@article {1699, title = {Disturbance observer-based force estimation for haptic feedback}, journal = {ASME Journal of Dynamic Systems, Measurement and Control}, volume = {133}, year = {2010}, month = {12/2010}, pages = {014505-1--014505-4}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/Gupta_O\%27Malley_2011_JDSMC_dist_obs_PRESS.pdf}, author = {Abhishek Gupta and Marcia K. O{\textquoteright}Malley} } @article {080611080561, title = {Design, control and performance of RiceWrist: A force feedback wrist exoskeleton for rehabilitation and training}, journal = {International Journal of Robotics Research}, volume = {27}, number = {2}, year = {2008}, note = {

Feedback wrist exoskeleton;Neurological injuries;

}, pages = {233 - 251}, abstract = {

This paper presents the design, control and performance of a high fidelity four degree-of-freedom wrist exoskeleton robot, RiceWrist, for training and rehabilitation. The RiceWrist is intended to provide kinesthetic feedback during the training of motor skills or rehabilitation of reaching movements. Motivation for such applications is based on findings that show robot-assisted physical therapy aids in the rehabilitation process following neurological injuries. The exoskeleton device accommodates forearm supination and pronation, wrist flexion and extension and radial and ulnar deviation in a compact parallel mechanism design with low friction, zero backlash and high stiffness. As compared to other exoskeleton devices, the RiceWrist allows easy measurement of human joint angles and independent kinesthetic feedback to individual human joints. In this paper, joint-space as well as task-space position controllers and an impedance-based force controller for the device are presented. The kinematic performance of the device is characterized in terms of its workspace, singularities, manipulability, backlash and backdrivability. The dynamic performance of RiceWrist is characterized in terms of motor torque output, joint friction, step responses, behavior under closed loop set-point and trajectory tracking control and display of virtual walls. The device is singularity-free, encompasses most of the natural workspace of the human joints and exhibits low friction, zero-backlash and high manipulability, which are kinematic properties that characterize a high-quality impedance display device. In addition, the device displays fast, accurate response under position control that matches human actuation bandwidth and the capability to display sufficiently hard contact with little coupling between controlled degrees-of-freedom.

}, keywords = {Control systems, Degrees of freedom (mechanics), Feedback, Neurology, Physical therapy, Systems analysis}, url = {http://dx.doi.org/10.1177/0278364907084261}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/48-IJRR-Feb-2008-small.pdf}, author = {Abhishek Gupta and O{\textquoteright}Malley, M.K. and Volkan Patoglu and Burgar, Charles} } @inbook {105, title = {Haptic Interfaces}, booktitle = {HCI: Beyond the GUI}, year = {2008}, pages = {25-74}, publisher = {Morgan-Kaufman Publisher}, organization = {Morgan-Kaufman Publisher}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/105-Kortum02Gupta-O\%27Malley.pdf}, author = {O{\textquoteright}Malley, M.K. and Abhishek Gupta} } @proceedings {082211289622, title = {Disturbance observer based closed loop force control for haptic feedback}, volume = {9 PART B}, year = {2007}, note = {

Disturbance observer;Haptic feedback;Pseudostatic interactions;

}, pages = {1343 - 1349}, address = {Seattle, WA, United States}, abstract = {

Most commonly used impedance-type haptic interfaces employ open-loop force control under the assumption of pseudostatic interactions. Advanced force control in such interfaces can increase simulation fidelity through improvement of the transparency of the device, and can further improve robustness. However, closed loop force-feedback is limited both due to the bandwidth limitations of force sensing and the associated cost of force sensors required for its implementation. In this paper, we propose the use of a nonlinear disturbance observer for estimation of contact forces during haptic interactions. This approach circumvents the traditional drawbacks of force sensing while exhibiting the advantages of closed-loop force control in haptic devices. The feedback of contact force information further enables implementation of advanced robot force control techniques such as robust hybrid impedance and admittance control. Simulation and experimental results, utilizing a PHANToM Premium 1.0A haptic interface, are presented to demonstrate the efficacy of the proposed approach. Copyright {\textcopyright} 2007 by ASME.

}, keywords = {Computer simulation, Force control, Haptic interfaces, Robotics, Robustness (control systems)}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/50-gupta-imece07.pdf}, author = {Abhishek Gupta and O{\textquoteright}Malley, M.K. and Volkan Patoglu} } @inbook {106, title = {Robotic Exoskeletons for Upper Extremity Rehabilitation}, booktitle = {Rehabilitation Robotics}, year = {2007}, pages = {371-396}, publisher = {I-Tech Education and Publishing}, organization = {I-Tech Education and Publishing}, address = {Vienna, Austria}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/106-robotic_exoskeletons_Gupta_O\%27Malley.pdf}, author = {Abhishek Gupta and O{\textquoteright}Malley, M.K.} } @article {071210493824, title = {Design of a haptic arm exoskeleton for training and rehabilitation}, journal = {IEEE/ASME Transactions on Mechatronics}, volume = {11}, number = {3}, year = {2006}, note = {

Arm exoskeletons;Apparent inertia;Design methodology;

}, pages = {280 - 289}, abstract = {

A high-quality haptic interface is typically characterized by low apparent inertia and damping, high structural stiffness, minimal backlash, and absence of mechanical singularities in the workspace. In addition to these specifications, exoskeleton haptic interface design involves consideration of space and weight limitations, workspace requirements, and the kinematic constraints placed on the device by the human arm. These constraints impose conflicting design requirements on the engineer attempting to design an arm exoskeleton. In this paper, the authors present a detailed review of the requirements and constraints that are involved in the design of a high-quality haptic arm exoskeleton. In this context, the design of a five-degree-of-freedom haptic arm exoskeleton for training and rehabilitation in virtual environments is presented. The device is capable of providing kinesthetic feedback to the joints of the lower arm and wrist of the operator, and will be used in future work for robot-assisted rehabilitation and training. Motivation for such applications is based on findings that show robot-assisted physical therapy aids in the rehabilitation process following neurological injuries. As a training tool, the device provides a means to implement flexible, repeatable, and safe training methodologies. \© 2006 IEEE.

}, keywords = {Damping, Degrees of freedom (mechanics), Joints (anatomy), Patient rehabilitation, Robot applications, Sensory perception, Stiffness}, url = {http://dx.doi.org/10.1109/TMECH.2006.875558}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/47-IEEEASME_HapticArmExoskeleton.pdf}, author = {Abhishek Gupta and O{\textquoteright}Malley, M.K.} } @proceedings {072310640980, title = {The RiceWrist: A distal upper extremity rehabilitation robot for stroke therapy}, year = {2006}, note = {

Mirror Image Movement Enabler (MIME) system;Rehabilitation robot;Robotic therapy;

}, month = {11/2006}, pages = {10 -}, publisher = {ASME}, address = {Chicago, IL, United States}, abstract = {

This paper presents the design and kinematics of a four degree-of-freedom upper extremity rehabilitation robot for stroke therapy, to be used in conjunction with the Mirror Image Movement Enabler (MIME) system. The RiceWrist is intended to provide robotic therapy via force-feedback during range-of-motion tasks. The exoskeleton device accommodates forearm supination and pronation, wrist flexion and extension, and radial and ulnar deviation in a compact design with low friction and backlash. Joint range of motion and torque output of the electricmotor driven device is matched to human capabilities. The paper describes the design of the device, along with three control modes that allow for various methods of interaction between the patient and the robotic device. Passive, triggered, and active-constrained modes, such as those developed for MIME, allow for therapist control of therapy protocols based on patient capability and progress. Also presented is the graphical user interface for therapist control of the interactions modes of the RiceWrist, basic experimental protocol, and preliminary experimental results. Copyright {\textcopyright} 2006 by ASME.

}, keywords = {Degrees of freedom (mechanics), Graphical user interfaces, Human rehabilitation equipment, Patient treatment}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/46-00\%20-\%20IMECE2006-16103-O\%27Malley.pdf}, author = {O{\textquoteright}Malley, M.K. and Alan Sledd and Abhishek Gupta and Volkan Patoglu and Joel C. Huegel and Burgar, Charles} } @article {06199869875, title = {Shared control in haptic systems for performance enhancement and training}, journal = {Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME}, volume = {128}, number = {1}, year = {2006}, note = {

Virtual environments;Mass-spring-damper;System dynamics;Shared control;

}, pages = {75 - 85}, chapter = {75}, abstract = {

This paper presents a shared-control interaction paradigm for haptic interface systems, with experimental data from two user studies. Shared control, evolved from its initial telerobotics applications, is adapted as a form of haptic assistance in that the haptic device contributes to execution of a dynamic manual target-hitting task via force commands from an automatic controller. Compared to haptic virtual environments, which merely display the physics of the virtual system, or to passive methods of haptic assistance for performance enhancement based on virtual fixtures, the shared-control approach offers a method for actively demonstrating desired motions during virtual environment interactions. The paper presents a thorough review of the literature related to haptic assistance. In addition, two experiments were conducted to independently verify the efficacy of the shared-control approach for performance enhancement and improved training effectiveness of the task. In the first experiment, shared control is found to be as effective as virtual fixtures for performance enhancement, with both methods resulting in significantly better performance in terms of time between target hits for the manual target-hitting task than sessions where subjects feel only the forces arising from the mass-spring-damper system dynamics. Since shared control is more general than virtual fixtures, this approach may be extremely beneficial for performance enhancement in virtual environments. In terms of training enhancement, shared control and virtual fixtures were no better than practice in an unassisted mode. For manual control tasks, such as the one described in this paper, shared control is beneficial for performance enhancement, but may not be viable for enhancing training effectiveness. Copyright \© 2006 by ASME.

}, keywords = {Control equipment, Damping, Data reduction, Haptic interfaces, Robotics, Robots}, issn = {0022-0434}, doi = {10.1115/1.2168160 }, url = {http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal\&id=JDSMAA000128000001000075000001\&idtype=cvips\&gifs=yes}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/52-00\%20-\%20JDSMC\%20Shared\%20control.pdf}, author = {O{\textquoteright}Malley, M.K. and Abhishek Gupta and Gen, Matthew and Yanfang Li} } @proceedings {072310640927, title = {Vision based force sensing for nanorobotic manipulation}, year = {2006}, note = {

Nanomanipulation;Nanoassembly;

}, pages = {10 -}, address = {Chicago, IL, United States}, abstract = {

Over the last decade, considerable interest has been generated in building and manipulating nanoscale structures. Applications of nanomanipulation include study of nanoparticles, molecules, DNA and viruses, and bottom-up nanoassembly. We propose a Nanomanipulation System using the Zyvex S100 nanomanipulator, -which operates within a scanning electron microscope (SEM), as its primary component. The primary advantage of the S100 setup over standard scanning probe microscopy based nanomanipulators is the ability to see the object during manipulation. Relying on visual feedback alone to control the nanomanipulator is not preferable due to perceptual limitations of depth and contact within the SEM. To improve operator performance over visual feedback alone, an impedance-controlled bilateral teleoperation setup is envisioned. Lack of on-board force sensors on the S100 system is the primary hindrance in the realization of the proposed architecture. In this paper, we present a computer vision based force sensing scheme. The advantages of this sensing strategy include its low cost and lack of requirement of hardware modifications). Force sensing is implemented using an atomic force microscopy (AFM) probe attached to the S100 end-effector. Deformation of the cantilever probe is monitored using a Hough transform based algorithm. These deformations are mapped to corresponding end-effector forces following the Euler-Bernoulli beam mechanics model. The forces thus sensed can be used to provide force-feedback to the operator through a master manipulator. Copyright {\textcopyright} 2006 by ASME.

}, keywords = {Atomic force microscopy, Force measurement, Manipulators, Nanoparticles, Nanotechnology, Scanning electron microscopy}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/49-IMECE2006-15111-Gupta-small.pdf}, author = {Abhishek Gupta and Volkan Patoglu and O{\textquoteright}Malley, M.K.} } @proceedings {05239144488, title = {Design of a haptic arm exoskeleton for training and rehabilitation}, volume = {73}, number = {2 PART B}, year = {2004}, note = {

Haptic arm exoskeleton;Inertia;Structural stiffness;Kinesthetic feedback;

}, pages = {1011 - 1018}, address = {Anaheim, CA, United States}, abstract = {

A high-quality haptic interface is typically characterized by low apparent inertia and damping, high structural stiffness, minimal backlash and absence of mechanical singularities in the workspace. In addition to these specifications, exoskeleton haptic interface design involves consideration of additional parameters and constraints including space and weight limitations, workspace requirements and the kinematic constraints placed on the device by the human arm. In this context, we present the design of a five degree-of-freedom haptic arm exoskeleton for training and rehabilitation in virtual environments. The design of the device, including actuator and sensor selection, is discussed. Limitations of the device that result from the above selections are also presented. The device is capable of providing kinesthetic feedback to the joints of the lower arm and wrist of the operator, and will be used in future work for robot-assisted rehabilitation and training. Copyright {\textcopyright} 2004 by ASME.

}, keywords = {Actuators, Bandwidth, Damping, Degrees of freedom (mechanics), Friction, Human computer interaction, Kinematics, Robotic arms, Robots, Sensors, Stiffness}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/gupta2004asme.pdf}, author = {Abhishek Gupta and O{\textquoteright}Malley, M.K.} } @proceedings {7780496, title = {Passive and active assistance for human performance of a simulated underactuated dynamic task}, year = {2003}, note = {

simulated underactuated dynamic task;machine-mediated training;virtual fixtures;active assist;haptic feedback;visual feedback;

}, pages = {348 - 55}, address = {Los Angeles, CA, USA}, abstract = {

Machine-mediated training of dynamic task completion is typically implemented with passive intervention via virtual fixtures or active assist by means of record and replay strategies. During interaction with a real dynamic system however, the user relies on both visual and haptic feedback real-time in order to elicit desired motions. This work investigates human performance in a Fitts{\textquoteright} type targeting task with an underactuated dynamic system. Performance, in terms of number of hits and between-target tap times, is measured while various passive and active control modes are displayed concurrently with the haptic feedback from the simulated system{\textquoteright}s own dynamic behavior. It Is hypothesized that passive and active assist modes that are implemented during manipulation of simulated underactuated systems could be beneficial in rehabilitation applications. Results indicate that human performance can be improved significantly with the passive and active assist modes

}, keywords = {Haptic interfaces, Virtual reality}, url = {http://dx.doi.org/10.1109/HAPTIC.2003.1191308}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2003HAPTICS.pdf}, author = {O{\textquoteright}Malley, M.K. and Abhishek Gupta} } @proceedings {7971173, title = {Skill transfer in a simulated underactuated dynamic task}, year = {2003}, note = {

underactuated dynamic system;Fitts{\textquoteright} type;skill transfer;haptic feedback;

}, pages = {315 - 20}, address = {Millbrae, CA, USA}, abstract = {

Machine-mediated teaching of dynamic task completion is typically implemented with passive intervention via virtual fixtures or active assist by means of record and replay strategies. During interaction with a real dynamic system however, the user relies on both visual and haptic feedback in order to elicit desired motions. This work investigates skill transfer from assisted to unassisted modes for a Fitts{\textquoteright} type targeting task with an underactuated dynamic system. Performance, in terms of between target tap times, is measured during an unassisted baseline session and during various types of assisted training sessions. It is hypothesized that passive and active assist modes that are implemented during training of a dynamic task could improve skill transfer to a real environment or unassisted simulation of the task. Results indicate that transfer of skill is slight but significant for the assisted training modes

}, keywords = {computer based training, Haptic interfaces, learning (artificial intelligence), Virtual reality}, url = {http://dx.doi.org/10.1109/ROMAN.2003.1251864}, attachments = {https://mahilab.rice.edu/sites/default/files/publications/omalley2003ieeeskilltrans.pdf}, author = {O{\textquoteright}Malley, M.K. and Abhishek Gupta} }