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2024 Conference of Young Researchers in Electrical and Electronic Engineering, ElCon 2024

作者： Belov, Alexander M. Belov, Mikhail P. Saint Petersburg Electrotechnical University 'LETI' Chair of Robotics and Automation of Manufacturing Systems Saint Petersburg Russia

ISBN: (纸本)9798350360646

This report deals with optimization of parameters of the control system of electric drives and cutting process of metalworking machine tools using neural networks. Synthesis of optimal parameters allows to reduce errors of machining of parts on a metalworking machine. Neural regulators are used to find the optimal parameters of the control system of electric drives and cutting process. During optimization, various modes of part machining are considered, affecting the depth of cut, feed rate, surface roughness. © 2024 IEEE.

关键词： multi electric neural network (NN) neural controller

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A modular and extensible framework for real and virtual bin-picking environments

A modular and extensible framework for real and virtual bin-...

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IEEE International Conference on robotics and automation (ICRA)

作者： Adrian Schyja Alfred Hypki Bernd Kuhlenkötter Chair of Industrial Robotics and Production Automation (IRPA) Technical University Dortmund Germany

The number of industrial applications where a robot needs to unload disordered parts is increasing substantially. The usage of robot vision is highly preferred to obtain reliable results. In the past different algorithms for localizing objects as well as for motion planning to avoid collisions between gripper, object and environment were presented and even some commercial Bin-Picking systems are available. Nevertheless a realistic simulation taking account of various vision and robot systems and path planning strategies to predict cycle times is still not possible. In this paper a universal software framework with the focus on virtual Bin-Picking is presented. Utilizing a generic approach this framework enables the integration of various algorithms for object recognition, motion planning, different types of robots, grippers and vision systems. Thus an efficient simulation of different (virtual) Bin-Picking setups including equipment such as sensor devices or robot controllers within a virtual environment is possible. Furthermore the use of such a system allows the prediction of cycle times, percentage of tangible objects or testing of different Bin-Picking setups.

关键词： Robot sensing systems Machine vision Service robots Collision avoidance Solid modeling Planning

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Managing processes of perceptual organization for emerging geometrical objects

Managing processes of perceptual organization for emerging g...

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IEEE International Conference on Systems, Man and Cybernetics

作者： A. Kasinski T. Piascik Chair of Robotics Automation and Computer Science Poznan University of Technology Poznan Poland

Three lower level layers of the hierarchical machine perception system are described, and experimental results are provided. The system is based on agile camera and aimed at automatic recognition of simple geometric scenes, made of crafted manipulation objects. The primary process of grouping the edgelets on the image is described. Two methods of edgelet grouping are compared, namely a Hough transform based method and a method based on LSR. Some modifications to both methods have been proposed. Next, a process of perceptual grouping of elementary features, short segments, is described. Three approaches to feature fusion are addressed: one based on crisp, geometrical, heuristic conditions, the second based on fuzzified conditions and the third one based on Dempster-Shafer theory. The results obtained with the three methods are compared and presented on the example image of a real scene. Higher layer issues, namely a problem of contour closing and of separating particular objects (in the case of occlusions) are briefly discussed. Some preliminary results in that area are reported.

关键词： Layout Cameras Feature extraction robotics and automation Robot vision systems Image recognition Image segmentation Image reconstruction Computer vision Surface reconstruction

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Reachability-Based Confidence-Aware Probabilistic Collision Detection in Highway Driving

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Engineering 2024年第2期33卷 90-107页

作者： Xinwei Wang Zirui Li Javier Alonso-Mora Meng Wang School of Engineering and Materials Science Queen Mary University of LondonLondon E14NSUK Department of Cognitive Robotics Delft University of TechnologyDelft 2628 CDNetherlands School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China Chair of Traffic Process Automation “Friedrich List”Faculty of Transport and Traffic SciencesTU DresdenDresden 01069Germany

Risk assessment is a crucial component of collision warning and avoidance systems for intelligent ***-based formal approaches have been developed to ensure driving safety to accurately detect potential vehicle ***,they suffer from over-conservatism,potentially resulting in false–positive risk events in complicated real-world *** this paper,we combine two reachability analysis techniques,a backward reachable set(BRS)and a stochastic forward reachable set(FRS),and propose an integrated probabilistic collision–detection framework for highway *** this framework,we can first use a BRS to formally check whether a two-vehicle interaction is safe;otherwise,a prediction-based stochastic FRS is employed to estimate the collision probability at each future time ***,the framework can not only identify non-risky events with guaranteed safety but also provide accurate collision risk estimation in safety-critical *** construct the stochastic FRS,we develop a neural network-based acceleration model for surrounding vehicles and further incorporate a confidence-aware dynamic belief to improve the prediction *** experiments were conducted to validate the performance of the acceleration prediction model based on naturalistic highway driving *** efficiency and effectiveness of the framework with infused confidence beliefs were tested in both naturalistic and simulated highway *** proposed risk assessment framework is promising for real-world applications.

关键词： Probabilistic collision detection Confidence awareness Probabilistic acceleration prediction Reachability analysis Risk assessment

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Safety System for Industrial Robots Based on Human Detection Using an RGB-D Camera

Safety System for Industrial Robots Based on Human Detection...

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Proceedings of the International Convention MIPRO

作者： Valentin Šimundić Dario Mihelčić Damian Svirac Petra Đurović Robert Cupec Faculty of Electrical Engineering Computer Science and Information Technology Osijek Croatia Chair of Automation and Robotics

A robotic system, in general, should be safe for the operators who are using it and, if possible, it should be safe for the system itself and the environment it interacts with. This paper investigates three methods for human detection by an RGB-D camera and their adjustments for monitored robot movement. The methods are implemented in ROS and integrated into a robotic system consisting of an industrial robot arm ABB IRB-2400L and an RGB-D camera. Validation and comparison of the implemented algorithms was performed on the recorded video dataset containing people in the robot working area with per-frame annotations of human presence, velocity and proximity to the robot. The algorithms detect humans with highest recall of 98%.

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Universal IoT Vending Machine Management Platform

Universal IoT Vending Machine Management Platform

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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Srdjan Tegeltija Branislav Tejić Ivana Šenk Laslo Tarjan Gordana Ostojić Chair of Mechatronics Robotics and Automation Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia

ISBN: (数字)9781728147758

ISBN: (纸本)9781728147765

With the advances of technology, vending machines have evolved from simple devices that sell individual products and provide simple services to complex devices where product and service offerings are tailored to each individual user. Following the increasing need to use a large amount of information in real-time (optimization of supply, timely updating of machines, monitoring the status of vending machines, etc), an increasing number of vending machines are connecting to the Internet and represent the IoT devices in the IoT ecosystem. In this paper, a solution for a universal IoT platform for managing vending machines is proposed. Emphasis is placed on the implementation of the control unit with an additional module for interaction with the users.

关键词： Computers Hardware Machine control Temperature sensors Microcontrollers Monitoring

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Features of Optimization of Parameters of Electric Drives Control System and Cutting Process of Metalworking Machine Tools Using Neural Networks

Features of Optimization of Parameters of Electric Drives Co...

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IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)

作者： Alexander M. Belov Mikhail P. Belov Chair of Robotics and Automation of Manufacturing Systems Saint Petersburg Electrotechnical University “LETI” Saint Petersburg Russia

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Synthesis of a Neural Controller for Controlling a Multi-drive Industrial Mechanism

Synthesis of a Neural Controller for Controlling a Multi-dri...

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Electrical Engineering, automation & Control Systems, Theory and Practical Applications (EEACS), Seminar on

作者： Alexander M. Belov Mikhail P. Belov Chair of Robotics and Automation of Manufacturing Systems Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia

The analysis of the synthesis of a neural controller for the control of a multi electric drive industrial mechanism, taking into account different modes of operation and disturbing influences is carried out. The influence of neural controller on dynamics and accuracy of velocity maintenance is investigated in Matlab mathematical environment. The recommendations for the synthesis of the neural controller are formulated.

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Automated Disassembly Sequence Prediction for Industry 4.0 Using Enhanced Genetic Algorithm

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Computers, Materials & Continua 2021年第11期69卷 2531-2548页

作者： Anil Kumar Gulivindala M.V.A.Raju Bahubalendruni R.Chandrasekar Ejaz Ahmed Mustufa Haider Abidi Abdulrahman Al-Ahmari Department of Mechanical Engineering Industrial Robotics and Manufacturing Automation LaboratoryNational Institute of TechnologyKariakal609609India Department of Computer Science Engineering National Institute of TechnologyKariakal609609India Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The evolution of Industry 4.0 made it essential to adopt the Internet of Things(IoT)and Cloud Computing(CC)technologies to perform activities in the new age of *** technologies enable collecting,storing,and retrieving essential information from the manufacturing *** collected at sites are shared with others where execution automatedly *** obtained information must be validated at manufacturing to avoid undesirable data losses during the de-manufacturing ***,information sharing from the assembly level at the manufacturing stage to disassembly at the product end-of-life state is a major *** current research validates the information optimally to offer a minimum set of activities to complete the disassembly *** optimal disassembly sequence plan(DSP)can possess valid information to organize the necessary actions in ***,finding an optimal DSP is complex because of its combinatorial *** genetic algorithm(GA)is a widely preferred artificial intelligence(AI)algorithm to obtain a near-optimal solution for the DSP *** converging nature at local optima is a limitation in the traditional *** study improvised the GA workability by integrating with the proposed priori crossover *** optimality function is defined to reduce disassembly effort by considering directional changes as *** enhanced GA method is tested on a real-time product to evaluate the *** obtained results reveal that diversity control depends on the operators employed in the disassembly *** proposed method’s solution can be stored in the cloud and shared through IoT devices for effective resource allocation and disassembly for maximum recovery of the *** effectiveness of the proposed enhanced GA method is determined by making a comparative assessment with traditional GA and other AI methods at different population sizes.

关键词： automation internet of things disassembly sequence planning priori cross over operator enhanced GA disassembly predicates

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Unconventional integration of the fundamental elements of soft computing and traditional methods in adaptive robot control

Unconventional integration of the fundamental elements of so...

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IEEE International Conference on robotics and automation (ICRA)

作者： J.K. Tar I.J. Rudas J.F. Bito K. Kozlowski Department of Information Technology Centre of Robotics and Automation Bánki Donát Polytechnic Hungary Chair of Control Robotics and Computer Science Poznan University of Technology Poznan Poland

Traditional fuzzy controllers or artificial neural networks are constrained by standardized formal procedures and structural restrictions. While in general it is guaranteed that these approaches or their integration can solve a quite wide class of problems, their "orthodox" application may result in too complicated control not exploiting the peculiarities of the given task under consideration. The aim of the paper is to demonstrate that unconventional integration of simple elements such as classic PID/ST, regression analysis, saturated sigmoid transition functions, fuzzy sets and uniform structures obtained from the Lagrangian classical mechanics instead of the connection structure of a feedforward artificial neural networks can result in a simple and efficient adaptive control for robots involved in unknown environmental dynamic interaction. Due to their simplicity and reduced number of parameters real time tuning can be carried out in these structures. Most of the parameters are independent of the particular problem to be solved and neither "scaling problems" nor "network paralysis" occur during the learning phase. It is concluded that the different components of the control can successfully co-operate in finding the "proper" system model even in the case of very rough initial model estimation and external interaction.

关键词： Robot control Fuzzy control Artificial neural networks Motion control Adaptive control robotics and automation Automatic control Space technology Programmable control Information technology

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