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Tytuł:
Exploration and mining learning robot of autonomous marine resources based on adaptive neural network controller
Autorzy:
Pan, L.
Powiązania:
https://bibliotekanauki.pl/articles/260396.pdf
Data publikacji:
2018
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
adaptive neural network
marine resources
learning robot
Opis:
To study the autonomous learning model of the learning robot for marine resource exploration, an adaptive neural network controller was applied. The motion characteristics of autonomous learning robots were identified. The mathematical model of the multilayer forward neural network and its improved learning algorithm were studied. The improved Elman regression neural network and the composite input dynamic regression neural network were further discussed. At the same time, the diagonal neural network was analysed from the structure and learning algorithms. The results showed that for the complex environment of the ocean, the structure of the composite input dynamic regression network was simple, and the convergence was fast. In summary, the identification method of underwater robot system based on neural network is effective.
Źródło:
Polish Maritime Research; 2018, S 3; 78-83
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Adapting an Anthropomorphized Robot for Enhancing EFL Learning Motivation and Performance at an Elementary School in Taiwan
Autorzy:
Tsai, Cheng-Chang
Powiązania:
https://bibliotekanauki.pl/articles/1967568.pdf
Data publikacji:
2019-12-31
Wydawca:
Wydawnictwo Adam Marszałek
Tematy:
educational robot
English learning
learning motivation
Opis:
This study introduced an anthropomorphized robot-assisted instructional tool that we developed for English as a foreign language (EFL) learning and assessed the effectiveness of robot-assisted English learning. An experimental design was adopted in this study and a total of 53 Taiwanese students in the third grade of elementary school participated in the experiment, including: one class consisting of 28 students, which was labeled as the experimental group, while another class of 25 students was labeled as the control group. There were two kinds of data collection that were used in this study: two tests (listening-and-acting as well as questioning-and-answering tests) and a questionnaire (learning material motivation scale). On the whole, the experimental group performed better than the control group on the listening-and-acting as well as on the questioning-and-answering tests. Additionally, the experimental group had higher learning material motivation than the control group, inclusive of attention, relevance, confidence, and satisfaction domains. The overall results suggest a new paradigm about our applications in teaching and learning English for Taiwanese EFL elementary school students.
Źródło:
The New Educational Review; 2019, 58; 22-35
1732-6729
Pojawia się w:
The New Educational Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Effect of robot utterances using onomatopoeia on collaborative learning
Autorzy:
Jimenez, F.
Kanoh, M.
Yoshikawa, T.
Furuhashi, T.
Nakamura, T.
Powiązania:
https://bibliotekanauki.pl/articles/91733.pdf
Data publikacji:
2014
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
robot
onomatopoeia
collaborative learning
Opis:
We investigated the effect of robot’s utterances using onomatopoeia in collaborative learning. The robot was designed to provide encouragement using onomatopoeia when students are given problems to be solved issued by a learning system. Eight college students used a mathematics learning system with a robot for three weeks and then took exams. The results indicated that the robot using utterances with onomatopoeia could comfort learners more than the robot without onomatopoeia. It suggests that the robot that praises or comforts using onomatopoeia helps learners maintain their motivation in collaborative learning.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2014, 4, 2; 125-131
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Navigation strategy for mobile robot based on computer vision and YOLOv5 network in the unknown environment
Autorzy:
Bui, Thanh-Lam
Tran, Ngoc-Tien
Powiązania:
https://bibliotekanauki.pl/articles/30148249.pdf
Data publikacji:
2023
Wydawca:
Polskie Towarzystwo Promocji Wiedzy
Tematy:
mobile robot
navigation
deep learning
computer vision
Opis:
The capacity to navigate effectively in complex environments is a crucial prerequisite for mobile robots. In this study, the YOLOv5 model is utilized to identify objects to aid the mobile robot in determining movement conditions. However, the limitation of deep learning models being trained on insufficient data, leading to inaccurate recognition in unforeseen scenarios, is addressed by introducing an innovative computer vision technology that detects lanes in real-time. Combining the deep learning model with computer vision technology, the robot can identify different types of objects, allowing it to estimate distance and adjust speed accordingly. Additionally, the paper investigates the recognition reliability in varying light intensities. When the light illumination increases from 300 lux to 1000 lux, the reliability of the recognition model on different objects also improves, from about 75% to 98%, respectively. The findings of this study offer promising directions for future breakthroughs in mobile robot navigation.
Źródło:
Applied Computer Science; 2023, 19, 2; 82-95
1895-3735
2353-6977
Pojawia się w:
Applied Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Development of an automated assembly process supported with an artificial neural network
Autorzy:
Bobka, P.
Heyn, J.
Henningson, J.-O.
Römer, M.
Engbers, T.
Dietrich, F.
Dröder, K.
Powiązania:
https://bibliotekanauki.pl/articles/99408.pdf
Data publikacji:
2018
Wydawca:
Wrocławska Rada Federacji Stowarzyszeń Naukowo-Technicznych
Tematy:
assembly
machine learning
neural network
industrial robot
Opis:
A central problem in automated assembly is the ramp-up phase. In order to achieve the required tolerances and cycle times, assembly parameters must be determined by extensive manual parameter variations. Therefore, the duration of the ramp-up phase represents a planning uncertainty and a financial risk, especially when high demands are placed on dynamics and precision. To complete this phase as efficiently as possible, comprehensive planning and experienced personnel are necessary. In this paper, we examine the use of machine learning techniques for the ramp-up of an automated assembly process. Specifically we use a deep artificial neural network to learn process parameters for pick-and-place operations of planar objects. We describe how the handling parameters of an industrial robot can be adjusted and optimized automatically by artificial neural networks and examine this approach in laboratory experiments. Furthermore, we test whether an artificial neural network can be used to optimize assembly parameters in process as an adaptive process controller. Finally, we discuss the advantages and disadvantages of the described approach for the determination of optimal assembly parameters in the ramp-up phase and during the utilization phase.
Źródło:
Journal of Machine Engineering; 2018, 18, 3; 28-41
1895-7595
2391-8071
Pojawia się w:
Journal of Machine Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Academic E-Teacher in E-Learning
Autorzy:
Wenta, Kazimierz
Powiązania:
https://bibliotekanauki.pl/articles/26186855.pdf
Data publikacji:
2013-06-30
Wydawca:
Wydawnictwo Adam Marszałek
Tematy:
academic e-teacher
e-learning
educational robot
Opis:
Issues concerning the e-university teacher in the context of e-learning as an implemented from-method of education are solved on the basis of literature and quality environmental research. Theoretical analysis covers a range of media pedagogy and academic pedeutology and quality research the students of postgraduate and extra-mural studies participated in. Developed research material revealed that there are two perspectives ahead of academic e-teacher: 1) intensive preparation for e-learning implementation, especially in extra-mural and postgraduate studies; 2) satisfying students’ various educational needs with the use of traditional and multimedia forms-methods for their preparation for LLL. We should also predict that the robot of a university teacher assistant in the future will become competition in the higher education market.
Źródło:
The New Educational Review; 2013, 32; 335-344
1732-6729
Pojawia się w:
The New Educational Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Creation of third generation e-learning systems using telepresence robot and specialized visual programming language
Tworzenie systemów e-learningowych trzeciej generacji przy użyciu robota telepresence i specjalistycznego języka programowania wizualnego
Autorzy:
Matviychuk, Yaroslav
Hasko, Roman
Powiązania:
https://bibliotekanauki.pl/articles/941762.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Rzeszowski. Wydawnictwo Uniwersytetu Rzeszowskiego
Tematy:
robot
teleobecność
e-learning
wizualny język programowania
telepresence robot
visual programming language
Opis:
W artykule przedstawiono typowe wady istniejących systemów e-learningowych opartych na Web 2.0 oraz zaproponowano podstawową strukturę ich nowej generacji. Kluczowym elementem tego rozwiązania jest robot telepresence sterowany za pomocą interfejsu WWW z elementami autonomicznego zachowania. Drugą ważną cechą jest wbudowany wizualny język programowania (VPL) pozwalający na wzmocnienie zarówno procesu uczenia się, jak i autonomii robota telepresence. Wykorzystano system oparty na MINDSTORMS, tablet PC działający pod systemem Android do wideokonferencji i serwer MOODLE do konstrukcji działającego prototypu zaproponowanego systemu e-learningowego z robotem telepresence.
The article describes the typical drawbacks of existing e-learning systems based on Web 2.0 and proposes the basic structure for a new solution. The key feature is a telepresence robot with elements of autonomous behaviour controlled via a web-interface. The second feature is the use of built-in visual programming language to empower both the learning process and the autonomy of the telepresence robot. A working prototype of the proposed e-learning system with telepresence robot based on MINDSTORMS, Android powered tablet PC for video and MOODLE-based server side was developed.
Źródło:
Nierówności Społeczne a Wzrost Gospodarczy; 2013, 36; 327-332
1898-5084
2658-0780
Pojawia się w:
Nierówności Społeczne a Wzrost Gospodarczy
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A human robot interaction by a model of the emotional learning in the brain
Autorzy:
Sonoh, S.
Aou, S.
Horio, K.
Tamukoh, H.
Koga, T.
Yamakawa, T.
Powiązania:
https://bibliotekanauki.pl/articles/384207.pdf
Data publikacji:
2010
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
emotional learning
amygdala
lassical conditioning
human-robot interaction
Opis:
In this paper, we proposed an emotional expression system as a brain-inspired system. The emotional expression was achieved by an Emotional expression Model of the Amygdala (EMA), which was an engineering model inspired by an emotional learning in the brain. EMA can realize both recognition of sensory inputs and a classical conditioning of emotional inputs. Furthermore, a specific hardware of EMA was developed with a massively parallel architecture by using an FPGA, and achieved a calculation speed that is over 20 times faster than an embedded general-purpose computer. Finally, we confirmed an effectiveness of a human-robot interaction with the emotions, which were generated by the proposed emotional expression system.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2010, 4, 2; 48-54
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A scalable tree based path planning for a service robot
Autorzy:
Nippun Kumaar, A. A.
Kochuvila, Sreeja
Nagaraja, S. R.
Powiązania:
https://bibliotekanauki.pl/articles/2204556.pdf
Data publikacji:
2022
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
learning from demonstration
path mapping
path planning
navigation system
mobile robot
service robot
Opis:
Path planning plays a vital role in a mobile robot navi‐ gation system. It essentially generates the shortest tra‐ versable path between two given points. There are many path planning algorithms that have been proposed by re‐ searchers all over the world; however, there is very little work focussing on path planning for a service environ‐ ment. The general assumption is that either the environ‐ ment is fully known or unknown. Both cases would not be suitable for a service environment. A fully known en‐ vironment will restrict further expansion in terms of the number of navigation points and an unknown environ‐ ment would give an inefficient path. Unlike other envi‐ ronments, service environments have certain factors to be considered, like user‐friendliness, repeatability, sca‐ lability, and portability, which are very essential for a service robot. In this paper, a simple, efficient, robust, and environment‐independent path planning algorithm for an indoor mobile service robot is presented. Initially, the robot is trained to navigate to all the possible desti‐ nations sequentially with a minimal user interface, which will ensure that the robot knows partial paths in the en‐ vironment. With the trained data, the path planning al‐ gorithm maps all the logical paths between all the des‐ tinations, which helps in autonomous navigation. The al‐ gorithm is implemented and tested using a 2D simulator Player/Stage. The proposed system is tested with two dif‐ ferent service environment layouts and proved to have features like scalability, trainability, accuracy, and repe‐ atability. The algorithm is compared with various classi‐ cal path planning algorithms and the results show that the proposed path planning algorithm is on par with the other algorithms in terms of accuracy and efficient path generation.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2022, 16, 1; 31--45
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Handling realistic noise in multi-agent systems with self-supervised learning and curiosity
Autorzy:
Szemenyei, Marton
Reizinger, Patrik
Powiązania:
https://bibliotekanauki.pl/articles/2147129.pdf
Data publikacji:
2022
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
deep reinforcement learning
multi-agent environment
autonomous driving
robot soccer
self-supervised learning
Opis:
Most reinforcement learning benchmarks – especially in multi-agent tasks – do not go beyond observations with simple noise; nonetheless, real scenarios induce more elaborate vision pipeline failures: false sightings, misclassifications or occlusion. In this work, we propose a lightweight, 2D environment for robot soccer and autonomous driving that can emulate the above discrepancies. Besides establishing a benchmark for accessible multiagent reinforcement learning research, our work addresses the challenges the simulator imposes. For handling realistic noise, we use self-supervised learning to enhance scene reconstruction and extend curiosity-driven learning to model longer horizons. Our extensive experiments show that the proposed methods achieve state-of-the-art performance, compared against actor-critic methods, ICM, and PPO.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2022, 12, 2; 135--148
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Self-supervised learning of motion-induced acoustic noise awareness in social robots
Autorzy:
Andrade, João
Pedro, Santana
Almeida, Alexandre P.
Powiązania:
https://bibliotekanauki.pl/articles/950803.pdf
Data publikacji:
2019
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
social robot
acoustic noise
motion control
self-supervised learning
robot społeczny
hałas akustyczny
kontrola ruchu
Opis:
With the growing presence of robots in human populated environments, it becomes necessary to render their presence natural, rather than invasive. To do that, robots need to make sure the acoustic noise induced by their motion does not disturb people nearby. In this line, this paper proposes a method that allows the robot to learn how to control the amount of noise it produces, taking into account the environmental context and the robot’s mechanical characteristics. Concretely, the robot adapts its motion to a speed that allows it to produce less noise than the environment’s background noise and, hence, avoiding to disturb nearby humans. For that, before executing any given task in the environment, the robot learns how much acoustic noise it produces at different speeds in that environment by gathering acoustic informatinon through a microphone. The proposed method was successfully validated on various environments with various background noises. In addition, a PIR sensor was installed on the robot in order to test the robot’s ability to trigger the noise-aware speed control procedure when a person enters the sensor’s field of view. The use of a such a simple sensor aims at demonstrating the ability of the proposed system to be deployed in minimalistic robots, such as micro unmanned aerial vehicles.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2019, 13, 1; 3-14
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Sztuczne sieci neuronowe jako motoryczna pamięć asocjacyjna ręki robota humanoidalnego
Artificial neural networks as a motorical associative memory for humanoid robot hand
Autorzy:
Olszewski, P.
Kamiński, W. A.
Powiązania:
https://bibliotekanauki.pl/articles/408803.pdf
Data publikacji:
2017
Wydawca:
Politechnika Lubelska. Wydawnictwo Politechniki Lubelskiej
Tematy:
sztuczna sieć neuronowa
metoda uczenia
robot humanoidalny
manipulator
artificial neural network
learning system
humanoid robot
manipulators
Opis:
Opisane badania dotyczą użycia sztucznych sieci neuronowych przy realizacji asocjacyjnej pamięci motorycznej zarządzającej ręką robota humanoidalnego. Zaproponowano model kognitywnego sterowania odwołujący się do struktur i mechanizmów przetwarzania znanych z badań neurofizjologicznych. Do realizacji asocjacji posłużono się dwiema różnymi sieciami: maszyną płynową i jednokierunkową siecią asocjacyjną podobną do BAM.
This paper relates to the artificial neural networks usage for the purpose of associative memory implementation managing humanoid robot hand. Refering to the structures and mechanisms of processing known from neurophysiological studies model of cognitive control was proposed. In the association realization process two different networks were used: a liquid state machine and a one-way associative network similar to BAM.
Źródło:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska; 2017, 7, 3; 72-77
2083-0157
2391-6761
Pojawia się w:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Constrained Output Iterative Learning Control
Autorzy:
Yovchev, Kaloyan
Delchev, Kamen
Krastev, Evgeniy
Powiązania:
https://bibliotekanauki.pl/articles/229181.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
constrained output systems
convergence analysis
iterative learning control
robot manipulators
Opis:
Iterative Learning Control (ILC) is a well-known method for control of systems performing repetitive jobs with high precision. This paper presents Constrained Output ILC (COILC) for non-linear state space constrained systems. In the existing literature there is no general solution for applying ILC to such systems. This novel method is based on the Bounded Error Algorithm (BEA) and resolves the transient growth error problem, which is a major obstacle in applying ILC to non-linear systems. Another advantage of COILC is that this method can be applied to constrained output systems. Unlike other ILC methods the COILC method employs an algorithm that stops the iteration before the occurrence of a violation in any of the state space constraints. This way COILC resolves both the hard constraints in the non-linear state space and the transient growth problem. The convergence of the proposed numerical procedure is proved in this paper. The performance of the method is evaluated through a computer simulation and the obtained results are compared to the BEA method for controlling non-linear systems. The numerical experiments demonstrate that COILC is more computationally effective and provides better overall performance. The robustness and convergence of the method make it suitable for solving constrained state space problems of non-linear systems in robotics.
Źródło:
Archives of Control Sciences; 2020, 30, 1; 157-176
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Iterative learning control with sampled-data feedback for robot manipulators
Autorzy:
Delchev, K.
Boiadjiev, G.
Kawasaki, H.
Mouri, T.
Powiązania:
https://bibliotekanauki.pl/articles/229323.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
sampled-data systems
iterative learning control
robot manipulators
convergence analysis
Opis:
This paper deals with the improvement of the stability of sampled-data (SD) feedback control for nonlinear multiple-input multiple-output time varying systems, such as robotic manipulators, by incorporating an off-line model based nonlinear iterative learning controller. The proposed scheme of nonlinear iterative learning control (NILC) with SD feedback is applicable to a large class of robots because the sampled-data feedback is required for model based feedback controllers, especially for robotic manipulators with complicated dynamics (6 or 7 DOF, or more), while the feedforward control from the off-line iterative learning controller should be assumed as a continuous one. The robustness and convergence of the proposed NILC law with SD feedback is proven, and the derived sufficient condition for convergence is the same as the condition for a NILC with a continuous feedback control input. With respect to the presented NILC algorithm applied to a virtual PUMA 560 robot, simulation results are presented in order to verify convergence and applicability of the proposed learning controller with SD feedback controller attached.
Źródło:
Archives of Control Sciences; 2014, 24, 3; 299-319
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
System bezpieczeństwa dla współpracującego robota przemysłowego na bazie kamer głębi
Safety System for an Industrial Cooperating Robot Based on Depth Cameras
Autorzy:
Masłowski, Dawid
Czubenko, Michał
Powiązania:
https://bibliotekanauki.pl/articles/276876.pdf
Data publikacji:
2019
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
system wizyjny
robot produkcyjny
system bezpieczeństwa
stereowizja
HSI
vision system
production robot
inspection system
machine learning
Opis:
W artykule zarysowano problematykę robotyzacji małych przedsiębiorstw, w szczególności aspekt robotyzacji z uwzględnieniem robotów współpracujących. Szeroko omówiono zagadnienie robotów współpracujących oraz bezpieczeństwa człowieka podczas takiej współpracy. Przedstawiono również najbardziej popularne systemy bezpieczeństwa w odniesieniu do obowiązujących norm. W głównej części artykułu przedstawiono Cooperating Automaton System with Stereovision Invigilating the Environment (CASSIE), system dedykowany do monitorowania bezpieczeństwa robotów kooperacyjnych za pomocą multimodalnych sensorów głębi. Ukazano również efekt działania takiego systemu.
This article outlines the problems of robotization in small production enterprises, in particular the aspect of their robotization with colaborating robots. The issue of cobots, especially the human security aspect in such a cooperation has been presented. The most popular safety systems in relation to applicable standards has been also presented. The main part of the article shows the Cooperating Automaton System with Stereovision Invigilating the Environment (CASSIE), a system dedicated for safety monitoring of cobot environment using multimodal depth sensors. The effect of such a system has also been shown.
Źródło:
Pomiary Automatyka Robotyka; 2019, 23, 4; 41-46
1427-9126
Pojawia się w:
Pomiary Automatyka Robotyka
Dostawca treści:
Biblioteka Nauki
Artykuł
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