Computers & Industrial Engineering, Год журнала: 2021, Номер 161, С. 107621 - 107621
Опубликована: Авг. 13, 2021
Язык: Английский
Digital Communications and Networks, Год журнала: 2023, Номер 9(6), С. 1265 - 1290
Опубликована: Май 29, 2023
Nowadays, Multi Robotic System (MRS) consisting of different robot shapes, sizes and capabilities has received significant attention from researchers are being deployed in a variety real-world applications. From sensors actuators improved by communication technologies to powerful computing systems utilizing advanced Artificial Intelligence (AI) algorithms have rapidly driven the development MRS, so Internet Things (IoT) MRS become new topic, namely Robots (IoRT). This paper summarises comprehensive survey state-of-the-art for mobile robots, including general architecture, benefits, challenges, practical applications, future research directions. In addition, remarkable i) multi-robot navigation, ii) network routing protocols communications, iii) coordination among robots as well data analysis via external (cloud, fog, edge, edge-cloud) merged with IoRT architecture according their applicability. Moreover, security is long-term challenge because various attack vectors, flaws, vulnerabilities. Security threats, attacks, existing solutions based on architectures also under scrutiny. identification environmental situations that crucial all types such detection objects, human, obstacles, critically reviewed. Finally, directions given analyzing challenges robots.
Язык: Английский
Процитировано
41
Computer-Aided Civil and Infrastructure Engineering, Год журнала: 2023, Номер 39(5), С. 656 - 678
Опубликована: Май 12, 2023
Abstract During a deep excavation project, monitoring the structural health of adjacent buildings is crucial to ensure safety. Therefore, this study proposes novel probabilistic reinforcement learning (PDRL) framework optimize plan minimize cost and excavation‐induced risk. First, Bayesian‐bi‐directional general regression neural network built as model describe relationship between ground settlement foundation pit safety state building, along with actions in dynamic manner. Subsequently, double Q‐network method, which can capture realistic features management problem, trained form closed decision loop for continuous strategies. Finally, proposed PDRL approach applied real‐world case No. 14 Shanghai Metro. This estimate time‐variant probability damage occurrence maintenance update building. According strategy via PDRL, begins middle stage rather than on first day project if there full confidence quality data. When uncertainty level data rises, starting might shift an earlier date. It worth noting that method adequately robust address uncertainties embedded environment model, thus contributing optimizing achieving cost‐effectiveness risk mitigation.
Язык: Английский
Процитировано
32
Advanced Intelligent Systems, Год журнала: 2023, Номер 5(7)
Опубликована: Март 15, 2023
The past decades have seen the rapid development of tactile sensors in material, fabrication, and mechanical structure design. advancement has heightened expectation sensor functions, thus put forward a higher demand for data processing. However, conventional analysis techniques not kept pace with still suffer from some severe drawbacks, like cumbersome models, poor efficiency, expensive costs. Machine learning, its prominent ability big fast processing speed, can offer many possibilities analysis. Herein, machine learning employed signals are reviewed. Supervised unsupervised analog covered, spike summarized. Furthermore, applications robotic perception human activity monitoring presented. Finally, current challenges future prospects sensors, data, algorithms, benchmarks discussed.
Язык: Английский
Процитировано
27
Environmental Chemistry Letters, Год журнала: 2024, Номер unknown
Опубликована: Сен. 5, 2024
Язык: Английский
Процитировано
11
Deleted Journal, Год журнала: 2024, Номер 6(2)
Опубликована: Фев. 2, 2024
Abstract The rotary inverted pendulum system (RIPS) is an underactuated mechanical with highly nonlinear dynamics and it difficult to control a RIPS using the classic models. In last few years, reinforcement learning (RL) has become popular method. RL powerful potential systems high non-linearity complex dynamics, such as RIPS. Nevertheless, for not been well studied there limited research on development evaluation of this paper, algorithms are developed swing-up stabilization single-link (SLRIP) compared methods PID LQR. A physical model SLRIP created MATLAB/Simscape Toolbox, used dynamic simulation in MATLAB/Simulink train agents. An agent trainer Q-learning (QL) deep Q-network (DQNL) proposed data training. Furthermore, actions actuating horizontal arm states angles velocities arm. reward computed according zero when attends upright position. without understanding classical controllers implement agent. Finally, outcome indicates effectiveness QL DQNL conventional LQR controllers.
Язык: Английский
Процитировано
10
Robotics and Autonomous Systems, Год журнала: 2025, Номер unknown, С. 104913 - 104913
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
2
Computers in Industry, Год журнала: 2025, Номер 167, С. 104263 - 104263
Опубликована: Фев. 18, 2025
Процитировано
2
Food and Humanity, Год журнала: 2025, Номер unknown, С. 100587 - 100587
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
1
Applied Artificial Intelligence, Год журнала: 2024, Номер 38(1)
Опубликована: Авг. 5, 2024
In recent years, the integration of intelligent industrial process monitoring, quality prediction, and predictive maintenance solutions has garnered significant attention, driven by rapid advancements in digitalization, data analytics, machine learning. As traditional production systems evolve into self-aware self-learning configurations, capable autonomously adapting to dynamic environmental conditions, significance reinforcement learning becomes increasingly apparent. This paper provides an overview developments applications manufacturing industry. Various sectors within manufacturing, including robot automation, welding processes, semiconductor industry, injection molding, metal forming, milling power are explored for instances application. The analysis focuses on application types, problem modeling, training algorithms, validation methods, deployment statuses. Key benefits these identified. Particular emphasis is placed elucidating primary obstacles impeding adoption implementation technology settings, such as model complexity, accessibility simulation environments, safety constraints, interpretability. concludes proposing potential alternatives avenues future research address challenges, improving sample efficiency bridging simulation-to-reality gap.
Язык: Английский
Процитировано
7
Educational and Psychological Measurement, Год журнала: 2025, Номер unknown
Опубликована: Янв. 3, 2025
This study examines the performance of ChatGPT, developed by OpenAI and widely used as an AI-based conversational tool, a data analysis tool through exploratory factor (EFA). To this end, simulated were generated under various conditions, including normal distribution, response category, sample size, test length, loading, measurement models. The analyzed using ChatGPT-4o twice with 1-week interval same prompt, results compared those obtained R code. In analysis, Kaiser–Meyer–Olkin (KMO) value, total variance explained, number factors estimated empirical Kaiser criterion, Hull method, Kaiser–Guttman well loadings, calculated. findings from ChatGPT at two different times found to be consistent R. Overall, demonstrated good for steps that require only computational decisions without involving researcher judgment or theoretical evaluation (such KMO, loadings). However, multidimensional structures, although was across analyses, biases observed, suggesting researchers should exercise caution in such decisions.
Язык: Английский
Процитировано
1