On the Influence of Hand Dynamics on Motion Planning of Reaching Movements in Haptic Environments

The paper presents an analysis of human reaching movements in the manipulation of flexible objects. Two models, the minimum hand jerk and the minimum driving hand forcechange, are used for modelling and verification of experimental data. The data are collected with the haptic system supporting dynamic simulation of the flexible object in real time. We describe some initial experimental results and analyze the applicability of the models. It is found that even for short-term movements human motion planning strategy can depend on arm inertia and configuration. This conclusion is based on the experimental evidence of the multi-phased hand velocity profiles that can be well captured by the minimum driving hand force-change criterion. To support the latest observation, an experiment with reinforcement learning was conducted

How do humans mediate with the external physical world? From perception to control of articulated objects

Many actions in our daily life involve operation with articulated tools. Despite the ubiquity of articulated objects in daily life, human ability in perceiving the properties and control of articulated objects has been merely studied. Articulated objects are composed of links and revolute or prismatic joints. Moving one part of the linkage results in the movement of the other ones. Reaching a position with the tip of a tool requires adapting the motor commands to the change of position of the endeffector different from the action of reaching the same position with the hand. The dynamic properties are complex and variant in the movement of articulated bodies. For instance, apparent mass, a quantity that measures the dynamic interaction of the articulated object, varies as a function of the changes in configuration. An actuated articulated system can generate a static, but position-dependent force field with constant torques about joints. There are evidences that internal models are involved in the perception and control of tools. In the present work, we aim to investigate several aspects of the perception and control of articulated objects and address two questions, The first question is how people perceive the kinematic and dynamic properties in the haptic interaction with articulated objects? And the second question is what effect has seeing the tool on the planning and execution of reaching movements with a complex tool? Does the visual representation of mechanism structures help in the reaching movement and how? To address these questions, 3D printed physical articulated objects and robotic systems have been designed and developed for the psychophysical studies. The present work involves three studies in different aspects of perception and control of articulated objects. We first did haptic size discrimination tasks using three different types of objects, namely, wooden boxes, actuated apparatus with two movable flat surfaces, and large-size pliers, in unimanual, bimanual grounded and bimanual free conditions. We found bimanual integration occurred in particular in the free manipulation of objects. The second study was on the visuo-motor reaching with complex tools. We found that seeing the mechanism of the tool, even briefly at the beginning of the trial, improved the reaching performance. The last study was about force perception, evidences showed that people could take use of the force field at the end-effector to induce the torque about the joints generated by the articulated system

Haptic Guidance for Extended Range Telepresence

A novel navigation assistance for extended range telepresence is presented. The haptic information from the target environment is augmented with guidance commands to assist the user in reaching desired goals in the arbitrarily large target environment from the spatially restricted user environment. Furthermore, a semi-mobile haptic interface was developed, one whose lightweight design and setup configuration atop the user provide for an absolutely safe operation and high force display quality

Modeling of equilibrium point trajectory control in human arm movements

The underlying concept of the Equilibrium Point Hypothesis (EPH) is that the CNS provides a virtual trajectory of joint motion, representing spacing and timing, with actual movement dynamics being produced by interactions of limb inertia, muscle viscosity and speed/position feedback from muscle spindles. To counter criticisms of the EPH, investigators have proposed the use of complex virtual trajectories, non-linear damping, stiffness and time varying stiffness to the EPH model. While these features allow the EPH to adequately produce human joint velocities, they conflict with the EPH’s premise of simple pre-planned monotonic control of movement trajectory. As a result, this study proposed an EPH based method, which provides a simpler mechanism in motor control without conflict with the core advantages of the original approach. This work has proposed relative damping as an addition to the EPH model to predict the single and two joint arm movements. This addition results in simulated data that not only closely match experimental angle data, but also match the experimental joint torques. In addition, it is suggested that this modified model can be used to predict the multi-joint angular trajectories with fast and normal velocities, without the need for time varying or non-linear stiffness and damping, but with simple monotonic virtual trajectories. In the following study, this relative damping model has been further enhanced with an EMG-based determination of the virtual trajectory and with physiologically realistic neuromuscular delays. The results of unobstructed voluntary movement studies suggest that the EPH models use realistic impedance values and produce desired joint trajectories and joint torques in unperturbed voluntary arm movement. A subsequent study of obstructed voluntary arm movement extended the relative damping concept, and incorporated the influential factors of the mechanical behavior of the neural, muscular and skeletal system in the control and coordination of arm posture and movement. A significant problem of the study is how this information should be used to modify control signals to achieve desired performance. This study used an EPH model to examine changes of controlling signals for arm movements in the context of adding perturbation/load in the form of forces/torques. The mechanical properties and reflex actions of muscles of the elbow joint were examined. Brief unexpected torque/force pulses of identical magnitude and time duration were introduced at different stages of the movement in a random order by a pre-programmed 3 degree of freedom (DOF) robotic arm (MOOG FCS HapticMaster). The results show that the subjects may maintain the same control parameters (virtual trajectory, stiffness and damping) regardless of added perturbations that cause substantial changes in EMG activity and kinematics

Assessment of a hand exoskeleton on proximal and distal training in virtual environments for robot mediated upper extremity rehabilitation

Stroke is the leading cause of disability in the United States with approximately 800,000 cases per year. This cerebral vascular accident results in neurological impairments that reduce limb function and limit the daily independence of the individual. Evidence suggests that therapeutic interventions with repetitive motor training can aid in functional recovery of the paretic limb. Robotic rehabilitation may present an exercise intervention that can improve training and induce motor plasticity in individuals with stroke. An active (motorized) hand exoskeleton that provides support for wrist flexion/extension, abduction/adduction, pronation/supination, and finger pinch is integrated with a pre-existing 3-Degree of Freedom (DOF) haptic robot (Haptic Master, FCS Moog) to determine the efficacy of increased DOF during proximal and distal training in Upper Extremity (UE) rehabilitation. Subjects are randomly assigned into four groups to evaluate the significance of increased DOF during virtual training: Haptic Master control group (HM), Haptic Master with Gripper (HMG), Haptic Master with Wrist (HMW), and Haptic Master with Gripper and Wrist (HMWG). Each subject group performs a Pick and Place Task in a virtual environment where the distal hand exoskeleton is mapped to the virtual representation of the hand. Subjects are instructed to transport as many virtual cubes as possible to a specified target in the allotted time period of 120s. Three cube sizes are assessed to determine efficacy of the assistive end-effector. An additional virtual task, Mailbox Task, is performed to determine the effect of training and the ability to transfer skills between virtual settings in an unfamiliar environment. The effects of viewing mediums are also investigated to determine the effect of immersion on performance using an Oculus Rift as an HMD compared to conventional projection displays. It is hypothesized that individuals with both proximal and complete distal hand control (HMWG) will see increased benefit during the Pick and Place Task than individuals without the complete distal attachment, as assisted daily living tasks are often accomplished with coordinated arm and hand movement. The purpose of this study is to investigate the additive effect of increased degrees of freedom at the hand through task-specific training of the upper arm in a virtual environment, validate the ability to transfer skills obtained in a virtual environment to an untrained task, and determine the effects of viewing mediums on performance. A feasibility study is conducted in individuals with stroke to determine if the modular gripper can assist pinch movements. These investigations represent a comprehensive investigation to assess the potential benefits of assistive devices in a virtual reality setting to retrain lost function and increase efficacy in motor control in populations with motor impairments

Learning to push and learning to move: The adaptive control of contact forces

To be successful at manipulating objects one needs to apply simultaneously well controlled movements and contact forces. We present a computational theory of how the brain may successfully generate a vast spectrum of interactive behaviors by combining two independent processes. One process is competent to control movements in free space and the other is competent to control contact forces against rigid constraints. Free space and rigid constraints are singularities at the boundaries of a continuum of mechanical impedance. Within this continuum, forces and motions occur in \u201ccompatible pairs\u201d connected by the equations of Newtonian dynamics. The force applied to an object determines its motion. Conversely, inverse dynamics determine a unique force trajectory from a movement trajectory. In this perspective, we describe motor learning as a process leading to the discovery of compatible force/motion pairs. The learned compatible pairs constitute a local representation of the environment's mechanics. Experiments on force field adaptation have already provided us with evidence that the brain is able to predict and compensate the forces encountered when one is attempting to generate a motion. Here, we tested the theory in the dual case, i.e., when one attempts at applying a desired contact force against a simulated rigid surface. If the surface becomes unexpectedly compliant, the contact point moves as a function of the applied force and this causes the applied force to deviate from its desired value. We found that, through repeated attempts at generating the desired contact force, subjects discovered the unique compatible hand motion. When, after learning, the rigid contact was unexpectedly restored, subjects displayed after effects of learning, consistent with the concurrent operation of a motion control system and a force control system. Together, theory and experiment support a new and broader view of modularity in the coordinated control of forces and motions

A white paper: NASA virtual environment research, applications, and technology

Research support for Virtual Environment technology development has been a part of NASA's human factors research program since 1985. Under the auspices of the Office of Aeronautics and Space Technology (OAST), initial funding was provided to the Aerospace Human Factors Research Division, Ames Research Center, which resulted in the origination of this technology. Since 1985, other Centers have begun using and developing this technology. At each research and space flight center, NASA missions have been major drivers of the technology. This White Paper was the joint effort of all the Centers which have been involved in the development of technology and its applications to their unique missions. Appendix A is the list of those who have worked to prepare the document, directed by Dr. Cynthia H. Null, Ames Research Center, and Dr. James P. Jenkins, NASA Headquarters. This White Paper describes the technology and its applications in NASA Centers (Chapters 1, 2 and 3), the potential roles it can take in NASA (Chapters 4 and 5), and a roadmap of the next 5 years (FY 1994-1998). The audience for this White Paper consists of managers, engineers, scientists and the general public with an interest in Virtual Environment technology. Those who read the paper will determine whether this roadmap, or others, are to be followed

Dyadic behavior in co-manipulation :from humans to robots

To both decrease the physical toll on a human worker, and increase a robot’s environment perception, a human-robot dyad may be used to co-manipulate a shared object. From the premise that humans are efficient working together, this work’s approach is to investigate human-human dyads co-manipulating an object. The co-manipulation is evaluated from motion capture data, surface electromyography (EMG) sensors, and custom contact sensors for qualitative performance analysis. A human-human dyadic co-manipulation experiment is designed in which every human is instructed to behave as a leader, as a follower or neither, acting as naturally as possible. The experiment data analysis revealed that humans modulate their arm mechanical impedance depending on their role during the co-manipulation. In order to emulate the human behavior during a co-manipulation task, an admittance controller with varying stiffness is presented. The desired stiffness is continuously varied based on a scalar and smooth function that assigns a degree of leadership to the robot. Furthermore, the controller is analyzed through simulations, its stability is analyzed by Lyapunov. The resulting object trajectories greatly resemble the patterns seen in the human-human dyad experiment.Para tanto diminuir o esforço físico de um humano, quanto aumentar a percepção de um ambiente por um robô, um díade humano-robô pode ser usado para co-manipulação de um objeto compartilhado. Partindo da premissa de que humanos são eficientes trabalhando juntos, a abordagem deste trabalho é a de investigar díades humano-humano co-manipulando um objeto compartilhado. A co-manipulação é avaliada a partir de dados de um sistema de captura de movimentos, sinais de eletromiografia (EMG), e de sensores de contato customizados para análise qualitativa de desempenho. Um experimento de co-manipulação com díades humano-humano foi projetado no qual cada humano é instruído a se comportar como um líder, um seguidor, ou simplesmente agir tão naturalmente quanto possível. A análise de dados do experimento revelou que os humanos modulam a rigidez mecânica do braço a depender de que tipo de comportamento eles foram designados antes da co-manipulação. Para emular o comportamento humano durante uma tarefa de co-manipulação, um controle por admitância com rigidez variável é apresentado neste trabalho. A rigidez desejada é continuamente variada com base em uma função escalar suave que define o grau de liderança do robô. Além disso, o controlador é analisado por meio de simulações, e sua estabilidade é analisada pela teoria de Lyapunov. As trajetórias resultantes do uso do controlador mostraram um padrão de comportamento muito parecido ao do experimento com díades humano-humano

Optimal exoskeleton design and effective human-in-the-loop control frameworks for rehabilitation robotics

Attention, since they decrease the cost of repetitive movement therapies, enable quantitative measurement of the patient progress and promise development of more e ective rehabilitation protocols. The goal of this dissertation is to provide systematic frameworks for optimal design of rehabilitation robots and e ective delivery of therapeutic exercises. The design framework is built upon identification and categorization of the design requirements, and satisfaction of them through several design stages. In particular, type selection is performed to ensure imperative design requirements of safety, ergonomy and wearability, optimal dimensional synthesis is undertaken to maximize global kinematic and dynamic performance defined over the singularity-free workspace volume, while workspace optimization is performed to utilize maximum singularity-free device workspace computed via Grassmann line theory. Then, humanin- the-loop controllers that ensure coupled stability of the human-robot system are implemented in the robot task space using appropriate error metrics. The design framework is demonstrated on a forearm-wrist exoskeleton, since forearm and wrist rotations are critical in performing activities of daily living and recovery of these joints is essential for achieving functional independence of patients. In particular, a non-symmetric 3RPS-R mechanism is selected as the underlying kinematics type and the performance improvements due to workspace and multi-criteria optimizations are experimentally characterized as 27 % larger workspace volume, 32 % higher position control bandwidth and 17 % increase in kinematic isotropy when compared to a similar device in the literature. The exoskeleton is also shown to feature high passive back-driveability and accurate sti ness rendering capability, even under open-loop impedance control. Local controllers to accommodate for each stage of rehabilitation therapies are designed for the forearm-wrist exoskeleton in SO(3): trajectory tracking controllers are designed for early stages of rehabilitation when severely injured patients are kept passive, impedance controllers are designed to render virtual tunnels implementing forbidden regions in the device workspace and allowing for haptic interactions with virtual environments, and passive contour tracking controllers are implemented to allow for rehabilitation exercises that emphasize coordination and synchronization of multi degrees-of-freedom movements, while leaving the exact timing along the desired contour to the patient. These local controllers are incorporated into a multi-lateral shared controller architecture, which allows for patients to train with online virtual dynamic tasks in collaboration with a therapist. Utilizing this control architecture not only enables the shift of control authority of each agent so that therapists can guide or evaluate movements of patients or share the control with them, but also enables the implementation of remote and group therapies, as well as remote assessments. The proposed control framework to deliver e ective robotic therapies can ensure active involvement of patients through online modification of the task parameters, while simultaneously guaranteeing their safety. In particular, utilizing passive velocity field control and extending it with a method for online generation of velocity fields for parametric curves, temporal, spatial and assistive aspects of a desired task can be seamlessly modified online, while ensuring passivity with respect to externally applied forces. Through human subject experiments, this control framework is shown to be e ective in delivering evidence-based rehabilitation therapies, providing assistance as-needed, preventing slacking behavior of patients, and delivering repetitive therapies without exact repetition. Lastly, to guide design of e ective rehabilitation treatment protocols, a set of healthy human subject experiments are conducted in order to identify underlying principles of adaptation mechanism of human motor control system. In these catch-trial based experiments, equivalent transfer functions are utilized during execution of rhythmic dynamic tasks. Statistical evidence suggests that i) force feedback is the dominant factor that guides human adaptation while performing fast rhythmic dynamic tasks rather than the visual feedback and ii) as the e ort required to perform the task increases, the rate of adaptation decreases; indicating a fundamental trade-o between task performance and level of force feedback provided