scholarly journals Novel surface optimization for trajectory reconstruction in industrial robot tasks

2021 ◽  
Vol 18 (6) ◽  
pp. 172988142110647
Author(s):  
Miguel Angel Funes-Lora ◽  
Eduardo Vega-Alvarado ◽  
Raúl Rivera-Blas ◽  
María Barbara Calva-Yáñez ◽  
Gabriel Sepúlveda-Cervantes
Keyword(s):  
Industrial Robot ◽  
Steepest Descent ◽  
The Novel ◽  
Workpiece Surface ◽  
Trajectory Reconstruction ◽  
Minimal Error ◽  
Toolpath Optimization ◽  
Robot Tasks ◽  
Algorithm Implementation ◽  
Novel Algorithm

This study presents a novel algorithm implementation that optimizes manually recorded toolpaths with the use of a 3D-workpiece model to reduce manual error induced. The novel algorithm has three steps: workpiece declaration, manual toolpath declaration, and toolpath optimization using steepest descent algorithm. Steepest descent finds the surface route wherein the manually recorded toolpaths traverse over a 3D-workpiece surface. The optimized toolpaths were simulated and tested with an industrial robot showing minimal error compared to the desired optimized toolpaths. The results obtained from the presented implementation on three different trajectories demonstrate that the proposed methodology can reduce the manual error induced using as a reference the CAD-workpiece surface.

Novel Algorithmic Approach to Deciphering Rovash Inscriptions

2015 ◽  
pp. 7222-7233 ◽  
Author(s):  
Loránd Lehel Tóth ◽  
Raymond Pardede ◽  
Gábor Hosszú
Keyword(s):  
Experimental Results ◽  
The Novel ◽  
Statistical Probability ◽  
Algorithmic Approach ◽  
Topological Parameters ◽  
Novel Method ◽  
Novel Algorithm

The article presents a method to decipher Rovash inscriptions made by the Szekelys in the 15th-18th centuries. The difficulty of the deciphering work is that a large portion of the Rovash inscriptions contains incomplete words, calligraphic glyphs or grapheme errors. Based on the topological parameters of the undeciphered symbols registered in the database, the presented novel algorithm estimates the meaning of the inscriptions by the matching accuracies of the recognized graphemes and gives a statistical probability for deciphering. The developed algorithm was implemented in software, which also contains a built-in dictionary. Based on the dictionary, the novel method takes into account the context in identifying the meaning of the inscription. The proposed algorithm offers one or more words in a different random values as a result, from which users can select the relevant one. The article also presents experimental results, which demonstrate the efficiency of method.

scholarly journals Optimal Design of IPMSM for FCEV Using Novel Immune Algorithm Combined with Steepest Descent Method

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3395 ◽  
Author(s):  
Ji-Chang Son ◽  
Young-Rok Kang ◽  
Dong-Kuk Lim
Keyword(s):  
Optimal Design ◽  
Permanent Magnet Synchronous Motor ◽  
Global Solutions ◽  
Torque Ripple ◽  
Descent Method ◽  
Immune Algorithm ◽  
Steepest Descent ◽  
Steepest Descent Method ◽  
The Novel ◽  
Interior Permanent Magnet

In this paper, the Novel Immune Algorithm (NIA) is proposed for an optimal design of electrical machines. By coupling the conventional Immune Algorithm and Steepest Descent Method, the NIA can perform fast and exact convergence to both global solutions and local solutions. Specifically, the concept of an antibody radius is newly introduced to improve the ability to navigate full areas effectively and to find new peaks by excluding already searched areas. The validity of the NIA is confirmed by mathematical test functions with complex objective function regions. The NIA is applied to an optimal design of an interior permanent magnet synchronous motor for fuel cell electric vehicles and to derive an optimum design with diminished torque ripple.

scholarly journals Learning and Planning Based on Merged Experience from Multiple Situations for a Service Robot

2018 ◽  
Vol 8 (10) ◽  
pp. 1832
Author(s):  
Zhixian Chen ◽  
Baoliang Zhao ◽  
Shijia Zhao ◽  
Ying Hu ◽  
Jianwei Zhang
Keyword(s):  
Robot Learning ◽  
Physical Experiment ◽  
Planning Method ◽  
Service Robot ◽  
The Novel ◽  
Changing Environment ◽  
Task Knowledge ◽  
Learn Activity ◽  
Abstract Method ◽  
Novel Algorithm

For a service robot, learning appropriate behaviours to acquire task knowledge and deliberation in various situations is essential, but the existing methods do not support merging the plan-based activity experiences from multiple situations in the same task. In this paper, an abstract method is introduced to integrate the empirical activity schemas of multiple situations, and a novel algorithm is presented to learn activity schema with abstract methods. Furthermore, a novel planner called the schema-based optimized planner (SBOP) is developed based on the learned activity schema, in which actions merging optimization and partially backtracking techniques are adopted. A simulation with a PR2 robot and a physical experiment is conducted to validate the proposed method. The results show that the robot can generate a plan to recover from failure automatically using the novel learning and planning method, given that the experienced exception has been merged in the activity schema. Owing to the improved autonomy, the proposed SBOP exhibits increased efficiency in dealing with tasks containing loops and multiple activity schema instances. This research presents a novel solution of how to merge activity experiences from multiple situations and generate an intelligent and efficient plan that could adapt to a dynamically changing environment.

A Novel Neutrosophic Image Segmentation Based on Improved Fuzzy C-Means Algorithm (NIS-IFCM)

2019 ◽  
Vol 34 (05) ◽  
pp. 2055011
Author(s):  
Jing Zhao ◽  
Xiaoli Wang ◽  
Ming Li
Keyword(s):  
Computer Vision ◽  
Particle Swarm Optimization ◽  
Image Segmentation ◽  
Classical Problem ◽  
Local Optimum ◽  
The Novel ◽  
Swarm Optimization ◽  
Novel Method ◽  
Fuzzy C Means Algorithm ◽  
Novel Algorithm

Image segmentation is a classical problem in the field of computer vision. Fuzzy [Formula: see text]-means algorithm (FCM) is often used in image segmentation. However, when there is noise in the image, it easily falls into the local optimum, which results in poor image boundary segmentation effect. A novel method is proposed to solve this problem. In the proposed method, first, the image is transformed into a neutrosophic image. In order to improve the ability of global search, a combined FCM based on particle swarm optimization (PSO) is proposed. Finally, the proposed algorithm is applied to the neutrosophic image segmentation. The results of experiments show that the novel algorithm can eliminate image noise more effectively than the FCM algorithm, and make the boundary of the segmentation area clearer.

scholarly journals Tracking intermediate performance of vigilant attention using multiple eye metrics

SLEEP ◽  
2020 ◽  
Vol 43 (3) ◽  
Author(s):  
Takashi Abe ◽  
Kazuo Mishima ◽  
Shingo Kitamura ◽  
Akiko Hida ◽  
Yuichi Inoue ◽  
...  
Keyword(s):  
Sleep Deprivation ◽  
Human Error ◽  
Reaction Times ◽  
Simultaneous Recording ◽  
Time On Task ◽  
The Novel ◽  
Eyelid Closure ◽  
Psychomotor Vigilance Test ◽  
Falling Asleep ◽  
Novel Algorithm

Abstract Vigilance deficits account for a substantial number of accidents and errors. Current techniques to detect vigilance impairment measure only the most severe level evident in eyelid closure and falling asleep, which is often too late to avoid an accident or error. The present study sought to identify ocular biometrics of intermediate impairment of vigilance and develop a new technique that could detect a range of deficits in vigilant attention (VA). Sixteen healthy adults performed well-validated Psychomotor Vigilance Test (PVT) for tracking vigilance attention while undergoing simultaneous recording of eye metrics every 2 hours during 38 hours of continuous wakefulness. A novel marker was found that measured VA when the eyes were open—the prevalence of microsaccades. Notably, the prevalence of microsaccades decreased in response to sleep deprivation and time-on-task. In addition, a novel algorithm for detecting multilevel VA was developed, which estimated performance on the PVT by integrating the novel marker with other eye-related indices. The novel algorithm also tracked changes in intermediate level of VA (specific reaction times in the PVT, i.e. 300–500 ms) during prolonged time-on-task and sleep deprivation, which had not been tracked previously by conventional techniques. The implication of the findings is that this novel algorithm, named “eye-metrical estimation version of the PVT: PVT-E,” can be used to reduce human-error-related accidents caused by vigilance impairment even when its level is intermediate.

Monitoring and Control of Dual-Arm Industrial Robot Tasks Using IoT Application and Services

2015 ◽  
Vol 762 ◽  
pp. 255-260 ◽  
Author(s):  
Mircea Murar ◽  
Stelian Brad
Keyword(s):  
Experimental Testing ◽  
Industrial Robot ◽  
Cyber Physical Systems ◽  
Monitoring And Control ◽  
Research Directions ◽  
Physical Systems ◽  
Selection For ◽  
Robot Tasks ◽  
And Control ◽  
Dual Arm

In the context of latest technological revolution, Industry 4.0, connectivity and therefore access and control of cyber-physical systems and resources from any place, at any time by any means represent a technological enabler of crucial importance. The first part of this paperwork contains a brief introduction of cyber-physical systems and IoT concepts, together with a review of major IoT providers. The second part introduces an approach towards achieving connectivity and remote control of task selection for a dual-arm industrial robot using a commercially available IoT infrastructure and technology provided by ioBridge. Within the third part, details about experimental testing and evaluation of the selected solutions are presented. The last part is allocated for conclusions and further research directions.

Diagnostics of Product by Vision System

2013 ◽  
Vol 308 ◽  
pp. 33-38 ◽  
Author(s):  
Kamil Židek ◽  
Eva Rigasová
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Vision System ◽  
Industrial Robot ◽  
Current Status ◽  
Basic Algorithm ◽  
Red Color ◽  
Plastic Parts ◽  
Modular Education ◽  
Algorithm Implementation

This article describes the vision system, which is designed for diagnostics of defects in casted products. In the first part an overview about image processing, edge and pattern recognition algorithms and current status in available free and commercial vision libraries is found. For the described task we selected open source Aforge .NET library. The next part describes common defects in casted products. Modular education system MPS 500 from Festo with conveyor and palette with plastic parts is used for simulation of production system. This system contains an industrial robot which can be used for sorting defective parts. The selected vision library is used for two level diagnostics of algorithm implementation. The first level algorithm detects position of part, its dimensions and edge disturbances. The second algorithm detects any defects inside of a part. The basic algorithm is presented only for circular shape with red color texture, but can be easily extended to other basic shapes by shape detector.

Accurate determination of DNA in agarose gels using the novel algorithm GelScann(1.0)

1995 ◽  
Vol 11 (2) ◽  
pp. 187-194
Author(s):  
Michael L. Metzker ◽  
Kyle M. Allain ◽  
Richard A. Gibbs
Keyword(s):  
Accurate Determination ◽  
The Novel ◽  
Agarose Gels ◽  
Novel Algorithm

Dynamic Controller Based on Ying Learning Algorithm for Medical Temperature System

2011 ◽  
Vol 187 ◽  
pp. 371-376
Author(s):  
Ping Zhang ◽  
Xiao Hong Hao ◽  
Heng Jie Li
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Fuzzy Neural Network ◽  
Learning Algorithm ◽  
Fuzzy Neural Networks ◽  
The Novel ◽  
Fuzzy Neural ◽  
Learning Set ◽  
And Training ◽  
Novel Algorithm

In order to avoid the over fitting and training and solve the knowledge extraction problem in fuzzy neural networks system. Ying Learning Dynamic Fuzzy Neural Network (YL-DFNN) algorithm is proposed. The Learning Set based on K-VNN is constituted from message. Then the framework of is designed and its stability is proved. Finally, Simulation indicates that the novel algorithm is fast, compact, and capable in generalization.

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