scholarly journals Trajectory Extrapolation for Manual Robot Remote Welding

Robotics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 77
Author(s):  
Lucas Christoph Ebel ◽  
Jochen Maaß ◽  
Patrick Zuther ◽  
Shahram Sheikhi
Keyword(s):  
Spline Function ◽  
Weld Seam ◽  
Motion Patterns ◽  
Hand Motion ◽  
Motion Data ◽  
Input Signals ◽  
Subsequent Application ◽  
Remote Welding ◽  
The Given ◽  
Welding System

This article describes an algorithm for the online extrapolation of hand-motion during remote welding. The aim is to overcome the spatial limitations of the human welder’s arms in order to cover a larger workspace with a continuous weld seam and to substantially relieve the welder from strain and fatigue. Depending on the sampled hand-motion data, an extrapolation of the given motion patterns is achieved by decomposing the input signals in a linear direction and a periodic motion component. An approach to efficiently determine the periodicity using a sampled autocorrelation function and the subsequent application of parameter identification using a spline function are presented in this paper. The proposed approach is able to resemble all practically relevant motion patterns and has been validated successfully on a remote welding system with limited input space and audio-visual feedback by an experienced welder.

scholarly journals sEMG Signal Acquisition Strategy towards Hand FES Control

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Cinthya Lourdes Toledo-Peral ◽  
Josefina Gutiérrez-Martínez ◽  
Jorge Airy Mercado-Gutiérrez ◽  
Ana Isabel Martín-Vignon-Whaley ◽  
Arturo Vera-Hernández ◽  
...  
Keyword(s):  
Electrode Placement ◽  
Signal Acquisition ◽  
Semg Signal ◽  
Motion Patterns ◽  
Upper Limb Rehabilitation ◽  
Hand Motion ◽  
Hand Dexterity ◽  
Severe Fatigue ◽  
Patients Experience ◽  
Limb Rehabilitation

Due to damage of the nervous system, patients experience impediments in their daily life: severe fatigue, tremor or impaired hand dexterity, hemiparesis, or hemiplegia. Surface electromyography (sEMG) signal analysis is used to identify motion; however, standardization of electrode placement and classification of sEMG patterns are major challenges. This paper describes a technique used to acquire sEMG signals for five hand motion patterns from six able-bodied subjects using an array of recording and stimulation electrodes placed on the forearm and its effects over functional electrical stimulation (FES) and volitional sEMG combinations, in order to eventually control a sEMG-driven FES neuroprosthesis for upper limb rehabilitation. A two-part protocol was performed. First, personalized templates to place eight sEMG bipolar channels were designed; with these data, a universal template, called forearm electrode set (FELT), was built. Second, volitional and evoked movements were recorded during FES application. 95% classification accuracy was achieved using two sessions per movement. With the FELT, it was possible to perform FES and sEMG recordings simultaneously. Also, it was possible to extract the volitional and evoked sEMG from the raw signal, which is highly important for closed-loop FES control.

Kalman Filtering for Seam Tracking in Master-Slave Robot Remote Welding System

2011 ◽  
Vol 314-316 ◽  
pp. 1005-1008
Author(s):  
Hong Tang Chen ◽  
Hai Chao Li ◽  
Hong Ming Gao ◽  
Lin Wu
Keyword(s):  
Kalman Filtering ◽  
Seam Tracking ◽  
Experimental Results ◽  
Welding Quality ◽  
Welding Seam ◽  
Tracking Process ◽  
Key Factor ◽  
Remote Welding ◽  
Welding System

Welding seam tracking precision is a key factor influencing welding quality for master-slave robot remote welding system. However, it does not satisfy the welding requirement due to significant noises. To eliminate the influence of noises upon the seam tracking precision and improve the seam tracking precision, a master-slave robot remote welding system was built and Kalman filtering (KF) was applied to the seam tracking process. The experimental results show that the KF eliminated the influence of noises upon the seam tracking precision and improved the seam tracking precision.

scholarly journals Handwriting Recognition in Free Space Using WIMU-Based Hand Motion Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Shashidhar Patil ◽  
Dubeom Kim ◽  
Seongsill Park ◽  
Youngho Chai
Keyword(s):  
Real Time ◽  
Motion Analysis ◽  
Computer Games ◽  
Free Space ◽  
Handwriting Recognition ◽  
Angular Rate ◽  
Measurement Unit ◽  
Hand Motion ◽  
Motion Data ◽  
3D Space

We present a wireless-inertial-measurement-unit- (WIMU-) based hand motion analysis technique for handwriting recognition in three-dimensional (3D) space. The proposed handwriting recognition system is not bounded by any limitations or constraints; users have the freedom and flexibility to write characters in free space. It uses hand motion analysis to segment hand motion data from a WIMU device that incorporates magnetic, angular rate, and gravity sensors (MARG) and a sensor fusion algorithm to automatically distinguish segments that represent handwriting from nonhandwriting data in continuous hand motion data. Dynamic time warping (DTW) recognition algorithm is used to recognize handwriting in real-time. We demonstrate that a user can freely write in air using an intuitive WIMU as an input and hand motion analysis device to recognize the handwriting in 3D space. The experimental results for recognizing handwriting in free space show that the proposed method is effective and efficient for other natural interaction techniques, such as in computer games and real-time hand gesture recognition applications.

Study on Weld Seam Modeling for Remote Welding

2013 ◽  
Vol 401-403 ◽  
pp. 895-898
Author(s):  
Sheng Gao ◽  
Yu Wang
Keyword(s):  
Virtual Environment ◽  
Template Matching ◽  
Weld Seam ◽  
Spline Interpolation ◽  
Continuous Model ◽  
Vision Sensor ◽  
Laser Vision Sensor ◽  
Laser Vision ◽  
Operative Difficulty ◽  
Remote Welding

This paper studies the dynamic modeling of weld seam by using the laser vision sensor in virtual environment (VE). By introducing virtual guide (VG), lowering operative difficulty and showing high security can be obtained. Template matching is used to recognize remote weld seam, and the uniform contour of V is defined to represent the features of remote seam. Cubic spline interpolation is employed to construct the continuous model of the seam.

Latent Variable Grasp Prediction for Exoskeletal Glove Control

2018 ◽  
Author(s):  
Raghuraj J. Chauhan ◽  
Pinhas Ben-Tzvi
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Random Noise ◽  
Prediction Algorithm ◽  
Small Motion ◽  
Hand Motion ◽  
User Input ◽  
Motion Data ◽  
Nonlinear Motion ◽  
Successful Prediction

This paper presents a grasp prediction algorithm designed to govern the motion of an exoskeletal glove in rehabilitative and assistive applications. Recent research into the dynamics of hand motion has shown that the complex motion of the finger joints can be represented as a smaller set of coordinated motions or latent variables. This fact forms the basis of the proposed algorithm capable of successful prediction even with noisy data. From relatively small motion (minute user hand movements) as the input, the developed algorithm can predict intended grasp configurations. The 16 finger joint angles, with random noise, are mapped onto a set of six latent variables for which the estimated noise and future configuration are simultaneously determined using a linear regression. The algorithm was tested in simulation on published motion data from 30 healthy subjects performing a set of common grasps on multiple objects. The algorithm was able to determine the target state with an accuracy of approximately 90% for each subject, despite the nonlinear motion and non-uniform trajectory variations. We propose that the predicted grasp is an adequate target for an exoskeletal glove to provide initial gross movement for the user, then iteratively converge to the desired grasp with only limited additional user input.

Design, Modeling, and Motion Analysis of a Novel Fluid Actuated Spherical Rolling Robot

2019 ◽  
Vol 11 (4) ◽  
Author(s):  
Seyed Amir Tafrishi ◽  
Mikhail Svinin ◽  
Esmaeil Esmaeilzadeh ◽  
Motoji Yamamoto
Keyword(s):  
Forward Direction ◽  
Motion Patterns ◽  
Design Specifications ◽  
The Core ◽  
D’Alembert Principle ◽  
Circular Pipes ◽  
Fluid Properties ◽  
Spherical Mobile Robot ◽  
The Given ◽  
Rolling Robot

This paper studies a novel fluid actuated system for a spherical mobile robot. The robot’s mechanism consists of two essential parts: circular pipes to lead spherical moving masses (cores) and an internal driving unit to propel the cores. The spherical shell of the robot is rolled by displacing the cores in the pipes filled with fluid. First, we describe the structure of the robot and derive its nonlinear dynamics using the D’Alembert principle. Next, we model the internal driving unit that actuates the core inside the pipe. The simulated driving unit is studied with respect to three important parameters—the input motor torque, the actuator size, and the fluid properties. The overall model of the robot is then used for analyzing motion patterns in the forward direction. Analytical studies show that the modeled robot can be implemented under the given design specifications.

scholarly journals Immersive analysis of user motion in VR applications

2020 ◽  
Vol 36 (10-12) ◽  
pp. 1937-1949
Author(s):  
Simon Kloiber ◽  
Volker Settgast ◽  
Christoph Schinko ◽  
Martin Weinzerl ◽  
Johannes Fritz ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Virtual Environment ◽  
Visual Analysis ◽  
Human Motion ◽  
Motion Patterns ◽  
Motion Data ◽  
Data Mining Algorithms ◽  
Novel Approach ◽  
Analysis System ◽  
Mining Algorithms

Abstract With the rise of virtual reality experiences for applications in entertainment, industry, science and medicine, the evaluation of human motion in immersive environments is becoming more important. By analysing the motion of virtual reality users, design choices and training progress in the virtual environment can be understood and improved. Since the motion is captured in a virtual environment, performing the analysis in the same environment provides a valuable context and guidance for the analysis. We have created a visual analysis system that is designed for immersive visualisation and exploration of human motion data. By combining suitable data mining algorithms with immersive visualisation techniques, we facilitate the reasoning and understanding of the underlying motion. We apply and evaluate this novel approach on a relevant VR application domain to identify and interpret motion patterns in a meaningful way.

Motion Patterns in Acupuncture Needle Manipulation

2014 ◽  
Vol 32 (5) ◽  
pp. 394-399 ◽  
Author(s):  
Yoonjeong Seo ◽  
In-Seon Lee ◽  
Won-Mo Jung ◽  
Ho-Sun Ryu ◽  
Jinwoong Lim ◽  
...  
Keyword(s):  
Individual Variability ◽  
Regression Curve ◽  
Average Amplitude ◽  
Motion Patterns ◽  
Motion Data ◽  
Regression Curves ◽  
Time Motion ◽  
Motion Unit ◽  
Individual Consistency ◽  
Mixed Modelling

Background In clinical practice, acupuncture manipulation is highly individualised for each practitioner. Before we establish a standard for acupuncture manipulation, it is important to understand completely the manifestations of acupuncture manipulation in the actual clinic. To examine motion patterns during acupuncture manipulation, we generated a fitted model of practitioners’ motion patterns and evaluated their consistencies in acupuncture manipulation. Methods Using a motion sensor, we obtained real-time motion data from eight experienced practitioners while they conducted acupuncture manipulation using their own techniques. We calculated the average amplitude and duration of a sampled motion unit for each practitioner and, after normalisation, we generated a true regression curve of motion patterns for each practitioner using a generalised additive mixed modelling (GAMM). Results We observed significant differences in rotation amplitude and duration in motion samples among practitioners. GAMM showed marked variations in average regression curves of motion patterns among practitioners but there was strong consistency in motion parameters for individual practitioners. The fitted regression model showed that the true regression curve accounted for an average of 50.2% of variance in the motion pattern for each practitioner. Conclusions Our findings suggest that there is great inter-individual variability between practitioners, but remarkable intra-individual consistency within each practitioner.

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