Sliding mode speed auto-regulation technique for robotic tracking

In advanced industry manufacturing involving robotic operations, the required tasks can be frequently formulated in terms of a path or trajectory tracking. In this paper, an approach based on sliding mode conditioning of a path parametrization is proposed to achieve the greatest tracking speed which is compatible with the robot input constraints (joint speeds). Some distinctive features of the proposal are that: (1) it is completely independent of the robot parameters, and it does not require a priori knowledge of the desired path either, (2) it avoids on-line computations necessary for conventional analytical methodologies, and (3) it can be easily added as a supervisory block to pre-existing path tracking schemes. A sufficient condition (lower bound on desired tracking speed) for the sliding mode regulation to be activated is derived, while a chattering amplitude estimation is obtained in terms of the sampling period and a tunable first-order filter bandwidth. The algorithm is evaluated on the freely accessible 6R robot model PUMA-560, for which a path passing through a wrist singularity is considered to show the effectiveness of the proposal under hard tracking conditions. © 2011 Elsevier B.V. All rights reserved.This research is partially supported by DISICOM project PROM-ETEO 2008/088 of Generalitat Valenciana (Spain), research project DPI2008-06731-C02-01 of the Spanish Government (Spain), Technical University of Valencia (Spain), and the Argentinian Government (UNLP 111127, CONICET PIP 112-200801-0, ANPCyT PICT 2007 00535).Garelli, F.; Gracia Calandin, LI.; Sala, A.; Albertos Pérez, P. (2011). Sliding mode speed auto-regulation technique for robotic tracking. Robotics and Autonomous Systems. 59(7-8):519-529. https://doi.org/10.1016/j.robot.2011.03.007S519529597-

Uncalibrated Dynamic Mechanical System Controller

An apparatus and method for enabling an uncalibrated, model independent controller for a mechanical system using a dynamic quasi-Newton algorithm which incorporates velocity components of any moving system parameter(s) is provided. In the preferred embodiment, tracking of a moving target by a robot having multiple degrees of freedom is achieved using an uncalibrated model independent visual servo control. Model independent visual servo control is defined as using visual feedback to control a robot's servomotors without a precisely calibrated kinematic robot model or camera model. A processor updates a Jacobian and a controller provides control signals such that the robot's end effector is directed to a desired location relative to a target on a workpiece.Georgia Tech Research Corporatio

Brain–Machine Interface and Visual Compressive Sensing-Based Teleoperation Control of an Exoskeleton Robot

This paper presents a teleoperation control for an exoskeleton robotic system based on the brain-machine interface and vision feedback. Vision compressive sensing, brain-machine reference commands, and adaptive fuzzy controllers in joint-space have been effectively integrated to enable the robot performing manipulation tasks guided by human operator's mind. First, a visual-feedback link is implemented by a video captured by a camera, allowing him/her to visualize the manipulator's workspace and movements being executed. Then, the compressed images are used as feedback errors in a nonvector space for producing steady-state visual evoked potentials electroencephalography (EEG) signals, and it requires no prior information on features in contrast to the traditional visual servoing. The proposed EEG decoding algorithm generates control signals for the exoskeleton robot using features extracted from neural activity. Considering coupled dynamics and actuator input constraints during the robot manipulation, a local adaptive fuzzy controller has been designed to drive the exoskeleton tracking the intended trajectories in human operator's mind and to provide a convenient way of dynamics compensation with minimal knowledge of the dynamics parameters of the exoskeleton robot. Extensive experiment studies employing three subjects have been performed to verify the validity of the proposed method

МЕТОД ОЦІНКИ ВІДГУКІВ ПАЦІЄНТІВ МЕДИЧНИХ ЗАКЛАДІВ З ВИКОРИСТАННЯМ НЕЧІТКОЇ ЛОГІКИ

This paper concentrates on problems of assessing the quality of health care facilities process. Research describes methods and approaches of gathering customer feedback. Aspects of patients feedback aggregation and satisfaction statistics building during treatment are considered. Investigated possibilities of using fuzzy logic systems with a view to solving the problem of evaluating the quality of treatment. Constructed fuzzy logic controller in order to consolidate parameters of medication for provisioning of measurable results.В статті описано проблематику оцінки якості роботи медичних закладів. Подано методи збору відгуку клієнтів клінік. Розглянуто аспекти агрегування та побудови статистики вдоволення пацієнтів процесом лікування. Досліджено можливості використання систем нечіткої логіки з метою для вирішення задачі оцінювання вдоволеності якістю лікування. Побудовано та апробовано контролер нечіткої логіки для консолідації параметрів оцінки якості та надання вимірюваного результату

Vision-based interface applied to assistive robots

This paper presents two vision-based interfaces for disabled people to command a mobile robot for personal assistance. The developed interfaces can be subdivided according to the algorithm of image processing implemented for the detection and tracking of two different body regions. The first interface detects and tracks movements of the user's head, and these movements are transformed into linear and angular velocities in order to command a mobile robot. The second interface detects and tracks movements of the user's hand, and these movements are similarly transformed. In addition, this paper also presents the control laws for the robot. The experimental results demonstrate good performance and balance between complexity and feasibility for real-time applications.Fil: Pérez Berenguer, María Elisa. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Soria, Carlos Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: López Celani, Natalia Martina. Universidad Nacional de San Juan. Facultad de Ingeniería. Departamento de Electrónica y Automática. Gabinete de Tecnología Médica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Nasisi, Oscar Herminio. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; ArgentinaFil: Mut, Vicente Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan. Instituto de Automática. Universidad Nacional de San Juan. Facultad de Ingeniería. Instituto de Automática; Argentin

Advanced intelligent control and optimization for cardiac pacemaker systems

Since cardiovascular diseases are major causes of morbidity and mortality in the developed countries and the number one cause of death in the United States, their accurate diagnosis and effective treatment via advanced cardiac pacemaker systems have become very important. Intelligent control and optimization of the pacemakers are significant research subjects. Serious but infrequently occurring arrhythmias are difficult to diagnose. The use of electrocardiogram (ECG) waveform only cannot exactly distinguish between deadly abnormalities and temporary arrhythmias. Thus, this work develops a new method based on frequency entrainment to analyze pole-zero characteristics of the phase error between abnormal ECG and entrained Yanagihara, Noma, and Irisawa (YNI)-response. The thresholds of poles and zeros to diagnose deadly bradycardia and tachycardia are derived, respectively, for the first time. For bradycardia under different states, a fuzzy proportional-integral-derivative (FPID) controller for dual- sensor cardiac pacemaker systems is designed. It can automatically control the heart rate to accurately track a desired preset profile. Through comparing with the conventional algorithm, FPID provides a more suitable control strategy for offering better adaptation of the heart rate, in order to fulfill the patient\u27s physiological needs. This novel control method improves the robustness and performance of a pacemaker system significantly. Higher delivered energy for stimulation may cause higher energy consumption in pacemakers and accelerated battery depletion. Hence, this work designs an optimal single-pulse stimulus to treat sudden cardiac arrest, while minimizing the pulse amplitude and releasing stimulus pain. Moreover, it derives the minimum pulse amplitude for successful entrainment. The simulation results confirm that the optimal single-pulse is effective to induce rapid response of sudden cardiac arrest for heartbeat recovery, while a significant reduction in the delivered energy is achieved. The study will be helpful for not only better diagnosis and treatment of cardiovascular diseases but also improving the performance of pacemaker systems

Pressure at play:measuring player approach and avoidance behaviour through the keyboard

With the increased adoption of real-time objective measurements of player experience, advances have been made in characterising the dynamically changing aspects of the player experience during gameplay itself. A direct coupling to player action, however, is not without challenges. Many physiological responses, for instance, have an inherent delay, and often take some time to return to a baseline, providing challenges of interpretation when analysing rapidly changing gameplay on a micro level of interaction. The development of event-related, or phasic, measurements directly coupled to player actions provides additional insights, for instance through player modelling, but also through the use of behavioural characteristics of the human computer interaction itself. In this study, we focused on the latter, and measured keyboard pressure in a number of different, fast-paced action games. In this particular case, we related specific functional game actions (keyboard presses) to experiential player behaviour. We found keyboard pressure to be higher for avoidance as compared to approach-oriented actions. Additionally, the difference between avoidance and approach keyboard pressure related to levels of arousal. The findings illustrate the application potential of qualifying players’ functional actions at play (navigating in a game) and interpret player experience related to these actions through players’ real world behavioural characteristics like interface pressure

Learning Algorithm Design for Human-Robot Skill Transfer

In this research, we develop an intelligent learning scheme for performing human-robot skills transfer. Techniques adopted in the scheme include the Dynamic Movement Prim- itive (DMP) method with Dynamic Time Warping (DTW), Gaussian Mixture Model (G- MM) with Gaussian Mixture Regression (GMR) and the Radical Basis Function Neural Networks (RBFNNs). A series of experiments are conducted on a Baxter robot, a NAO robot and a KUKA iiwa robot to verify the effectiveness of the proposed design.During the design of the intelligent learning scheme, an online tracking system is de- veloped to control the arm and head movement of the NAO robot using a Kinect sensor. The NAO robot is a humanoid robot with 5 degrees of freedom (DOF) for each arm. The joint motions of the operator’s head and arm are captured by a Kinect V2 sensor, and this information is then transferred into the workspace via the forward and inverse kinematics. In addition, to improve the tracking performance, a Kalman filter is further employed to fuse motion signals from the operator sensed by the Kinect V2 sensor and a pair of MYO armbands, so as to teleoperate the Baxter robot. In this regard, a new strategy is developed using the vector approach to accomplish a specific motion capture task. For instance, the arm motion of the operator is captured by a Kinect sensor and programmed through a processing software. Two MYO armbands with embedded inertial measurement units are worn by the operator to aid the robots in detecting and replicating the operator’s arm movements. For this purpose, the armbands help to recognize and calculate the precise velocity of motion of the operator’s arm. Additionally, a neural network based adaptive controller is designed and implemented on the Baxter robot to illustrate the validation forthe teleoperation of the Baxter robot.Subsequently, an enhanced teaching interface has been developed for the robot using DMP and GMR. Motion signals are collected from a human demonstrator via the Kinect v2 sensor, and the data is sent to a remote PC for teleoperating the Baxter robot. At this stage, the DMP is utilized to model and generalize the movements. In order to learn from multiple demonstrations, DTW is used for the preprocessing of the data recorded on the robot platform, and GMM is employed for the evaluation of DMP to generate multiple patterns after the completion of the teaching process. Next, we apply the GMR algorithm to generate a synthesized trajectory to minimize position errors in the three dimensional (3D) space. This approach has been tested by performing tasks on a KUKA iiwa and a Baxter robot, respectively.Finally, an optimized DMP is added to the teaching interface. A character recombination technology based on DMP segmentation that uses verbal command has also been developed and incorporated in a Baxter robot platform. To imitate the recorded motion signals produced by the demonstrator, the operator trains the Baxter robot by physically guiding it to complete the given task. This is repeated five times, and the generated training data set is utilized via the playback system. Subsequently, the DTW is employed to preprocess the experimental data. For modelling and overall movement control, DMP is chosen. The GMM is used to generate multiple patterns after implementing the teaching process. Next, we employ the GMR algorithm to reduce position errors in the 3D space after a synthesized trajectory has been generated. The Baxter robot, remotely controlled by the user datagram protocol (UDP) in a PC, records and reproduces every trajectory. Additionally, Dragon Natural Speaking software is adopted to transcribe the voice data. This proposed approach has been verified by enabling the Baxter robot to perform a writing task of drawing robot has been taught to write only one character