244 research outputs found
A Comprehensive Survey of the Tactile Internet: State of the art and Research Directions
The Internet has made several giant leaps over the years, from a fixed to a
mobile Internet, then to the Internet of Things, and now to a Tactile Internet.
The Tactile Internet goes far beyond data, audio and video delivery over fixed
and mobile networks, and even beyond allowing communication and collaboration
among things. It is expected to enable haptic communication and allow skill set
delivery over networks. Some examples of potential applications are
tele-surgery, vehicle fleets, augmented reality and industrial process
automation. Several papers already cover many of the Tactile Internet-related
concepts and technologies, such as haptic codecs, applications, and supporting
technologies. However, none of them offers a comprehensive survey of the
Tactile Internet, including its architectures and algorithms. Furthermore, none
of them provides a systematic and critical review of the existing solutions. To
address these lacunae, we provide a comprehensive survey of the architectures
and algorithms proposed to date for the Tactile Internet. In addition, we
critically review them using a well-defined set of requirements and discuss
some of the lessons learned as well as the most promising research directions
Advanced Strategies for Robot Manipulators
Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored
Human-Robot Collaborations in Industrial Automation
Technology is changing the manufacturing world. For example, sensors are being used to track inventories from the manufacturing floor up to a retail shelf or a customer’s door. These types of interconnected systems have been called the fourth industrial revolution, also known as Industry 4.0, and are projected to lower manufacturing costs. As industry moves toward these integrated technologies and lower costs, engineers will need to connect these systems via the Internet of Things (IoT). These engineers will also need to design how these connected systems interact with humans. The focus of this Special Issue is the smart sensors used in these human–robot collaborations
An Integrated Decision Making Approach for Adaptive Shared Control of Mobility Assistance Robots
© 2016, Springer Science+Business Media Dordrecht. Mobility assistance robots provide support to elderly or patients during walking. The design of a safe and intuitive assistance behavior is one of the major challenges in this context. We present an integrated approach for the context-specific, on-line adaptation of the assistance level of a rollator-type mobility assistance robot by gain-scheduling of low-level robot control parameters. A human-inspired decision-making model, the drift-diffusion Model, is introduced as the key principle to gain-schedule parameters and with this to adapt the provided robot assistance in order to achieve a human-like assistive behavior. The mobility assistance robot is designed to provide (a) cognitive assistance to help the user following a desired path towards a predefined destination as well as (b) sensorial assistance to avoid collisions with obstacles while allowing for an intentional approach of them. Further, the robot observes the user long-term performance and fatigue to adapt the overall level of (c) physical assistance provided. For each type of assistance a decision-making problem is formulated that affects different low-level control parameters. The effectiveness of the proposed approach is demonstrated in technical validation experiments. Moreover, the proposed approach is evaluated in a user study with 35 elderly persons. Obtained results indicate that the proposed gain-scheduling technique incorporating ideas of human decision-making models shows a general high potential for the application in adaptive shared control of mobility assistance robots
Robotic contour tracking with adaptive feedforward control by fuzzy online tuning
Industrial robots have great importance in manufacturing. Typical uses of the robots are welding, painting, deburring, grinding, polishing and shape recovery. Most of these tasks such as grinding, deburring need force control to achieve high performance. These tasks involve contour following. Contour following is a challenging task because in many of applications the geometry physical of the targeted contour are unknown. In addition to that, achieving tasks as polishing, grinding and deburring requires small force and velocity tracking errors. In order to accomplish these tasks, disturbances have to be taken account. In this thesis the aim is to achieve contour tracking with using fuzzy online tuning. The fuzzy method is proposed in this thesis to adjust a feedforward force control parameter. In this technique, the varying feedforward control parameter compensates for disturbance effects. The method employs the chattering of control signal and the normal force and tangential velocity errors to adjust the control term. Simulations with the model of a direct drive planar elbow manipulator are used to last proposed technique
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
Task-Oriented Cross-System Design for Timely and Accurate Modeling in the Metaverse
In this paper, we establish a task-oriented cross-system design framework to
minimize the required packet rate for timely and accurate modeling of a
real-world robotic arm in the Metaverse, where sensing, communication,
prediction, control, and rendering are considered. To optimize a scheduling
policy and prediction horizons, we design a Constraint Proximal Policy
Optimization(C-PPO) algorithm by integrating domain knowledge from relevant
systems into the advanced reinforcement learning algorithm, Proximal Policy
Optimization(PPO). Specifically, the Jacobian matrix for analyzing the motion
of the robotic arm is included in the state of the C-PPO algorithm, and the
Conditional Value-at-Risk(CVaR) of the state-value function characterizing the
long-term modeling error is adopted in the constraint. Besides, the policy is
represented by a two-branch neural network determining the scheduling policy
and the prediction horizons, respectively. To evaluate our algorithm, we build
a prototype including a real-world robotic arm and its digital model in the
Metaverse. The experimental results indicate that domain knowledge helps to
reduce the convergence time and the required packet rate by up to 50%, and the
cross-system design framework outperforms a baseline framework in terms of the
required packet rate and the tail distribution of the modeling error.Comment: This paper is accepted by IEEE Journal on Selected Areas in
Communications, JSAC-SI-HCM 202
Adaptive assistance-based on decision-making models for telerobotics systems
Esta tesis propone una nueva estrategia de asistencia háptica en la interacción humano-robot. Dado que el humano es el elemento fundamental del sistema, es necesario proponer estrategias que se adapten a su comportamiento, además de garantizar un mejoramiento del desempeño en la tarea. El inconveniente surge cuando se requiere asistir al operador en mejorar el desempeño de la tarea y permitir al usuario total control de la tarea cuando sea necesario, desviándose del plan original con el objetivo de abordar situaciones imprevistas. Desde una perspectiva enfocada en el control, se debe resolver el compromiso existente entre proveer un alto nivel de asistencia para mejorar el desempeño de la tarea y un bajo nivel de asistencia para permitir al operador desviarse del plan pre-programado (original). Se propone entonces incorporar en la asistencia háptica un mecanismo de toma de decisiones usado por los humanos en tareas básicas de decisión entre dos alternativas. Este mecanismo de decisión se incorporar como el método de selección de parámetros en un controlador adaptativo de estructura fija (i.e. un controlador de impedencia/admitancia de parámetros variables). Los resultados experimentales demuestran que el modelo de toma de decisión, i.e. el modelo drift-diffusion modificado, permite asignar el nivel de autonomÃa de una forma que resulta intuitiva para el usuario y mejora el desempeño en la tarea. Además la estrategia de asistencia basada en modelos de toma de decisión proporciona un mecanismo de sintonizaci ón para resolver diferentes requerimientos de la tarea, lo cual es importante en entornos no estructurados. Dado el número de parámetros configurables presentes en la asistencia, la etapa experimental expone la función de cada uno de estos parámetros. Se realizó un experimento con usuarios en un entorno de teleoperación donde se evalúa estadÃsticamente el comportamiento de la asistencia en entornos parcialmente estructurados y se compara con la asistencia proporcionada por un experto humano, la cual puede ser considerada como la asistencia adaptativa nominal.Abstract. This thesis proposes a novel haptic assistance method for human-robot interaction. Since the human is the main element of the system, it is necessary to propose strategies that adapt the robot’s dynamics to the human behavior, while guaranteeing an improvement in task performance. The main issue arises when the assistance must chose between assisting the operator to improve task performance or allowing the user to have full authority over the task when necessary, allowing him/her to deviate from the original plan in order to handle unforeseen situations. From a control systems’ perspective, the assistance has to solve the trade-off between high assistance levels to improve task performance and low assistance level to allow the user to deviate from the preprogrammed (original) plan. The main results of this work incorporate into the haptic assistance a human-like decision-making mechanism used in two-alternative force choice tasks. Our experimental results show that the drift-diffusion, which is a decision-making model proposed in the cognitive area, allocates control authority in a way that is intuitive for the user. The the proposed assistance provides a tunable (decision-making) mechanism that is capable of fulfilling different task requirements, which is an important when dealing with unstructured environments. Given the number of configurable parameters in the assistance mechanism, the experimental procedure exposes the effects of changing them. A user study in a telerobotic scenario was performed to evaluate the behavior of the assistance in a partially structured environment; the proposed assistance is compared to the assistance provided by a human expert, which may be considered as the nominal adaptive assistance.Doctorad
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