This thesis discusses three projects that revolve around the central concept of the control of artificial hands. The first part of the thesis discusses the design of a museum exhibit for the South Florida Science Center that allows the public to control an i-limb Revolution prosthetic hand using electromyograph (EMG) sensors. A custom armature was designed to house the EMG sensors that are used to control the prosthesis. The top arm of the armature utilized a double rocker design for a greater range of motion which allows the display to accommodate arm sizes ranging from small children to large adults. This display became open to the public in March of 2019. The second part of the thesis describes a new concept for a simultaneous multi-object grasp using the Shadow hand robotic hand. This grasp is tested in an experiment that involves grasp and transportation tasks. This experiment also aims to analyze the benefit of soft robotic haptic feedback armband during the grasp and transportation tasks when a simulated break threshold is imposed on the objects. The usefulness of the haptic feedback was further tested with a guess the object task where the subjects had to determine which object was in the hand based solely off the armband. The new grasp synergy was deemed a success as all subjects were able to use the control method effectively with very little initial training. It was also found that the haptic feedback greatly aided in the successfully completing the transportation tasks. The human subjects were asked to rate the haptic feedback after each task, the overall rating for the helpfulness of the haptic feedback was rated as 4.6 out of 5. The final part of the thesis discusses an approach at gaining additional control signals for a dexterous artificial hand using a brain computer interface. This project seeks to investigate three neuromarkers for control which are: mu, xi and alpha. During analysis, the mu rhythm was not seen in our subject but alpha and xi were. Using deep learning approaches at classification, we were able to classify alpha and xi with at least a 90 percent accuracy. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection

The need to lead an independent and fuller life is as much a right of a person with physical disability as any other human being. Driving capabilities of a person with a disability have been assessed and evaluated using qualitative techniques. However, certain inadequacies that arise using qualitative measures can be avoided if the assessment is based on quantitative techniques. The above requirement necessitates the need to devise a method and a system which is focused on the right development of the techniques used in assessing and measuring different capabilities (such as range of motion and force input) of the person with a disability in a detailed manner. This thesis focuses on developing an experimental method which can be adopted as an assessment tool to evaluate different capabilities of a person with a disability. The test bed used for this purpose consists of two independent systems combined together by an interface. They are the six-degree of freedom force reflecting hand controller known as the PHANTOM haptic device [12] and a commercially available adaptive driving control system known as the AEVIT system [15]. The test bed provides compatibility between the PHANTOM and AEVIT which makes it feasible for the PHANTOM to model and control the driving input devices (steering and gas/brake) of the AEVIT system.

The simulation of surgical procedures, in the case of hard tissues such as bone or teeth milling, using a haptic milling surgery simulator requires a haptic device which can provide high stiffness and transparency. To mimic a real milling process of hard tissue, such as for example creating a narrow channel or cavity, the simulator needs to provide force/torque feedback in 5–6 degrees of freedom (DOF). As described in this thesis, research has been performed to develop and optimize a haptic device that can provide high stiffness and force/torque capabilities to facilitate haptic interaction with stiff tissues.  The main contributions of this thesis are: (i) The use of a model-based design methodology for the design of haptic devices.  The proposed methodology is applied to a case study, i.e. the design and optimization of a haptic device based on parallel kinematics. Device requirements were elicited through dialogues with a prospective user from a neurosurgery clinic. In the conceptual design phase, different parallel concepts have been investigated and analyzed based on functional qualities such number of degrees of freedom, workspace size and force/torque capabilities. This analysis led to the selection of a specific 6 DOF kinematic structure for which dimension synthesis was performed including multi-objective optimization followed by control synthesis. Finally, a device prototype was realized and its performance verified. (ii) Optimization of the device for best kinematic and dynamic performance. For optimization, performance indices such as workspace-to-footprint ratio, kinematic isotropy and inertial indices were used. To cope with the problem of non-uniform units in the components of the Jacobian matrix, various normalization techniques were investigated. A new multi-objective optimization function is introduced to define the optimization problem, which is then resolved using multi-objective genetic algorithms. A sensitivity analysis of the performance indices against each design parameter is performed, as a basis for selecting a final set of design parameter values. (iii) A control strategy is investigated to achieve high transparency and stability of the device. The control strategy is based on careful analysis of the dynamics of the haptic device, computed torque feed-forward control and force control based on current feedback. (iv) Finally, experiments both separately in the lab and by using the device in a haptic milling surgery simulator were performed. Results from a face validity study performed in collaboration with orthopedists verify that the new haptic device enables high-performance force and torque feedback for stiff interactions. / QC 20120302

The present thesis is based on three studies that research different aspects of fine texture perception. The goal is to better understand the mechanisms involved in haptic perception of textures below 200 µm, also known as microtextures. Study I was conducted to establish a friction measurement model and relating the friction measurements to perceived coarseness of fine textures. A set of printing papers was used as stimulus material. In Study II an expanded set, including the set of Study I, was used as stimuli in a multidimensional scaling (MDS) experiment of haptic fine texture perception. Through scaling of perceptual attributes and similarities, a three dimensional space was found to best describe the data and the dimensions were interpreted as rough-smooth, thick-thin and distinct-indistinct. In Study III a series of model surfaces were manufactured with a systematically varied sinusoidal pattern, spanning from 300 nm to 80 µm. As in Study II, a similarity experiment was conducted and a two dimensional space was chosen, the dimensions of which were explained well through friction and the wavelength. Together these three studies form a better picture of fine texture perception. The dimensionality found with paper stimuli was very similar to the corresponding spaces for marcrotextures of everyday materials, even though a different perceptual system is used for fine texture perception. Regardless if the information is coded through the spatial or the vibratory sense, the perception does not seem to differ in dimensionality. Further, the largest among the microtextures seem to have been perceived as carrying spatial information. On the systematically varied, rigid, textures, the MDS space did not come out in a similar fashion to those of everyday materials but instead similar to the physical properties that characterizes the change in the textures. It was further found that the participants in Study III successfully discriminated textures with an amplitude of 13 nm from the unwrinkled surfaces. From these studies the main conclusions are (a) haptically measured friction and surface roughness are important contributors to fine texture perception, (b) even at microscales, spatial information is retrieved haptically, probably through vibrations, and (c) persons can haptically discriminate textures at a nanoscale.

Affective haptic research is a rapidly growing field. Today, more smart haptic clothes are being studied and implemented which are aimed to effect its users emotionally. However, they have some limitations. This research intends to improve the existing literature and contribute by involving consumers directly in the design of a smart haptic jacket by adding heat, vibration actuators, and by enhancing portability. In this thesis, we are interested in six basic emotions: love, joy, surprise, anger, sadness, and fear. An online survey was designed and conducted on 92 respondents that gave feedback of what it is expected from an affective haptic jacket. The results of this survey assisted in the general design, and the feedback helped to build a prototype. 86% of the respondents expressed interest in the system and are willing to try it when it is ready. A detailed design architecture is provided along with details on the hardware and software used for the implementation. Finally, the prototype was evaluated on 14 participants using the actual prototype haptic jacket based on a QoE comparison between the absence and the presence of haptic actuation. The proposed system showed improvement over a similar system that is designed for the same purpose.

Affective haptic research is a rapidly growing field. Today, more smart haptic clothes are being studied and implemented which are aimed to effect its users emotionally. However, they have some limitations. This research intends to improve the existing literature and contribute by involving consumers directly in the design of a smart haptic jacket by adding heat, vibration actuators, and by enhancing portability. In this thesis, we are interested in six basic emotions: love, joy, surprise, anger, sadness, and fear. An online survey was designed and conducted on 92 respondents that gave feedback of what it is expected from an affective haptic jacket. The results of this survey assisted in the general design, and the feedback helped to build a prototype. 86% of the respondents expressed interest in the system and are willing to try it when it is ready. A detailed design architecture is provided along with details on the hardware and software used for the implementation. Finally, the prototype was evaluated on 14 participants using the actual prototype haptic jacket based on a QoE comparison between the absence and the presence of haptic actuation. The proposed system showed improvement over a similar system that is designed for the same purpose.

A forest harvester operator is today facing a stressful work environment with a high demand on coordination skills and effectiveness to run the operation with positive economical outcome. The learning phase is very long compared to similar work.The vision for this project was to transform the machine, through intuitive and innovative interface design, into an extension of the operator’s body. In this way it provides higher productivity as well as user friendliness, shorter learning phase and a healthier work situation.This was realized through the use of prior but yet not market available related research. Through market studies, applicable technology already available in other industries was found. The result is a complete seat with controls for a conceptual Gremo harvester realizable in the year 2023.

Haptic applications often employ devices with many degrees of freedom in order to allow the user to have natural movement during human-machine interaction. From the development point of view, the complexity in mechanical dynamics imposes a lot of challenges in modelling the behaviour of the device. Traditional system identification methods for nonlinear systems are often computationally expensive. Moreover, current research on using neural network approaches disconnect the physical device dynamics with the identification process. This thesis proposes a different approach to system identification of complex haptic devices when analytical models are formulated. It organizes the unknowns to be identified based on the governing dynamic equations of the device and reduces the cost of computation. All the experimental work is done with the Freedom 6S, a haptic device with input and feedback in positions and velocities for all 6 degrees of freedom . <br /><br /> Once a symbolic model is developed, a subset of the overall dynamic equations describing selected joint(s) of the haptic robot can be obtained. The advantage of being able to describe the selected joint(s) is that when other non-selected joints are physically fixed or locked up, it mathematically simplifies the subset dynamic equation. Hence, a reduced set of unknowns (e. g. mass, centroid location, inertia, friction, etc) resulting from the simplified subset equation describes the dynamic of the selected joint(s) at a given mechanical orientation of the robot. By studying the subset equations describing the joints, a locking sequence of joints can be determined to minimize the number of unknowns to be determined at a time. All the unknowns of the system can be systematically determined by locking selected joint(s) of the device following this locking sequence. Two system identification methods are proposed: Method of Isolated Joint and Method of Coupling Joints. Simulation results confirm that the latter approach is able to successfully identify the system unknowns of Freedom 6S. Both open-loop experimental tests and close-loop verification comparison between the measured and simulated results are presented. <br /><br /> Once the haptic device is modelled, fuzzy logic is used to address chattering phenomenon common to strong virtual effects. In this work, a virtual wall is used to demonstrate this approach. The fuzzy controller design is discussed and experimental comparison between the performance of using a proportional-derivative gain controller and the designed fuzzy controller is presented. The fuzzy controller is able to outperform the traditional controller, eliminating the need for hardware upgrades for improved haptic performance. Summary of results and conclusions are included along with suggested future work to be done.

A commercial backhoe has been modified for haptic control research at Georgia Tech's Fluid Power and Motion Control Center (FPMC). Electrohydraulic valves and feedback sensors have been retrofitted to the backhoe and interfaced with a haptic joystick through a computerized control system. The resulting system provides force feedback to the hand of the operator as he or she manipulates the bucket with the joystick in Cartesian space. This system has been constructed for use as a platform for ongoing research in the area of haptic controls for the fluid power industry. The work presented herein is divided into seven chapters. The first chapter introduces the haptic backhoe concept and provides some motivation for the project. The second chapter presents the current state of haptics-for-hydraulics research as presented in scientific literature. The third chapter presents kinematic and dynamic modeling of the haptic backhoe components for use both in simulation and control. The fourth chapter presents simulation results from the model derived in the preceeding chapter. The fifth chapter describes the design of the physical system. The sixth chapter presents initial test results of the backhoe moving under closed-loop haptic control. The last chapter describes the current state of the system and suggests several areas for future exploration. It is hoped that the haptic backhoe will continue to serve as a useful research tool for many years into the future.

A ”Haptic servo system” is here understood as a servo system whereforces from a controlled system are fed back to an operator. This thesis workis a design work where the work among other things comprises the choice ofsuitable motors, one for operating the beam and another one for operatingthe steering wheel. Data for the beam and ball are assumed to be known.Data for the feed back torque to the steering wheel is assumed to be specifiedin advance. Two models to represent the human response are suggested. Asimulation study is carried out to show that the system works according tosome specification. The ball and beam process is simulated with hardwarein the loop. The hardware in the loop is a Maxon motor. The motor is usedas the steering wheel and the motor will also propagate the torque feedbackto the operator.The task of the thesis work could then be formulated as: Can a human, withtorque feedback, manually control the ball on the beam without looking atthe ball and the beam?