Inspired by achievements in rehabilitation, motor learning, and neuroscience, therapeutic robots are aiming to provoke neuromotor plasticity and improve recovery after stroke and mobility impairments. Human sensorimotor system is specialized with position and velocity sensory fibers and exhibits variant muscle impedance in accordance with the ongoing task. The virtually interfaced robotic ankle and balance trainer (vi-RABT) was introduced as a cost-effective platform-based rehabilitation robot to improve overall ankle / balance strength, mobility and control. This study is the first step toward assistive / resistive ankle rehabilitation using vi-RABT. We have implemented a task-dependent anisotropic impedance controller into the 2-DOF ankle rehabilitation robot. An objective virtual Maze game is developed. The controller is specifically designed for the Maze workspace; and exhibits elastic or pure viscos properties in compliant with the subject's direction of movement. Early results on two human subjects are presented.

Each year in the US, 628,000 people suffer an ankle sprain, and 795,000 suffer a new or recurrent stroke. Due to improved survival rates after stroke, significant increases in stroke population are projected by 2030. So far, there is no cost-effective robotic ankle/balance trainer in the market. In this paper, we present the Virtually-Interfaced Robotic Ankle and Balance Trainer (vi-RABT), a low-cost robotic system that will improve overall ankle / balance strength, mobility and control. The system is equipped with 2 degrees of freedom (DOF) controlled actuation along with complete means of force and angular measurements. The preliminary results on a single robotic footplate confirm the system design. The system will be used for measurement of ankle kinematics, ankle kinetics and balance function, as well as for retraining motor control and strength of the ankle during plantarflexion / dorsiflexion (PF/DF), ankle inversion / eversion (IN/EV) and circumduction motions.

Design and control of an active knee rehabilitation orthotic system called ANdROS that was designed as a wearable and portable gait rehabilitation tool is presented. A corrective force field that reinforces a desired gait pattern is applied to the patient's impaired leg around the knee joint via an impedance controlled exoskeleton. The impedance controller is synchronized with the patient's walking phase which is estimated from the kinematic measurements of the healthy leg. The performance of the controller is evaluated through bench-testing.

The Robotic Gait Rehabilitation (RGR) Trainer, was designed and built to target secondary gait deviations in patients post - stroke. Using an impedance control strategy and a linear electromagnetic actuator, the device applies a force field to control pelvic obliquity through an orthopedic brace while the patient ambulates on treadmill. Healthy human subject testing confirmed efficacy of the method to impart significant gait restoration forces as a response to abnormal pelvic obliquity (hip hiking). This novel approach to application of force fields using endpoint impedance controlled linear actuators takes into account soft tissue compliance.

A newly developed hand rehabilitation system is presented that combines robotics and interactive gaming to facilitate repetitive performance of task specific exercises for patients recovering from neurological motor deficits. A two degree of freedom robotic interface allows coordinated motions of the forearm and the hand (pronation/supination and grasp/release, respectively). It is driven by two novel Electro-Rheological Fluid based hydraulic actuators. Tests were conducted to characterize these actuators, and feed-forward controllers were developed for their force/torque control. A virtual reality environment (maze game) was developed in which the robot applies force fields to the user as the user navigates the environment, forming a haptic interface between the patient and the game.

Magnetic Resonance Imaging (MRI) guided nanorobotic systems that could perform diagnostic, curative and reconstructive treatments in the human body at the cellular and sub-cellular level in a controllable manner have recently been proposed. The concept of a MRI-guided nanorobotic system is based on the use of a MRI scanner to induce the required external driving forces to guide magnetic nanocapsules to a specific target. However, the maximum magnetic gradient specifications of existing clinical MRI systems are not capable of driving superparamagnetic nanocapsules against the blood flow and therefore these MRIs do not allow for navigation. The present paper proposes a way to overcome this critical drawback through the formation of micron size agglomerations where their size can be regulated by external magnetic stimuli. This approach is investigated through modeling of the physics that govern the self-assembly of the nanoparticles. Additionally a computational tool has been developed that incorporates the derived models and performs simulation, visualization and post-processing analysis. Preliminary simulation results demonstrate that external magnetic field causes aggregation of nanoparticles while they flow in the vessel. This is a promising result -in accordance with similar experimental results- and encourages further investigation on the nanoparticle based self-assembly structures for use in nanorobotic drug delivery.

In this paper the virtual reality augmented cycling kit (VRACK) a mechatronic rehabilitation system with an interactive virtual environment is presented. It was designed as a modular system that can convert most bicycles in virtual reality (VR) cycles. Novel hardware components embedded with sensors were implemented on a stationary exercise bicycle to monitor physiological and biomechanical parameters of participants while immersing them in a virtual reality simulation providing the user with visual, auditory and haptic feedback. This modular and adaptable system attaches to commercially-available stationary bicycle systems and interfaces with a personal computer for simulation and data acquisition processes. The bicycle system includes novel handle bars based on hydraulic pressure sensors and innovative pedals that monitor lower extremity kinetics and kinematics. Parameters monitored by these systems are communicated to a practitioner's interface screen and can be amplified before entering its virtual environment. The first prototype of the system was successful in demonstrating that a modular mechatronic kit can monitor and record kinetic, kinematic and physiologic parameters of riders.

New actuators are greatly demanded today in order to develop magnetic resonance imaging (MRI)-compatible mechatronic systems capable of extended and improved capabilities. They are particularly needed for MRI-guided interventional or rehabilitation procedures. Actuators based on dielectric elastomers, a specific class of electroactive polymers, appear as suitable candidates for new MRI-compatible technologies, due to their intrinsic material properties and working principle. This paper presents the first investigation on the MRI compatibility of a recently developed linear contractile actuator made of a silicone elastomer. The assessed absence of any degradation of both the actuator electromechanical performance in the MRI environment and the quality of images acquired from a phantom demonstrated the MRI compatibility of the actuator. These results suggest the suitability of this soft actuation technology as a possible new entry in the class of MRI compatible mechatronic systems.

The design hypothesis, architectures, and computational modeling of a novel peptide based nanoGripper are presented in this paper. We engineered the alpha-helical coiled coil portion of the yeast transcriptional activator peptide called GCN4 to obtain an environmentally-responsive nanoGripper. The dimeric coiled-coil peptide consists of two identical ~4.5nm long and ~3nm wide polypeptide chains. The actuation mechanism depends on the modification of electrostatic charges along the peptide by varying the pH of the solution resulting in the reversible movement of helices and therefore, creating the motion of a gripper. Using molecular dynamics simulations we showed that pH changes led to a reversible opening of up-to 1.5 nm which is approximately 150 % of the initial separation of the nanoGripper. We also investigated the forces generated by the nanoGripper upon pH actuation. Using a new method based on a modified steered molecular dynamics technique we were able to show that the force output of the nanoGripper is comparable to that generated by ATP-based molecular motors such as myosin and kinesin even though our molecular tweezer is smaller in size to these molecular motors.

This paper presents a novel, smart and portable active knee rehabilitation orthotic device (AKROD) designed to train stroke patients to correct knee hyperextension during stance and stiff-legged gait (defined as reduced knee flexion during swing). The knee brace provides variable damping controlled in ways that foster motor recovery in stroke patients. A resistive, variable damper, electro-rheological fluid (ERF) based component is used to facilitate knee flexion during stance by providing resistance to knee buckling. Furthermore, the knee brace is used to assist in knee control during swing, i.e. to allow patients to achieve adequate knee flexion for toe clearance and adequate knee extension in preparation to heel strike. The detailed design of AKROD, the first prototype built, closed loop control results and initial human testing are presented here

This paper presents a molecular mechanics study using a molecular dynamics software (NAMD) for characterization of molecular elastic joints for bio nanorobotic prototyping. Simple protein-like elastic joints elements for structural links have been carefully studied and simulated to understand the functional limits of each one of them: fibronectin, titin, deca-alanine, fibrillin, Rop and double-helical DNA molecules. We simulated the restoring forces involved under various external mechanical stress to predict the type of force spectra, reversibility, degrees of freedom and irreversible work that may be expected from single-molecule protein manipulation experiments. Their use as elementary molecular components for bio-nanorobotic structures are also simulated and the results discussed

This paper describes the development of an adaptive nonlinear PI torque control for electro-rheological fluid (ERF) based variable resistance brakes that are used in compact and portable rehabilitation devices. The electrorheologic fluid (ERF) brake concepts are introduced and previous work performed with a non-linear PI control on ERFs is tested and analysed. The response of ERF brake systems to this non-linear PI torque control, that utilizes an inverse model, is enhanced through the addition of two key components, a step logic function and an adaptable B-spline based algorithm. The description of each is provided along with tests verifying their effectiveness. In addition, the controller's response to disturbances is provided. The effectiveness of the control is validated through testing on two different electro-rheological fluid based brakes

This work aims to demonstrate the feasibility of using Electro-Rheological Fluid (ERF) actuators in orthotics, creating a new breed of rehabilitation devices. ERFs are fluids that experience dramatic changes in rheological properties, such as viscosity or yield stress, in the presence of an electric field. Using the electrically controlled rheological properties of ERFs, compact actuators with an ability to supply high resistive torques in a controllable and tunable fashion, have been developed. This study involves the design, fabrication and testing of an ERF based knee orthotic device and the innovative ERF actuators it uses. The knee orthotic is achieved through a standard brace design with a polycentric hinge and gear system. Coupled to this are two Flat-Plate ERF actuators, given that name for their characteristic set of parallel flat plates allowing for actuation of the fluid. A full model describing the field dependant torque output of these actuators is presented along with a full detailed description of the device design. The overall knee orthotic system is designed to resist up to 25.4% of an average human knee’s torque abilities and be controlled in real-time. The goal of this work is to provide a much more efficient means of rehabilitation over the average orthotic, while matching the proficiency of rehabilitation machines, all in a smaller, simpler, and more cost efficient design.

Dynamic and kinematic analysis is performed to predict and verify the performance of a new nanoscale biomolecular motor: The Viral Protein Linear (VPL) Motor. The motor is based on a conformational change observed in a family of viral envelope proteins when subjected to a changing pH environment. The conformational change produces a motion of about 10 nm, making the VPL a basic linear actuator which can be further interfaced with other organic/inorganic nanoscale components such as DNA actuators and carbon nanotubes. The proteins used in the motor are subjected to Molecular Dynamics simulation using the software called CHARMm (Chemistry at Harvard Molecular Mechanics). The results of dynamics are further verified by performing a set of kinematic simulations using direct and inverse kinematics methods.

Force-feedback mechanisms have been designed to simplify and enhance the human-vehicle interface. The increase in secondary controls within vehicle cockpits has created a desire for a simpler, more efficient human-vehicle interface. By consolidating various controls into a single, haptic feedback control device, information can be transmitted to the operator, without requiring the driver's visual attention. In this work, the experimental closed loop torque control of electro-rheological fluids (ERF) based actuators for haptic application is performed. ERFs are liquids that respond mechanically to electric fields by changing their properties, such as viscosity and shear stress, electroactively. Using the electrically controlled rheological properties of ERFs, we developed actuators for haptic devices that can resist human operator forces in a controlled and tunable fashion. In this study, the ERF actuator analytical model is derived and experimentally verified and accurate closed loop torque control is experimentally achieved using a non-linear proportional integral controller with a feed-forward loop.

In this paper the workspace optimization of translational 3-UPU parallel platforms with prismatic and universal joint constraints is performed. The workspace is parameterized using two design parameters, which are the prismatic joint stroke and the difference between the distances of the center to one of the corners of the triangular plate of the base and of the moving platform. For a large range of values for these design parameters the workspace of the corresponding 3-UPU platforms is calculated. This workspace is called the constrained workspace. For each design of the constrained workspace, three performance indices are calculated: 1) the workspace volume; 2) the average of the inverse of the condition number; and 3) a global condition index which is a combination of the other two performance indices. Plots of each performance index as a function of the two design parameters are generated and optimal values for these design parameters are determined. Finally, for the optimal design, it is shown that by introducing limits to the angles of the universal joints axis, the isotropy of the parallel platform is improved.

This research studied the optimal design of shape memory alloy (SMA) muscle wire bundle actuators. Current literature describes the use of multiple muscle wires placed in parallel to increase the lifting capabilities of an SMA actuator, which however, is limited to wires of like-diameter. A constrained optimization problem was formulated, with constraints on the maximum number of wires, voltage applied, and SMA bundle length and cross-sectional area, that explored the use of several different diameter wires for the development of an optimal SMA bundle actuator that will be able to apply maximum force. As a case study, the optimal design of SMA bundle actuators for the Rutgers robotic hand is presented.

In this paper, the application of rapid prototyping in fabricating nonassembly robotic systems is presented. Using the stereolithography apparatus SLA 190 of the Department of Mechanical and Aerospace Engineering of Rutgers University, and the selective laser sintering Sinterstation 2000 of DTM Corporation of Austin, TX, prototypes of mechanical joints were fabricated experimentally. The designs of these component joints were then used to fabricate the articulated structure of experimental prototypes for two robotic systems: (1) a three-legged parallel manipulator; (2) a four degree of freedom finger of a five-fingered robotic hand.

Describes the objectives of a project, which are to design artificial limbs that are lightweight, compact and dexterous, that mimic human anatomy and maintain a high lifting capability. The key to satisfying these objectives is the use of shape memory alloy (SMA) artificial muscles as actuators. A general methodology to find the placement of SMA wires to achieve desired ranges of motion is presented. Two experimental prototypes, emulating human skeletal structures that are actuated by SMA artificial muscles are described in detail.

The problem of achieving high accuracy positioning of a medical robot is studied. The Northeast Proton Therapy Center, at the Massachusetts General Hospital, is a new cancer research and treatment facility. A major component of the center is a robotic patient positioning system that will carry and position patients in a proton beam. The desired positioning accuracy of the robot is less than 0.5 mm. However, various sources of errors in the robot such as assembly errors or flexible deformation of the robot links result in big end-effector positioning errors. It is important to know these end-effector errors as a function of the robot joint variables and patient weight, to be able to compensate them using the manipulator controller. A multi-layer neural network is proposed to identify the robot positioning errors. The neural network is trained using the Levenberg-Marquardt method. Simulations and experimental results demonstrate the validity of the neural network.

A systematic methodology to calculate the end-effector position and orientation errors of a robotic manipulator is presented. The method treats the physical error sources in a unified manner during the system's design so that the effect they have on the end-effector positioning accuracy can be compared and the dominant sources identified. Based on this methodology, a computer program has been developed that can perform the error analysis on any serial link manipulator. This methodology and the software are applied here to the error analysis of a six degree of freedom high performance medical manipulator, for positioning in proton therapy.

The problem of impact dynamics of Space robotic systems that consist of a rigid manipulator supported by a flexible deployable structure is addressed. Due to joint back-drivability and the dynamic coupling between the manipulator and its supporting structure, unknown motion of the system occurs after it makes impulsive contact with the environment. A method that uses the system's dynamic model is proposed to estimate the motion of the system after impact. This method which can be used to find ways to minimize the impact effect and vibrations of the supporting structure due to impact, is verified experimentally using the MIT Vehicle Emulation System (VES II). The experimental results show that the impact force and the system motion after impact can be reduced if the manipulator configuration prior to impact and the controller gains are properly selected.

The problem of the end-point control of long reach manipulator systems, consisting of a dexterous manipulator carried by deployable structures, is addressed. Such systems can be important where a manipulator must perform a task in a difficult to reach location. Power line maintenance systems and the Space Station Freedom's external maintenance robot are examples. Their supporting deployable structures can exhibit substantial vibrations, making the system very difficult to control. Here, a sensor based control algorithm, called inferred end-point control is proposed. Simulation and experimental results show that it yields stable and accurate manipulator end-effector positioning control despite of vibrations of the system's supporting structure using easily obtained strain measurements.

This analytic and experimental study proposes a control algorithm based on Jacobian control for coordinated position and force control for autonomous multi-limbed mobile robotic systems. The technique is called coordinated Jacobian transpose control, or CJTC. Such position/force control algorithms will be required if future robotic systems are to operate effectively in unstructured environments. Generalized control variables, GCV's, express in a consistent and coordinated manner the desired behavior of the forces exerted by the multi-limbed robot on the environment and a system's motions. The effectiveness of this algorithm is demonstrated in simulation and laboratory experiments on a climbing system.>