stiffness, whereas decreasing the mechanical stiffness improves the quality of actuator decoupling and shock absorbance. Therefore, it is often useful to modulate the mechanical stiffness to balance the required level of stiffness and safety. In addition, the DSJ mechanism offers a compact form factor, which is suitable for applications where the size and weight are important. The performance of the DSJ mechanism in various areas is validated through a set of experiments.

}, url = {https://arxiv.org/abs/2301.09158}, author = {Mincheol Kim and Ashish Deshpande} } @conference {531, title = {An Extended Virtual Proxy Haptic Algorithm for Dexterous Manipulation in Virtual Environments}, booktitle = {2023 IEEE World Haptics Conference (WHC)}, year = {2023}, month = {July}, abstract = {

With the evolution of hand-based haptic interfaces, novel forms of controlled force feedback arise allowing multipoint interaction between virtual objects and the hand{\textquoteright}s digits. With these advances, there must be an effective force display coupled with an intuitive visualization of the hand at its points of high manipulability. This is the basis for dexterous manipulation immersion in virtual environments. Still, there are challenges due to the complexity of force interaction, bandwidth limitations, and redundant visual configurations. In this paper, we present an extended proxy algorithm for digit-based interactions, which through configuration-based optimization, provides an efficient, robust, and visually plausible way to interact with virtual objects with a virtual hand. Additionally, we revisit a seldom-seen modality of haptic rendering, whole-hand kinesthetic feedback, with the Maestro exoskeleton in the implementation of our algorithm. We unify these methods and develop a CHAI3D module in a comprehensive visuo-haptic framework that was evaluated through demonstrations of joint-level haptic force data during interaction with static and dynamic objects alike. Our computationally-efficient approach sets the foundation for the visual display of in-hand virtual object manipulation with the effective rendering of stable haptic interactions under complex tasks.

}, keywords = {Exoskeleton, Exoskeletons, Force, Force feedback, Haptics, Heuristic algorithms, Rendering (computer graphics), Simulation, Virtual environments, Virtual Reality, Visualization}, doi = {10.1109/WHC56415.2023.10224434}, author = {Galvan, Aldo F. and Ramirez, Job D. and Deshpande, Ashish D. and Fey, Ann Majewicz} } @article {530, title = {Kinematic coordinations capture learning during human-exoskeleton interaction}, journal = {Scientific Reports}, volume = {13}, year = {2023}, month = {06/2023}, abstract = {

Human{\textendash}exoskeleton interactions have the potential to bring about\ changes in human behavior for physical rehabilitation or skill augmentation. Despite significant advances in the design and control of these robots, their application to human training remains limited. The key obstacles to the design of such training paradigms are the prediction of human{\textendash}exoskeleton interaction effects and the selection of interaction control to affect human behavior. In this article, we present a method to elucidate behavioral changes in the human{\textendash}exoskeleton system and identify expert behaviors correlated with a task goal. Specifically, we observe the joint coordinations of the robot, also referred to as kinematic coordination behaviors, that emerge from human{\textendash}exoskeleton interaction during learning. We demonstrate the use of kinematic coordination behaviors with two task domains through a set of three human-subject studies. We find that participants (1) learn novel tasks within the exoskeleton environment, (2) demonstrate similarity of coordination during successful movements within participants, (3) learn to leverage these coordination behaviors to maximize success within participants, and (4) tend to converge to similar coordinations for a given task strategy across participants. At a high level, we identify task-specific joint coordinations that are used by different experts for a given task goal. These coordinations can be quantified by observing experts and the similarity to these coordinations can act as a measure of learning over the course of training for novices. The observed expert coordinations may further be used in the design of adaptive robot interactions aimed at teaching a participant the expert behaviors.

}, url = {https://www.nature.com/articles/s41598-023-35231-3}, author = {Keya Ghonasgi and Reuth Mirsky and Nisha Bhargava and Adrian M. Haith and Peter Stone and Ashish D. Deshpande} } @conference {532, title = {A Novel Control Law for Multi-Joint Human-Robot Interaction Tasks While Maintaining Postural Coordination}, booktitle = {2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year = {2023}, month = {Oct}, abstract = {

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{\textquoteright}s movements while incorporating their inputs (effort and movements) effectively during an interaction re-mains an open problem due to the complex and variable nature of human motion. In this paper, we present a control algorithm that leverages task-specific movement behaviors to control robot torques during unstructured interactions by implementing a force field that imposes a desired joint angle coordination behavior. This control law, built by using principal component analysis (PCA), is implemented and tested with the Harmony exoskeleton. We show that the proposed control law is versatile enough to allow for the imposition of different coordination behaviors with varying levels of impedance stiffness. We also test the feasibility of our method for unstructured human-robot interaction. Specifically, we demonstrate that participants in a human-subject experiment are able to effectively perform reaching tasks while the exoskeleton imposes the desired joint coordination under different movement speeds and interaction modes. Survey results further suggest that the proposed control law may offer a reduction in cognitive or motor effort. This control law opens up the possibility of using the exoskeleton for training the participating in accomplishing complex multi-joint motor tasks while maintaining postural coordination.

}, keywords = {Behavioral sciences, Exoskeletons, Human-robot interaction, Robot kinematics, Surveys, Training, Trajectory}, doi = {10.1109/IROS55552.2023.10342501}, author = {Ghonasgi, Keya and Mirsky, Reuth and Haith, Adrian M. and Stone, Peter and Deshpande, Ashish D.} } @article {486, title = {Designing Physical Human-Robot Interaction Interfaces: A Scalable Method for Simulation Based Design}, journal = {Frontiers in Neurorobotics}, year = {2022}, author = {Varghese, R. J. and Mukherjee, G. and Deshpande, A. D.} } @conference {497, title = {Dynamic Finger Task Identification Using Electromyography}, booktitle = {IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)}, year = {2022}, author = {Paria Esmatloo and Keya Ghonasgi and Raymond King and Ashish D. Deshpande} } @article {499, title = {Human-Like Endtip Stiffness Modulation Inspires Dexterous Manipulation With Robotic Hands}, journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering}, volume = {30}, year = {2022}, author = {Anna Shafer and Ashish D. Deshpande} } @conference {498, title = {Human-Robot Interaction: Muscle Activation and Angular Location Affect Soft Tissue Stiffness}, booktitle = {IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)}, year = {2022}, author = {Saad N. Yousaf and Keya Ghonasgi and Paria Esmatloo and Ashish D. Deshpande} } @conference {527, title = {Impact of Gravity Compensation on Upper Extremity Movements in Harmony Exoskeleton}, booktitle = {2022 International Conference on Rehabilitation Robotics (ICORR)}, year = {2022}, month = {July}, abstract = {

Robots have been used to offset the limb weight through gravity compensation in upper body rehabilitation to delineate the effects of loss of strength and loss of dexterity, which are two common forms of post-stroke impairments. In this paper, we explored the impact of this anti-gravity support on the quality of movement during reaching and coordinated arm movements in a pilot study with two participants with chronic stroke. The subjects donned the Harmony exoskeleton which supported proper shoulder coordination in addition to providing gravity compensation. Participants had previously taken part in seven one-hour sessions with the Harmony exoskeleton, performing six sets of passive-stretching and active exercises. Pre- and post-training sessions included assessments of two separate tasks, planar reaching and a set of six coordinated arm movements, in two conditions, outside of and supported by the exoskeleton. The movements were recorded using an optical motion capture system and analyzed using spectral arc length (SPARC) and straight line deviation to quantify movement smoothness and quality. We observed that gravity compensation resulted in an increased smoothness for the subject with high level of impairment whereas compensation resulted in a reduction in smoothness for the subject with low level of impairment in the reaching task. Both participants demonstrated better coordination of the shoulder-arm joint with gravity compensation. This result motivates further studies into the role of gravity compensation during coordinated movement training and rehabilitation interventions.

}, keywords = {Exoskeletons, Neural pathways, Optical feedback, Optical recording, Robot kinematics, Shoulder, Training}, doi = {10.1109/ICORR55369.2022.9896415}, author = {Hailey, Rhet O. and De Oliveira, Ana C. and Ghonasgi, Keya and Whitford, Bob and Lee, Robert K. and Rose, Chad G. and Deshpande, Ashish D.} } @conference {496, title = {Impact of Gravity Compensation on Upper Extremity Movements in Harmony Exoskeleton}, booktitle = {International Conference on Rehabilitation Robotics (ICORR)}, year = {2022}, author = {Rhet O. Hailey and Ana C. de Oliveira and Keya Ghonasgi and R. Whitford and R. Lee and Chad G. Rose and Ashish D. Deshpande} } @article {495, title = {Novel Biomedical Technologies: Rehabilitation Robotics}, journal = {Current Opinion in Biomedical Engineering}, volume = {22}, year = {2022}, author = {Ashish D. Deshpande} } @conference {528, title = {Quantifying Changes in Kinematic Behavior of a Human-Exoskeleton Interactive System}, booktitle = {2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)}, year = {2022}, month = {Oct}, abstract = {

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-exoskeleton system{\textquoteright}s behavior changes over time. Specifically, in this paper, we present a new performance metric that provides insight into the system{\textquoteright}s kinematics associated with {\textquoteleft}successful{\textquoteright} movements resulting in a richer characterization of changes in the system{\textquoteright}s behavior. A human subject study is carried out wherein participants learn to play a challenging and dynamic reaching game over multiple attempts, while donning an upper-body exoskeleton. The results demonstrate that repeated practice results in learning over time as identified through the improvement of extrinsic performance. Changes in the newly developed kinematics-based measure further illumi-nate how the participant{\textquoteright}s intrinsic behavior is altered over the training period. Thus, we are able to quantify the changes in the human-exoskeleton system{\textquoteright}s behavior observed in relation with learning.

}, keywords = {Atmospheric measurements, Exoskeletons, Games, Human-robot interaction, Interactive systems, Kinematics, Training}, doi = {10.1109/IROS47612.2022.9981032}, author = {Ghonasgi, Keya and Mirsky, Reuth and Haith, Adrian M. and Stone, Peter and Deshpande, Ashish D.} } @conference {526, title = {SCAPE: Learning Stiffness Control from Augmented Position Control Experiences}, booktitle = {Proceedings of the 5th Conference on Robot Learning}, year = {2022}, month = {08{\textendash}11 Nov}, publisher = {PMLR}, organization = {PMLR}, abstract = {

We introduce a sample-efficient method for learning state-dependent stiffness control policies for dexterous manipulation. The ability to control stiffness facilitates safe and reliable manipulation by providing compliance and robustness to uncertainties. Most current reinforcement learning approaches to achieve robotic manipulation have exclusively focused on position control, often due to the difficulty of learning high-dimensional stiffness control policies. This difficulty can be partially mitigated via policy guidance such as imitation learning. However, expert stiffness control demonstrations are often expensive or infeasible to record. Therefore, we present an approach to learn Stiffness Control from Augmented Position control Experiences (SCAPE) that bypasses this difficulty by transforming position control demonstrations into approximate, suboptimal stiffness control demonstrations. Then, the suboptimality of the augmented demonstrations is addressed by using complementary techniques that help the agent safely learn from both the demonstrations and reinforcement learning. By using simulation tools and experiments on a robotic testbed, we show that the proposed approach efficiently learns safe manipulation policies and outperforms learned position control policies and several other baseline learning algorithms.

}, url = {https://proceedings.mlr.press/v164/kim22b.html}, author = {Kim, Mincheol and Niekum, Scott and Deshpande, Ashish D.}, editor = {Faust, Aleksandra and Hsu, David and Neumann, Gerhard} } @conference {467, title = {An Actuated Indenter for Characterization of Soft Tissue Towards Human-Centered Design}, booktitle = { IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)}, year = {2021}, author = {Saad N. Yousaf and Keya Ghonasgi and Paria Esmatloo and Ashish D. Deshpande} } @conference {474, title = {Analytical Design of a Pneumatic Elastomer Robot with Deterministically Adjusted Stiffness}, booktitle = {2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021)}, year = {2021}, author = {Uksang Yoo and Yang Liu and Ashish Deshpande and Farshid Alambeigi} } @conference {468, title = {An Anthropomorphic Passive Instrumented Hand for Validating Wearable Robotic Systems}, booktitle = {IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)}, year = {2021}, author = {Avinash Baskaran and Paria Esmatloo and Matthew Times and Ashish Deshpande and Chad G. Rose} } @article {460, title = {Assessment of Upper-extremity Joint Angles using Harmony Exoskeleton}, journal = { IEEE Transactions on Neural Systems and Rehabilitation Engineering}, year = {2021}, issn = {1558-0210}, author = {Ana C. de Oliveira and James S. Sulzer and Ashish D. Deshpande} } @article {452, title = {Balancing Stability and Stiffness Through the Optimization of Parallel Compliance: Using Coupled Tendon Routing}, journal = {IEEE Robotics \& Automation Magazine}, volume = {28}, year = {2021}, month = {06/2021}, pages = {14-22}, author = {Mincheol Kim and Ashish D. Deshpande} } @conference {473, title = {Capturing Skill State in Curriculum Learning for Human Skill Acquisition}, booktitle = {2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021)}, year = {2021}, author = {Keya Ghonasgi and Reuth Mirsky and Sanmit Narvekar and Bharath Masetty and Adrian Haith and Peter Stone and Ashish Deshpande} } @conference {469, title = {Is the Cerebellum a Model-Based Reinforcement Learning Agent?}, booktitle = {Adaptive and Learning Agents (ALA) Workshop at the International Conference on Autonomous Agents and Multiagent Systems}, year = {2021}, author = {Bharath Masetty and Reuth Mirsky and Ashish D. Deshpande and Michael Mauk and Peter Stone} } @conference {465, title = {Design and Validation of a Novel Exoskeleton Hand Interface: The Eminence Grip}, booktitle = {IEEE International Conference on Robotics and Automation (ICRA)}, year = {2021}, author = {Keya Ghonasgi and Chad G. Rose and Ana C. de Oliveira and Rohit J. Varghese and Ashish D. Deshpande} } @conference {478, title = {The Effects of EMG-Based Classification and Robot Control Method on User{\textquoteright}s Neuromuscular Effort during Real-Time Assistive Hand Exoskeleton Operation}, booktitle = { International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)}, year = {2021}, abstract = {

EMG-based intention recognition and assistive device control are often developed separately, which can lead to the unintended consequence of requiring excessive muscular effort and fatigue during operation.\ In this paper, we address two important aspects of the performance of an integrated EMG-based assistive system. Firstly, we investigate the effects of muscular effort on EMG-based classification and robot control. Secondly, we propose a robot control solution that reduces muscular effort required in assisted dynamic daily tasks compared to the state-of-the-art control methods.

}, author = {Paria Esmatloo and Ashish Deshpande} } @article {448, title = {Improvement of Hand Functions of SCI Patients with EMG-driven Hand Exoskeleton: a Feasibility Study}, journal = {Wearable Technologies}, year = {2021}, abstract = {

We have developed a one-of-a-kind hand exoskeleton, called Maestro, which can power finger movements of those surviving severe disabilities to complete daily tasks using compliant joints. In this paper, we present results from a practical EMG control strategy conducted with spinal cord injury (SCI) patients (C5, C6 and C7) in which the subjects completed daily tasks controlling Maestro with electromyography (EMG) signals from their forearm muscles. With its compliant actuation and its degrees of freedom (DOF) that match the natural finger movements, Maestro is capable of helping the subjects grasp and manipulate a variety of daily objects (more than 15 from a standardized set). To generate control commands for Maestro, an artificial neural network algorithm was implemented along with a probabilistic control approach to classify and deliver four hand poses robustly with three EMG signals measured from the forearm and palm. Increase in the scores of a standardized test, called the Sollerman hand function test (SHFT), and enhancement in different aspects of grasping such as strength shows feasibility that Maestro can be capable of improving the hand function of SCI subjects.

}, author = {Youngmok Yun and Youngjin Na and Paria Esmatloo and Sarah Dancausse and Alfredo Serrato and Curtis A. Merring and Priyanshu Agarwal and Ashish D. Deshpande} } @article {453, title = {Kinematic comparison of single degree-of-freedom robotic gait trainers}, journal = {Mechanism and Machine Theory}, year = {2021}, abstract = {

Single degree-of-freedom mechanized gait trainers employing linkage mechanisms
can imitate the gait trajectory of the human user at a potentially lower cost than current
commercial solutions. Our goal was to evaluate recently introduced four-, six- and
eight-bar designs from the standpoint of kinematics, that is, the ability to follow a
natural gait pattern. Based on gait database of 113 healthy individuals, we synthesized
mechanisms allowing two link length adjustments and compared trajectory and path

accuracy of the ankle across mechanisms. We used cross-validation to obtain data-
independent accuracy. We used gait trajectories from a large human database and

predicted additional trajectories to represent effects of varying heights and speeds. We
found that trajectory error was significantly lower in the eight-bar mechanism (3.77 {\textpm}
0.17 cm, mean {\textpm} SD) than the four- (6.84 {\textpm} 0.37 cm) and six-bar (7.15 {\textpm} 0.48 cm)

configurations (p\<0.0001). However, we did not observe differences in time-
independent path error between configurations, or in mechanical advantage (p\>0.05).

We conclude that the eight-bar configuration is best when the mechanism is tied to a
constant velocity actuator, whereas the four-bar mechanism performs as well if the
actuator is well-controlled.

}, author = {Jeonghwan Lee and Lailu Li and Sung Yul Shin and Ashish D. Deshpande and James Sulzer} } @conference {466, title = {A Method for the Analysis of Physical Human Robot Interaction}, booktitle = { IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)}, year = {2021}, author = {Saad N. Yousaf and Paria Esmatloo and Keya Ghonasgi and Ashish D. Deshpande} } @article {455, title = {A Modular Design for Distributed Measurement of Human-Robot Interaction Forces in Wearable Devices}, journal = {Sensors}, year = {2021}, author = {Keya Ghonasgi and Saad N. Yousaf and Paria Esmatloo and Ashish D. Deshpande} } @conference {464, title = {Monitoring Fatigue-Induced Changes in Performance during Robot-Mediated Dynamic Movement}, booktitle = {IEEE International Conference on Robotics and Automation (ICRA)}, year = {2021}, author = {Kaci E. Madden and Dragan Djurdjanovic and Ashish D. Deshpande} } @article {470, title = {The Road Forward for Upper Extremity Rehabilitation Robotics}, journal = {Current Opinion in Biomedical Engineering}, year = {2021}, abstract = {

Despite concerted efforts over the last three decades, upper-extremity robotic rehabilitation has yet to reach its full potential. We assert that assuming the goal of robotic rehabilitation is to automate conventional therapy may have led to overly narrow research directions and to mixed results from clinical studies. Recontextualizing this assumption opens promising research avenues for roboticists. Breaking the robotic device design loop and instead seeking out {\textquoteleft}big data{\textquoteright} opportunities has the potential to identify promising robot-mediated interventions. This will require a shift in roboticists{\textquoteright} attitudes towards participating in neuroscience and clinical research. By expanding assessment beyond kinematics, robotic devices can provide clinicians with a more complete picture of impairment and recovery. We discuss the current assumptions in greater detail, and point towards promising research in these revised directions.

}, issn = {ISSN 2468-4511}, author = {Chad G. Rose and Ashish D. Deshpande and Jacob Carducci and Jeremy D.Brown} } @conference {481, title = {SCAPE: Learning Stiffness Control from Augmented Position Control Experiences}, booktitle = {Conference on Robot Learning. Proceedings of Machine Learning Research}, year = {2021}, author = {Mincheol Kim and Scott Niekum and Ashish Deshpande} } @article {454, title = {Using a System-Based Monitoring Paradigm to Assess Fatigue during Submaximal Static Exercise of the Elbow Extensor Muscles}, journal = {Sensors}, year = {2021}, author = {Kaci Madden and Dragan Djurdjanovic and Ashish Deshpande} } @conference {449, title = {Design and Validation of a Sensorized Physical Human-Robot Interface for Distributed Force Measurement}, booktitle = {2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Workshop on Ergonomic Human-Robot Collaboration: Opportunities and Challenges}, year = {2020}, author = {Keya Ghonasgi and Saad N. Yousaf and Paria Esmatloo and Ruth Heckler and Job Ramirez and Chad G. Rose and Ashish D. Deshpande} } @conference {428, title = {Fingertip Position and Force Control for Dexterous Manipulation through Model-Based Control of Hand-Exoskeleton-Environment}, booktitle = {IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM) (AIM 2020). }, year = {2020}, author = {Paria Esmatloo and Ashish D. Deshpande} } @conference {427, title = {Human-like Endtip Stiffness Modulation for Stable, Dexterous Manipulation}, booktitle = {8th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob 2020)}, year = {2020}, author = {Anna Shafer and Ashish D. Deshpande} } @proceedings {432, title = {A Novel Inverse Kinematics Method for Upper-Limb Exoskeleton under Joint Coordination Constraints}, year = {2020}, author = {Stefano D. Gasperina and Keya Ghonasgi and Ana C. de Oliveira and Ashish D. Deshpande} } @conference {396, title = {Effort Estimation in Robot-aided Training with a Neural Network}, booktitle = {IEEE International Conference on Robotics and Automation}, year = {2019}, author = {de Oliveira, Ana C and Warburton, Kevin and Sulzer, James and Deshpande, Ashish D} } @conference {411, title = {Estimating the Effect of Robotic Intervention on Elbow Joint Motion}, booktitle = { IEEE International Symposium on Robot and Human Interactive Communication }, year = {2019}, month = {09/2019}, author = {Keya Ghonasgi and Ana C. de Oliveira and Anna Shafer and Chad G. Rose and Ashish D. Deshpande} } @conference {397, title = {Exploring the Capabilities of Harmony for Upper-Limb Stroke Therapy}, booktitle = {IEEE International Conference on Rehabilitation Robotics}, year = {2019}, author = {de Oliveira, Ana C and Rose, Chad G. and Warburton, Kevin and Ogden, Evan M. and Whitford, B. and Lee, R.K. and Deshpande, A.D.} } @article {395, title = {A Framework for Adaptation of Training Task, Assistance and Feedback for Optimizing Motor (Re)-Learning With a Robotic Exoskeleton}, journal = {IEEE Robotics and Automation Letters}, volume = {4}, year = {2019}, chapter = {808}, author = {Priyanshu Agarwal and Ashish D. Deshpande} } @conference {370, title = {Analyzing and Improving Cartesian Stiffness Control Stability of Series Elastic Tendon-driven Robotic Hands}, booktitle = {IEEE International Conference on Robotics and Automation}, year = {2018}, author = {Rao, P. and Deshpande, A.D.} } @article {379, title = {Assessing Wrist Movement with Robotic Devices}, journal = {IEEE Transactions on Neural Systems \& Rehabilitation Engineering}, year = {2018}, author = {Chad G. Rose and Evan Pezent and Claudia K. Kanny and Ashish D. Deshpande and Marcia K. O{\textquoteright}Malley} } @article {377, title = {Design of an Underactuated, Adaptable Electromechanical Gait Trainer for People with Neurological Injury}, journal = {Journal of Mechanisms and Robotics}, year = {2018}, author = {S. Y. Shin and Deshpande, A. and Sulzer, J.} } @conference {378, title = {Designing Variable Stiffness Profiles To Optimize The Physical Human Robot Interface Of Hand Exoskeletons}, booktitle = {BioRob (IEEE International Conference on Biomedical Robotics and Biomechatronics)}, year = {2018}, author = {Varghese, R. J. and Mukherjee, G. and King, R. and Keller, S. and Deshpande, A. D.} } @conference {371, title = {Human-Inspired Object Manipulation Control with the Anatomically Correct Testbed Hand}, booktitle = {IEEE International Conference on Robotics and Automation}, year = {2018}, author = {Taylor D. Niehues and Ashish D. Deshpande} } @conference {383, title = {Methodology of an Inverse Kinematic Model for Estimating Shoulder Girdle Angles without Acromial Sensing}, booktitle = {48th International Conference on Environmental Systems}, year = {2018}, author = {Ogden, Evan M and Deshpande, Ashish D and Rajulu, Sudhakar L} } @conference {369, title = {Monitoring Human Neuromusculoskeletal System Performance during Spacesuit Glove Use: A Pilot Study}, booktitle = {IEEE Aerospace Conference}, year = {2018}, author = {Madden, Kaci E. and Djurdjanovic, D. and Deshpande, A.D.} } @article {357, title = {Subject-specific Assist-as-needed Controllers for a Hand Exoskeleton for Rehabilitation}, journal = {IEEE Robotics and Automation Letters (RA-L)}, volume = {3}, year = {2018}, author = {Agarwal, P and Deshpande, A. D.} } @conference {316, title = {Analyzing Achievable Stiffness Control Bounds of Robotic Hands With Compliantly Coupled Finger Joints}, booktitle = {IEEE International Conference on Robotics and Automation (ICRA)}, year = {2017}, author = {Prashant Rao and Gray C. Thomas and Luis Sentis and Ashish D. Deshpande} } @conference {381, title = {Arm kinematics estimation with the Harmony exoskeleton}, booktitle = {2017 International Symposium on Wearable Robotics and Rehabilitation (WeRob)}, year = {2017}, author = {de Oliveira, Ana C and Warburton, Kevin and Yun, Youngmok and Ogden, Evan M and Sulzer, James and Deshpande, Ashish D} } @conference {348, title = {Design and Characterization of a Robotics Exoskeletal Device for Hand-Wrist Rehabilitation}, booktitle = {IEEE International Conference on Rehabilitation Robotics (ICORR)}, year = {2017}, author = {Pezent, E. and Rose, C. G. and Deshpande, A. D. and O{\textquoteright}Malley, M. K.} } @article {300, title = {Design, Control and Testing of a Thumb Exoskeleton with Series Elastic Actuation}, journal = {International Journal of Robotics Research}, year = {2017}, keywords = {Exoskeleton, Hand, Thumb}, author = {Priyanshu Agarwal and Youngmok Yun and Jonas Fox and Kaci E. Madden and Ashish D. Deshpande} } @conference {318, title = {Development and validation of modeling framework for interconnected tendon networks in robotic and human fingers}, booktitle = {IEEE International Conference on Robotics and Automation (ICRA)}, year = {2017}, publisher = {IEEE}, organization = {IEEE}, author = {Niehues, Taylor D and King, Raymond J and Deshpande, Ashish D and Keller, Sean} } @conference {319, title = {An EMG-Driven Assistive Hand Exoskeleton for Spinal Cord Injury Patients: Maestro}, booktitle = {IEEE International Conference on Robotics and Automation (ICRA)}, year = {2017}, author = {Youngmok Yun and Sarah Dancausse and Paria Esmatloo and Alfredo Serrato and Curtis A. Merring and Ashish D. Deshpande} } @conference {349, title = {Estimating Anatomical Wrist Joint Motion with a Robotic Exoskeleton}, booktitle = {IEEE International Conference on Rehabilitation Robotics (ICORR)}, year = {2017}, author = {Rose, C. G. and Kann, C. K. and Deshpande, A. D. and O{\textquoteright}Malley, M. K.} } @conference {380, title = {Evaluation of the Harmony exoskeleton as an upper extremity rehabilitation tool after stroke}, booktitle = {2017 International Symposium on Wearable Robotics and Rehabilitation (WeRob)}, year = {2017}, author = {Ogden, Evan M and Chiu, David and Clearman, Rebecca and Card, Cynthia and Deshpande, Ashish D} } @conference {350, title = {The Influence of Robotic Assistance on Reducing Neuromuscular Effort and Fatigue during Extravehicular Activity Glove Use}, booktitle = {International Conference on Environmental Systems (ICES)}, year = {2017}, month = {07/2017}, author = {Madden, Kaci E. and Deshpande, Ashish D. and Peters, Benjamin J. and Rogers, Jonathan M. and Laske, Evan A. and McBryan, Emily R.} } @conference {334, title = {Methodologies for determining minimal grasping requirements and sensor locations for sEMG-based assistive hand orthosis for SCI patients}, booktitle = {IEEE International Conference of Rehabilitation Robotics (ICORR)}, year = {2017}, author = {Youngmok Yun and Paria Esmatloo and Alfredo Serrato and Curtis A. Merring and Ashish D. Deshpande} } @conference {382, title = {Mirrored movement therapy using an upper body robotic exoskeleton for stroke}, booktitle = {2017 International Symposium on Wearable Robotics and Rehabilitation (WeRob)}, year = {2017}, author = {Warburton, Kevin and de Oliveira, Ana C and Ogden, Evan M and Yun, Youngmok and Sulzer, James and Deshpande, Ashish D} } @article {331, title = {Series Elastic Actuators for Small-Scale Robotic Applications}, journal = {Journal of Mechanisms and Robotics}, volume = {9}, year = {2017}, month = {03/2017}, chapter = {1168}, author = {Priyanshu Agarwal and Ashish D. Deshpande} } @article {332, title = {An Upper-Body Rehabilitation Exoskeleton Harmony with an Anatomical Shoulder Mechanism: Design, Modeling, Control, and Performance Evaluation}, journal = {International Journal of Robotics Research (IJRR)}, volume = {36}, year = {2017}, pages = {414-435}, author = {Bongsu Kim and Ashish D. Deshpande} } @article {343, title = {Variable Thumb Moment Arm Modeling and Thumb-Tip Force Production of a Human-Like Robotic Hand}, journal = {Journal of Biomechanical Engineering}, volume = {139}, year = {2017}, pages = {101005}, author = {Niehues, Taylor D and Deshpande, Ashish D} } @conference {289, title = {Accurate Torque Control of Finger Joints with UT Hand Exoskeleton through Bowden Cable SEA}, booktitle = {IEEE International Conference on Robotics and Automation (IROS)}, year = {2016}, author = {Youngmok Yun and Agarwal, P. and Fox, Jonas and Madden, K.E. and Deshpande, A.D.} } @conference {325, title = {BloomBot, a Creative and Autonomous Land Art Robot}, booktitle = {IEEE International Conference on Robotics and Automation (IROS)}, year = {2016}, author = {James Sham and Mark L. Jennings and Ashish D. Deshpande} } @article {290, title = {Control in the Reliable Region of a Statistical Model}, journal = {Transactions on Robotics}, volume = {32}, year = {2016}, chapter = {1017}, author = {Yun, Y. and J. Ko and Deshpande, A.D.} } @conference {287, title = {A Novel Framework for Optimizing Motor (Re)-Learning with a Robotic Exoskeleton}, booktitle = {Biomechanics and Neural Control of Movement (BANCOM)}, year = {2016}, author = {Agarwal, P. and Deshpande, A.D.} } @article {288, title = {A Simulation Framework for Virtual Prototyping of Robotic Exoskeletons}, journal = {Journal of Biomechanical Engineering}, volume = {138}, year = {2016}, author = {Agarwal, P. and Neptune, R. and Deshpande, A.D.} } @conference {291, title = {Understanding the Mechanisms of Scapulohumeral Rhythm with the HARMONY Exoskeleton}, booktitle = {Biomechanics and Neural Control of Movement (BANCOM)}, year = {2016}, author = {Ogden, Evan M. and Deshpande, A. D.} } @article {yun2015accurate, title = {Accurate, Robust, and Real-Time Pose Estimation of Finger}, journal = {Journal of Dynamic Systems, Measurement, and Control}, volume = {137}, number = {3}, year = {2015}, pages = {034505}, publisher = {American Society of Mechanical Engineers}, chapter = {1}, author = {Yun, Youngmok and Agarwal, Priyanshu and Deshpande, A.D.} } @conference {286, title = {Assist-As-Needed Controllers for Index Finger Module of a Hand Exoskeleton for Rehabilitation}, booktitle = {Dynamic Systems and Control Conference (DSCC)}, year = {2015}, author = {Agarwal, P. and Fernandez, B. and Deshpande, A.D.} } @conference {rose2015characterization, title = {Characterization of a hand-wrist exoskeleton, READAPT, via kinematic analysis of redundant pointing tasks}, booktitle = {Rehabilitation Robotics (ICORR), 2015 IEEE International Conference on}, year = {2015}, pages = {205{\textendash}210}, publisher = {IEEE}, organization = {IEEE}, author = {Rose, Chad G. and Sergi, Fabrizio and Yun, Youngmok and Madden, Kaci E. and Deshpande, A.D. and O{\textquoteright}Malley, Marcia K.} } @article {niehues2015compliance, title = {Compliance in parallel to actuators for improving stability of robotic hands during grasping and manipulation}, journal = {The International Journal of Robotics Research}, volume = {34}, year = {2015}, pages = {0278364914558016}, publisher = {SAGE Publications}, chapter = {256}, author = {Niehues, Taylor D. and Rao, Prashant and Deshpande, A.D.} } @conference {315, title = {Crocheted Artificial Tendons and Ligaments for the Anatomically Correct Testbed (ACT) Hand}, booktitle = {IEEE ROBIO}, year = {2015}, author = {Z. Xu and Y. Matsuoka and Ashish D. Deshpande} } @article {kuo2015design, title = {Design and performance of a motor-driven mechanism to conduct experiments with the human index finger}, journal = {Journal of Mechanisms and Robotics}, volume = {7}, number = {3}, year = {2015}, pages = {031010}, publisher = {American Society of Mechanical Engineers}, author = {Kuo, Pei-Hsin and Hayes, Jerod and Deshpande, Ashish D.} } @conference {317, title = {Effect of Parallel Compliance on Stability of Robotic Hands With Series Elastic Actuators}, booktitle = {ASME Dynamic Systems and Controls Conference (DSCC)}, year = {2015}, month = {10/2015}, author = {Prashant Rao and Taylor D. Niehues and Ashish D. Deshpande} } @conference {agarwal2015impedance, title = {Impedance and Force-Field Control of the Index Finger Module of a Hand Exoskeleton for Rehabilitation}, booktitle = {Rehabilitation Robotics (ICORR)}, year = {2015}, pages = {85{\textendash}90}, publisher = {IEEE}, organization = {IEEE}, author = {Agarwal, Priyanshu and Deshpande, A.D.} } @article {285, title = {An Index Finger Exoskeleton with Series Elastic Actuation for Rehabilitation: Design, Control and Performance Characterization}, journal = {International Journal of Robotics Research (IJRR)}, volume = {34}, year = {2015}, chapter = {1747}, author = {Agarwal, P. and Fox, Jonas and Yun, Y. and O{\textquoteright}Malley, M.K. and Deshpande, A.D.} } @article {madden2015integration, title = {On Integration of Additive Manufacturing During the Design and Development of a Rehabilitation Robot: A Case Study}, journal = {Journal of Mechanical Design}, year = {2015}, author = {Madden, Kaci E. and Deshpande, A.D.} } @article {kuo2015novel, title = {A Novel Joint Design for Robotic Hands with Human-Like Nonlinear Compliance}, journal = {Journal of Mechanisms and Robotics}, year = {2015}, author = {Kuo, Pei-Hsin and Deshpande, A.D.} } @conference {niehues2014cartesian, title = {Cartesian-space control and dextrous manipulation for multi-fingered tendon-driven hand}, booktitle = {Robotics and Automation (ICRA), 2014 IEEE International Conference on}, year = {2014}, pages = {6777{\textendash}6783}, publisher = {IEEE}, organization = {IEEE}, author = {Niehues, Taylor D. and Badger, Julia and Diftler, Myron and Deshpande, Ashish D.} } @conference {yun2014control, title = {Control in the reliable region of a statistical model with Gaussian process regression}, booktitle = {Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on}, year = {2014}, pages = {654{\textendash}660}, publisher = {IEEE}, organization = {IEEE}, author = {Yun, Youngmok and Deshpande, Ashish D.} } @article {kim2014design, title = {Design of Nonlinear Rotational Stiffness Using a Noncircular Pulley-Spring Mechanism}, journal = {Journal of Mechanisms and Robotics}, volume = {6}, number = {4}, year = {2014}, pages = {041009}, publisher = {American Society of Mechanical Engineers}, author = {Kim, Bongsu and Deshpande, Ashish D.} } @inbook {deshpande2014development, title = {Development of an Anatomically Correct Testbed (ACT) Hand}, booktitle = {The Human Hand as an Inspiration for Robot Hand Development}, year = {2014}, pages = {453{\textendash}475}, publisher = {Springer}, organization = {Springer}, author = {Deshpande, Ashish D. and Matsuoka, Yoky} } @conference {chen2014experimental, title = {Experimental characterization of Bowden cable friction}, booktitle = {Robotics and Automation (ICRA), 2014 IEEE International Conference on}, year = {2014}, pages = {5927{\textendash}5933}, publisher = {IEEE}, organization = {IEEE}, author = {Chen, Dongyang and Yun, Youngmok and Deshpande, Ashish D.} } @conference {Kim:DSCC:2014, title = {Impedance Control Based on a Position Sensor in a Rehabilitation Robot}, booktitle = {ASME Dynamic Systems and Control Conference (DSCC)}, year = {2014}, author = {Kim, Bongsu and Rodot, Aurelien and Deshpande, A.D.} } @article {Kim:WeRob:2014, title = {Mechanical Design of A Wearable Robot for Upper Body Rehabilitation}, journal = {International Workshop on Wearable Robotics (WeRob)}, year = {2014}, author = {Kim, Bongsu and Deshpande, Ashish D.} } @article {yun2014statistical, title = {Statistical method for prediction of gait kinematics with Gaussian process regression}, journal = {Journal of Biomechanics}, volume = {47}, number = {1}, year = {2014}, pages = {186{\textendash}192}, publisher = {Elsevier}, author = {Yun, Youngmok and Kim, Hyun-Chul and Shin, Sung Yul and Lee, Junwon and Deshpande, Ashish D. and Kim, Changhwan} } @conference {yun2013accurate, title = {Accurate, robust, and real-time estimation of finger pose with a motion capture system}, booktitle = {Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on}, year = {2013}, pages = {1626{\textendash}1631}, publisher = {IEEE}, organization = {IEEE}, author = {Yun, Youngmok and Agarwal, Priyanshu and Deshpande, Ashish D.} } @article {deshpande2013control, title = {Control strategies for the index finger of a tendon-driven hand}, journal = {The International Journal of Robotics Research}, volume = {32}, number = {1}, year = {2013}, pages = {115{\textendash}128}, publisher = {SAGE Publications}, author = {Deshpande, Ashish D. and Ko, Jonathan and Fox, Dieter and Matsuoka, Yoky} } @conference {Agarwal:ASB:2013, title = {Integration of Musculoskeletal Analysis with Engineering Design for Virtual Prototyping of Exoskeletons}, booktitle = {American Society of Biomechanics}, year = {2013}, author = {Agarwal, Priyanshu and Kuo, Pei-Hsin and Neptune, Richard and Deshpande, Ashish D.} } @conference {agarwal2013kinematics, title = {Kinematics and Dynamics of a Biologically Inspired Index Finger Exoskeleton}, booktitle = {ASME 2013 Dynamic Systems and Control Conference}, year = {2013}, pages = {V002T28A001{\textendash}V002T28A001}, publisher = {American Society of Mechanical Engineers}, organization = {American Society of Mechanical Engineers}, author = {Agarwal, Priyanshu and Hechanova, Arnold and Deshpande, Ashish D.} } @article {deshpande2013mechanisms, title = {Mechanisms of the anatomically correct testbed hand}, journal = {Mechatronics, IEEE/ASME Transactions on}, volume = {18}, number = {1}, year = {2013}, pages = {238{\textendash}250}, publisher = {IEEE}, author = {Deshpande, Ashish D. and Xu, Zhe and Weghe, Michael J Vande and Brown, Benjamin H and Ko, Jonathan and Chang, Lillian Y and Wilkinson, David D and Bidic, Sean M and Matsuoka, Yoky} } @conference {kuo2013novel, title = {Novel design of a passive variable stiffness joint mechanism: Inspiration from biomechanics of hand joints}, booktitle = {ASME 2013 Dynamic Systems and Control Conference}, year = {2013}, pages = {V002T28A003{\textendash}V002T28A003}, publisher = {American Society of Mechanical Engineers}, organization = {American Society of Mechanical Engineers}, author = {Kuo, Pei-Hsin and Deshpande, Ashish D.} } @conference {agarwal2013novel, title = {A novel framework for virtual prototyping of rehabilitation exoskeletons}, booktitle = {Rehabilitation Robotics (ICORR), 2013 IEEE International Conference on}, year = {2013}, pages = {1{\textendash}6}, publisher = {IEEE}, organization = {IEEE}, author = {Agarwal, Priyanshu and Kuo, Pei-Hsin and Neptune, Richard and Deshpande, Ashish D.} } @conference {Yun:ASB:2013, title = {Statistical Functional Mapping From Body Parameters to Gait Kinematics}, booktitle = {American Society of Biomechanics}, year = {2013}, author = {Yun, Youngmok and Deshpande, Ashish D.} } @conference {Yun:DW:2013, title = {Synthesis of Gait Kinematics Using a Database}, booktitle = {Dynamic Walking}, year = {2013}, author = {Yun, Youngmok and Deshpande, Ashish D.} } @article {deshpande2012contributions, title = {Contributions of intrinsic visco-elastic torques during planar index finger and wrist movements}, journal = {Biomedical Engineering, IEEE Transactions on}, volume = {59}, number = {2}, year = {2012}, pages = {586{\textendash}594}, publisher = {IEEE}, author = {Deshpande, Ashish D. and Gialias, Nick and Matsuoka, Yoky} } @conference {rao2012effects, title = {Effects of moment arm variations on the joint stiffness characteristics of a musculo-tendon driven joint}, booktitle = {ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference}, year = {2012}, pages = {473{\textendash}482}, publisher = {American Society of Mechanical Engineers}, organization = {American Society of Mechanical Engineers}, author = {Rao, Prashant and Deshpande, Ashish D.} } @article {kuo2012muscle, title = {Muscle-tendon units provide limited contributions to the passive stiffness of the index finger metacarpophalangeal joint}, journal = {Journal of biomechanics}, volume = {45}, number = {15}, year = {2012}, pages = {2531{\textendash}2538}, publisher = {Elsevier}, author = {Kuo, Pei-Hsin and Deshpande, Ashish D.} } @conference {kuo2011design, title = {Design of a motor-driven mechanism to conduct experiments to determine the passive joint properties of the human index finger}, booktitle = {ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, year = {2011}, pages = {615{\textendash}622}, publisher = {American Society of Mechanical Engineers}, organization = {American Society of Mechanical Engineers}, author = {Kuo, Pei-Hsin and Hayes, Jerod and Deshpande, Ashish D.} } @conference {Kuo:ASB:2011, title = {Effects of Variations in Velocity on Viscoelastic Behaviour in the Metacarpophalangeal (MCP) Joint of the Human Hand}, booktitle = {In Proceedings of American Society of Biomechanics}, year = {2011}, author = {Kuo, Pei-Hsin and Deshpande, Ashish D.} } @article {deshpande2010acquiring, title = {Acquiring variable moment arms for index finger using a robotic testbed}, journal = {Biomedical Engineering, IEEE Transactions on}, volume = {57}, number = {8}, year = {2010}, pages = {2034{\textendash}2044}, publisher = {IEEE}, author = {Deshpande, Ashish D. and Balasubramanian, Ravi and Ko, Jonathan and Matsuoka, Yoky} } @conference {kuo2010contribution, title = {Contribution of passive properties of muscle-tendon units to the metacarpophalangeal joint torque of the index finger}, booktitle = {Biomedical Robotics and Biomechatronics (BioRob), 2010 3rd IEEE RAS and EMBS International Conference on}, year = {2010}, pages = {288{\textendash}294}, publisher = {IEEE}, organization = {IEEE}, author = {Kuo, Pei-Hsin and Deshpande, Ashish D.} } @conference {deshpande2009act, title = {ACT hand finger control: muscle and joint torque control strategies}, booktitle = {IEEE International Conference on Robotics and Automation}, year = {2009}, author = {Deshpande, Ashish D. and Ko, Jonathan and Fox, Dieter and Matsuoka, Yoky} } @article {deshpande2009methodology, title = {A methodology for design and analysis of cooperative behaviors with mobile robots}, journal = {Autonomous Robots}, volume = {27}, number = {3}, year = {2009}, pages = {261{\textendash}276}, publisher = {Springer}, author = {Deshpande, Ashish D. and Luntz, Jonathan E.} } @conference {deshpande2008human, title = {Human motion modeling with a robotics method: analysis of a person riding a bus}, booktitle = {ASME 2008 Dynamic Systems and Control Conference}, year = {2008}, pages = {647{\textendash}652}, publisher = {American Society of Mechanical Engineers}, organization = {American Society of Mechanical Engineers}, author = {Deshpande, Ashish D. and Luntz, Jonathan E.} } @conference {deshpande2008understanding, title = {Understanding variable moment arms for the index finger MCP joints through the ACT hand}, booktitle = {Biomedical Robotics and Biomechatronics, 2008. BioRob 2008. 2nd IEEE RAS \& EMBS International Conference on}, year = {2008}, pages = {776{\textendash}782}, publisher = {IEEE}, organization = {IEEE}, author = {Deshpande, Ashish D. and Balasubramanian, Ravi and Lin, Ralph and Dellon, Brian and Matsuoka, Yoky} } @article {deshpande2007behaviors, title = {Behaviors for physical cooperation between robots for mobility improvement}, journal = {Autonomous Robots}, volume = {23}, number = {4}, year = {2007}, pages = {259{\textendash}274}, publisher = {Springer}, author = {Deshpande, Ashish D. and Luntz, Jonathan E.} } @conference {deshpande2007control, title = {Control strategies and design guidelines for planar latch-less metamorphic robots based on analysis of dynamics}, booktitle = {Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on}, year = {2007}, pages = {4089{\textendash}4095}, publisher = {IEEE}, organization = {IEEE}, author = {Deshpande, Ashish D. and Srinivasa, Siddhartha S. and Pillai, Padmanabhan} } @conference {deshpande2007method, title = {A method to characterize and exploit actuation redundancy in mobility and manipulation}, booktitle = {Intelligent Robots and Systems, 2007. IROS 2007. IEEE/RSJ International Conference on}, year = {2007}, pages = {3515{\textendash}3521}, publisher = {IEEE}, organization = {IEEE}, author = {Deshpande, Ashish D. and Luntz, Jonathan E.} } @conference {deshpande2007methodology, title = {A methodology for kinematics and dynamics analysis of robotic systems internal actuation}, booktitle = {ASME 2007 International Mechanical Engineering Congress and Exposition}, year = {2007}, pages = {1361{\textendash}1367}, publisher = {American Society of Mechanical Engineers}, organization = {American Society of Mechanical Engineers}, author = {Deshpande, Ashish D. and Luntz, Jonathan E.} } @conference {deshpande2006behaviors, title = {Behaviors for Physical Cooperation Between Robots for Mobility Improvement: Hardware Results and Use of Dynamics}, booktitle = {Intelligent Robots and Systems, 2006 IEEE/RSJ International Conference on}, year = {2006}, pages = {2212{\textendash}2218}, publisher = {IEEE}, organization = {IEEE}, author = {Deshpande, Ashish D. and Luntz, Jonathan E.} } @conference {Deshpande-RSS-06, title = {Development of Methodology for Design and Analysis of Physically Cooperating Robot and Applications to Other Robotic Systems}, booktitle = {Proceedings of Robotics: Science and Systems}, year = {2006}, month = {August}, address = {Philadelphia, USA}, author = {Deshpande, Ashish D. and Luntz, Jonathan E.} } @article {Deshpande:AIEDAM:2006, title = {Intelligent Strategies for the Application of the Constraint Dominance Methods: Demonstration with Linear Motor Design Problem}, journal = {Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AIEDAM), Special Issue on Constraints and Design}, volume = {20}, year = {2006}, pages = {383{\textendash}397}, author = {Deshpande, Ashish D. and Rinderle, James R.} } @article {deshpande2006unified, title = {A unified framework to represent physically cooperating mobile robots and other robotic systems}, journal = {Robotics Science and System}, year = {2006}, author = {Deshpande, Ashish D. and Luntz, Jonathan E.} } @conference {Rinderle2003, title = {Constraint Dominance Determination Methods}, booktitle = {ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference}, year = {2003}, pages = {553{\textendash}563}, publisher = {American Society of Mechanical Engineers}, organization = {American Society of Mechanical Engineers}, author = {Rinderle, James R. and Deshpande, Ashish D.} } @conference {Deshpande2003b, title = {Constraint Dominance Methods Applied to the Design of a Linear Synchronous Motor}, booktitle = {International Design Engineering Technical Conference}, year = {2003}, author = {Deshpande, Ashish D. and Rinderle, James R.} } @conference {Deshpande2003a, title = {Decentralized control for a team of physically cooperating robots}, booktitle = {Intelligent Robots and Systems, 2003.(IROS 2003). Proceedings. 2003 IEEE/RSJ International Conference on}, volume = {2}, year = {2003}, pages = {1757{\textendash}1762}, publisher = {IEEE}, organization = {IEEE}, author = {Deshpande, Ashish D. and Luntz, Jonathan E.} } @conference {Deshpande2003, title = {Enhancing mobility of a group of mobile robots via physical co-operation among the robots}, booktitle = {Proceedings of SPIE conference on unmanned ground vehicle technology V}, year = {2003}, author = {Deshpande, Ashish D. and Luntz, Jonathan E.} }