@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 {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.} } @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}} } @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} } @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.} } @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 {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 {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.} } @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 {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.} } @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.} }