Design and analysis of a haptic device design for large and fast movements

Haptic devices tend to be kept small as it is easier to achieve a large change of stiffness with a low associated apparent mass. If large movements are required there is a usually a reduction in the quality of the haptic sensations which can be displayed. The typical measure of haptic device performance is impedance-width (z-width) but this does not account for actuator saturation, usable workspace or the ability to do rapid movements. This paper presents the analysis and evaluation of a haptic device design, utilizing a variant of redundant kinematics, sometimes referred to as a macro-micro configuration, intended to allow large and fast movements without loss of impedance-width. A brief mathematical analysis of the design constraints is given and a prototype system is described where the effects of different elements of the control scheme can be examined to better understand the potential benefits and trade-offs in the design. Finally, the performance of the system is evaluated using a Fitts’ Law test and found to compare favourably with similar evaluations of smaller workspace devices

Contributing to VRPN with a new server for haptic devices (ext. version)

This article is an extended version of the poster paper: Cuevas-Rodriguez, M., Gonzalez-Toledo D., Molina-Tanco, L., Reyes-Lecuona A., 2015, November. “Contributing to VRPN with a new server for haptic devices”. In Proceedings of the ACM symposium on Virtual reality software and technology. ACM.http://dx.doi.org/10.1145/2821592.2821639VRPN is a middleware to access Virtual Reality peripherals. VRPN standard distribution supports Geomagic® (formerly Phantom) haptic devices through the now superseded GHOST library. This paper presents VRPN OpenHaptics Server, a contribution to VRPN library that fully reimplements VRPN support of Geomagic Haptic Devices. The implementation is based on the OpenHaptics v3.0 HLAPI layer, which supports all Geomagic Haptic Devices. We present the architecture of the contributed server, a detailed description of the offered API and an analysis of its performance in a set of example scenarios.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Robot Impedance Control and Passivity Analysis with Inner Torque and Velocity Feedback Loops

Impedance control is a well-established technique to control interaction forces in robotics. However, real implementations of impedance control with an inner loop may suffer from several limitations. Although common practice in designing nested control systems is to maximize the bandwidth of the inner loop to improve tracking performance, it may not be the most suitable approach when a certain range of impedance parameters has to be rendered. In particular, it turns out that the viable range of stable stiffness and damping values can be strongly affected by the bandwidth of the inner control loops (e.g. a torque loop) as well as by the filtering and sampling frequency. This paper provides an extensive analysis on how these aspects influence the stability region of impedance parameters as well as the passivity of the system. This will be supported by both simulations and experimental data. Moreover, a methodology for designing joint impedance controllers based on an inner torque loop and a positive velocity feedback loop will be presented. The goal of the velocity feedback is to increase (given the constraints to preserve stability) the bandwidth of the torque loop without the need of a complex controller.Comment: 14 pages in Control Theory and Technology (2016

Exploring affective design for physical controls

Physical controls such as knobs, sliders, and buttons are experiencing a revival as many computing systems progress from personal computing architectures towards ubiquitous computing architectures. We demonstrate a process for measuring and comparing visceral emotional responses of a physical control to performance results of a target acquisition task. In our user study, participants experienced mechanical and rendered friction, inertia, and detent dynamics as they turned a haptic knob towards graphical targets of two different widths and amplitudes. Together, this process and user study provide novel affect- and performance-based design guidance to developers of physical controls for emerging ubiquitous computing environments. Our work bridges extensive human factors work in mechanical systems that peaked in the 1960’s, to contemporary trends, with a goal of integrating mechatronic controls into emerging ubiquitous computing systems. Author Keywords Haptic display, physical control, design process, affect

Investigating the Effectiveness of a Haptic Feedback System to Improve the Gait Speed of Older Adults in Overground Walking

While the use of tactile feedback for modifying gait has recently shown promising results in a number of research studies, there has been little attention given to its ability to effect change in the gait of older adults nor has the effect of the frequency of this feedback been examined. Given the important associations of walking speed with the health of older adults, the goal of this study was to determine if a recently developed haptic feedback system could increase the walking speed of older adults and whether the frequency at which this feedback was provided would have an impact on the results. In order to achieve a faster walking speed, peak thigh extension was selected as a biomechanical surrogate for stride length with vibrotactile haptic feedback being provided to the thighs to increase that parameter and, consequently, increase speed. Further, the influence of the frequency of the feedback on several other gait parameters was also investigated. Ten healthy older adults (68.4 ± 4.1 years) were recruited for this study, in which their peak thigh extension, cadence, normalized stride length, and normalized stride velocity, as well as their coefficients of variation (COV), were compared among six different experimental conditions. The study’s findings demonstrated that when compared to their pretest values, older people using the haptic feedback device had considerably longer peak thigh extensions during both post-tests and feedback walking conditions. The longer stride length made possible by this more extended thigh angle allowed for a corresponding rise in walking velocity. Surprisingly, none of the gait metrics examined were substantially impacted by the feedback’s frequency. In other words, regardless of how frequently the input was given, the haptic feedback device was successful in improving elderly people’s walking abilities. These results indicate the haptic feedback device has the potential to enhance gait speed, stride length, and stride velocity, which are essential elements involved with keeping independence and mobility in older people

Nonlinear Modeling and Control of Driving Interfaces and Continuum Robots for System Performance Gains

With the rise of (semi)autonomous vehicles and continuum robotics technology and applications, there has been an increasing interest in controller and haptic interface designs. The presence of nonlinearities in the vehicle dynamics is the main challenge in the selection of control algorithms for real-time regulation and tracking of (semi)autonomous vehicles. Moreover, control of continuum structures with infinite dimensions proves to be difficult due to their complex dynamics plus the soft and flexible nature of the manipulator body. The trajectory tracking and control of automobile and robotic systems requires control algorithms that can effectively deal with the nonlinearities of the system without the need for approximation, modeling uncertainties, and input disturbances. Control strategies based on a linearized model are often inadequate in meeting precise performance requirements. To cope with these challenges, one must consider nonlinear techniques. Nonlinear control systems provide tools and methodologies for enabling the design and realization of (semi)autonomous vehicle and continuum robots with extended specifications based on the operational mission profiles. This dissertation provides an insight into various nonlinear controllers developed for (semi)autonomous vehicles and continuum robots as a guideline for future applications in the automobile and soft robotics field. A comprehensive assessment of the approaches and control strategies, as well as insight into the future areas of research in this field, are presented.First, two vehicle haptic interfaces, including a robotic grip and a joystick, both of which are accompanied by nonlinear sliding mode control, have been developed and studied on a steer-by-wire platform integrated with a virtual reality driving environment. An operator-in-the-loop evaluation that included 30 human test subjects was used to investigate these haptic steering interfaces over a prescribed series of driving maneuvers through real time data logging and post-test questionnaires. A conventional steering wheel with a robust sliding mode controller was used for all the driving events for comparison. Test subjects operated these interfaces for a given track comprised of a double lane-change maneuver and a country road driving event. Subjective and objective results demonstrate that the driver’s experience can be enhanced up to 75.3% with a robotic steering input when compared to the traditional steering wheel during extreme maneuvers such as high-speed driving and sharp turn (e.g., hairpin turn) passing. Second, a cellphone-inspired portable human-machine-interface (HMI) that incorporated the directional control of the vehicle as well as the brake and throttle functionality into a single holistic device will be presented. A nonlinear adaptive control technique and an optimal control approach based on driver intent were also proposed to accompany the mechatronic system for combined longitudinal and lateral vehicle guidance. Assisting the disabled drivers by excluding extensive arm and leg movements ergonomically, the device has been tested in a driving simulator platform. Human test subjects evaluated the mechatronic system with various control configurations through obstacle avoidance and city road driving test, and a conventional set of steering wheel and pedals were also utilized for comparison. Subjective and objective results from the tests demonstrate that the mobile driving interface with the proposed control scheme can enhance the driver’s performance by up to 55.8% when compared to the traditional driving system during aggressive maneuvers. The system’s superior performance during certain vehicle maneuvers and approval received from the participants demonstrated its potential as an alternative driving adaptation for disabled drivers. Third, a novel strategy is designed for trajectory control of a multi-section continuum robot in three-dimensional space to achieve accurate orientation, curvature, and section length tracking. The formulation connects the continuum manipulator dynamic behavior to a virtual discrete-jointed robot whose degrees of freedom are directly mapped to those of a continuum robot section under the hypothesis of constant curvature. Based on this connection, a computed torque control architecture is developed for the virtual robot, for which inverse kinematics and dynamic equations are constructed and exploited, with appropriate transformations developed for implementation on the continuum robot. The control algorithm is validated in a realistic simulation and implemented on a six degree-of-freedom two-section OctArm continuum manipulator. Both simulation and experimental results show that the proposed method could manage simultaneous extension/contraction, bending, and torsion actions on multi-section continuum robots with decent tracking performance (e.g. steady state arc length and curvature tracking error of 3.3mm and 130mm-1, respectively). Last, semi-autonomous vehicles equipped with assistive control systems may experience degraded lateral behaviors when aggressive driver steering commands compete with high levels of autonomy. This challenge can be mitigated with effective operator intent recognition, which can configure automated systems in context-specific situations where the driver intends to perform a steering maneuver. In this article, an ensemble learning-based driver intent recognition strategy has been developed. A nonlinear model predictive control algorithm has been designed and implemented to generate haptic feedback for lateral vehicle guidance, assisting the drivers in accomplishing their intended action. To validate the framework, operator-in-the-loop testing with 30 human subjects was conducted on a steer-by-wire platform with a virtual reality driving environment. The roadway scenarios included lane change, obstacle avoidance, intersection turns, and highway exit. The automated system with learning-based driver intent recognition was compared to both the automated system with a finite state machine-based driver intent estimator and the automated system without any driver intent prediction for all driving events. Test results demonstrate that semi-autonomous vehicle performance can be enhanced by up to 74.1% with a learning-based intent predictor. The proposed holistic framework that integrates human intelligence, machine learning algorithms, and vehicle control can help solve the driver-system conflict problem leading to safer vehicle operations

Increasing Transparency and Presence of Teleoperation Systems Through Human-Centered Design

Teleoperation allows a human to control a robot to perform dexterous tasks in remote, dangerous, or unreachable environments. A perfect teleoperation system would enable the operator to complete such tasks at least as easily as if he or she was to complete them by hand. This ideal teleoperator must be perceptually transparent, meaning that the interface appears to be nearly nonexistent to the operator, allowing him or her to focus solely on the task environment, rather than on the teleoperation system itself. Furthermore, the ideal teleoperation system must give the operator a high sense of presence, meaning that the operator feels as though he or she is physically immersed in the remote task environment. This dissertation seeks to improve the transparency and presence of robot-arm-based teleoperation systems through a human-centered design approach, specifically by leveraging scientific knowledge about the human motor and sensory systems. First, this dissertation aims to improve the forward (efferent) teleoperation control channel, which carries information from the human operator to the robot. The traditional method of calculating the desired position of the robot\u27s hand simply scales the measured position of the human\u27s hand. This commonly used motion mapping erroneously assumes that the human\u27s produced motion identically matches his or her intended movement. Given that humans make systematic directional errors when moving the hand under conditions similar to those imposed by teleoperation, I propose a new paradigm of data-driven human-robot motion mappings for teleoperation. The mappings are determined by having the human operator mimic the target robot as it autonomously moves its arm through a variety of trajectories in the horizontal plane. Three data-driven motion mapping models are described and evaluated for their ability to correct for the systematic motion errors made in the mimicking task. Individually-fit and population-fit versions of the most promising motion mapping model are then tested in a teleoperation system that allows the operator to control a virtual robot. Results of a user study involving nine subjects indicate that the newly developed motion mapping model significantly increases the transparency of the teleoperation system. Second, this dissertation seeks to improve the feedback (afferent) teleoperation control channel, which carries information from the robot to the human operator. We aim to improve a teleoperation system a teleoperation system by providing the operator with multiple novel modalities of haptic (touch-based) feedback. We describe the design and control of a wearable haptic device that provides kinesthetic grip-force feedback through a geared DC motor and tactile fingertip-contact-and-pressure and high-frequency acceleration feedback through a pair of voice-coil actuators mounted at the tips of the thumb and index finger. Each included haptic feedback modality is known to be fundamental to direct task completion and can be implemented without great cost or complexity. A user study involving thirty subjects investigated how these three modalities of haptic feedback affect an operator\u27s ability to control a real remote robot in a teleoperated pick-and-place task. This study\u27s results strongly support the utility of grip-force and high-frequency acceleration feedback in teleoperation systems and show more mixed effects of fingertip-contact-and-pressure feedback

Modeling Three-Dimensional Interaction Tasks for Desktop Virtual Reality

A virtual environment is an interactive, head-referenced computer display that gives a user the illusion of presence in real or imaginary worlds. Two most significant differences between a virtual environment and a more traditional interactive 3D computer graphics system are the extent of the user's sense of presence and the level of user participation that can be obtained in the virtual environment. Over the years, advances in computer display hardware and software have substantially progressed the realism of computer-generated images, which dramatically enhanced user’s sense of presence in virtual environments. Unfortunately, such progress of user’s interaction with a virtual environment has not been observed. The scope of the thesis lies in the study of human-computer interaction that occurs in a desktop virtual environment. The objective is to develop/verify 3D interaction models that can be used to quantitatively describe users’ performance for 3D pointing, steering and object pursuit tasks and through the analysis of the interaction models and experimental results to gain a better understanding of users’ movements in the virtual environment. The approach applied throughout the thesis is a modeling methodology that is composed of three procedures, including identifying the variables involved for modeling a 3D interaction task, formulating and verifying the interaction model through user studies and statistical analysis, and applying the model to the evaluation of interaction techniques and input devices and gaining an insight into users’ movements in the virtual environment. In the study of 3D pointing tasks, a two-component model is used to break the tasks into a ballistic phase and a correction phase, and comparison is made between the real-world and virtual-world tasks in each phase. The results indicate that temporal differences arise in both phases, but the difference is significantly greater in the correction phase. This finding inspires us to design a methodology with two-component model and Fitts’ law, which decomposes a pointing task into the ballistic and correction phase and decreases the index of the difficulty of the task during the correction phase. The methodology allows for the development and evaluation of interaction techniques for 3D pointing tasks. For 3D steering tasks, the steering law, which was proposed to model 2D steering tasks, is adapted to 3D tasks by introducing three additional variables, i.e., path curvature, orientation and haptic feedback. The new model suggests that a 3D ball-and-tunnel steering movement consists of a series of small and jerky sub-movements that are similar to the ballistic/correction movements observed in the pointing movements. An interaction model is originally proposed and empirically verified for 3D object pursuit tasks, making use of Stevens’ power law. The results indicate that the power law can be used to model all three common interaction tasks, which may serve as a general law for modeling interaction tasks, and also provides a way to quantitatively compare the tasks