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Automatic Anti-Swing Gantry Crane Based on Gradient Descent Optimization Proportional Integrated Derivative (PID): A Comparison Simulation and Real Experiment

Automatic Anti-Swing Gantry Crane Based on Gradient Descent ...

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International Conference on Electrical engineering and Informatics, ICEEI

作者： Munzir Qadri Danang Karuna Harjanto Jonathan Miharja Winda Astuti Yosica Mariana Sofyan Tan Mahmud Iwan Solihin Mechanical Engineering Department Engineering Faculty University of Muhammadiyah Jakarta Jakarta Indonesia Computer Engineering Department Automotive and Robotics Program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Industrial Engineering Department Product Design program BINUS ASO School of Engineering Bina Nusantara University Jakarta Indonesia Departement of Mechanical & Mechatronics Engineering UCSI University Kuala Lumpur Malaysia

Transporting payload with precise swing angles and transfer times poses a challenging task in building construction, which is why gantry crane systems are extensively utilized. Various control strategies, including open-loop and closed-loop systems, have been proposed to tackle this issue. However, most of these controllers rely on a model and parameters specific to the crane system, making the process of modeling and parameter identification complex and time-consuming. To address this challenge, this work presents a practical and simulation control method for automatic gantry cranes, which is evaluated simulation and experimentally. The lab-scale Gantry crane is developed in this work, which consists of mechanical and electrical parts. Proportional Integral and Derivative (PID) and Proportional Derivative (PD) controllers which applied optimization method are implemented in the electrical part of the system. The PID and PD controller applied in controlled the position and swing angle, respectively. The Gradient Decent optimization method is the best optimization method in determining the parameter of the controller, since it has the best simulation performance in the output of the system. The experimental result is developed and compared between simulation and lab-scale Gantry crane hardware implementation part. The performance of experimental results is shown appropriately approaching the performance of the simulation result, with the approximately settling time.

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Non-Human Primate Monitoring System: Early Alert System Against Crop Raids for Farms in Nepal

Non-Human Primate Monitoring System: Early Alert System Agai...

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IEEE Global Humanitarian Technology Conference (GHTC)

作者： Daniil Slutskiy Zach Jacques Nuno Bazarian Saurav Basnet Amir Poudel Prakash Manandhar School of Engineering Wentworth Institute of Technology Boston Massachusetts USA Environmental Science and Policy Johns Hopkins University Baltimore MD USA Program of Computer Science Wentworth Institute of Technology Boston Massachusetts USA

ISBN: (数字)9798350377347

ISBN: (纸本)9798350377354

The ongoing shift of populations from rural villages to urban centers in Nepal has led to farmland abandonment, drawing wildlife, particularly rhesus macaques, closer to human settlements. This proximity has resulted in frequent crop raids, causing substantial agricultural damage, and affecting the wellbeing of farmers. Traditional non-lethal deterrent methods, including noisemakers and netting, have proven ineffective. To address this issue, the described project aimed to develop a surveillance system using AI technology and IoT modules to detect macaque raids and alert farmers promptly. The system comprises a Raspberry Pi equipped with a camera and microphone, designed to detect motion and process live video feeds for monkey detection. Audio data is also recorded for future model training. Unlike solutions requiring extensive infrastructure, this system is costeffective and deployable in remote areas without specialized transceivers. Initial tests indicate the system's potential to protect crops and enhance farmers’ quality of life, fostering a harmonious coexistence between humans and wildlife in Nepal.

关键词： Training Surveillance Wildlife Crops Cameras Transceivers Data models Feeds Artificial intelligence Microphones

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Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models

arXiv

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arXiv 2025年

作者： Chen, Qiguang Qin, Libo Liu, Jinhao Peng, Dengyun Guan, Jiannan Wang, Peng Hu, Mengkang Zhou, Yuhang Gao, Te Che, Wanxiang LARG China Research Center for Social Computing and Interactive Robotics China Harbin Institute of Technology China School of Computer Science and Engineering Central South University China The University of Hong Kong Hong Kong Fudan University China

Recent advancements in reasoning with large language models (RLLMs), such as OpenAI-O1 and DeepSeek-R1, have demonstrated their impressive capabilities in complex domains like mathematics and coding. A central factor in their success lies in the application of long chain-of-thought (Long CoT) characteristics, which enhance reasoning abilities and enable the solution of intricate problems. However, despite these developments, a comprehensive survey on Long CoT is still lacking, limiting our understanding of its distinctions from traditional short chain-of-thought (Short CoT) and complicating ongoing debates on issues like "overthinking" and "test-time scaling." This survey seeks to fill this gap by offering a unified perspective on Long CoT. (1) We first distinguish Long CoT from Short CoT and introduce a novel taxonomy to categorize current reasoning paradigms. (2) Next, we explore the key characteristics of Long CoT: deep reasoning, extensive exploration, and feasible reflection, which enable models to handle more complex tasks and produce more efficient, coherent outcomes compared to the shallower Short CoT. (3) We then investigate key phenomena such as the emergence of Long CoT with these characteristics, including overthinking, and test-time scaling, offering insights into how these processes manifest in practice. (4) Finally, we identify significant research gaps and highlight promising future directions, including the integration of multi-modal reasoning, efficiency improvements, and enhanced knowledge frameworks. By providing a structured overview, this survey aims to inspire future research and further the development of logical reasoning in artificial intelligence1 © 2025, CC BY-SA.

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Attention-Enhanced Lightweight Hourglass Network for Human Pose Estimation

arXiv

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arXiv 2024年

作者： Kappan, Marsha Mariya Sandoval, Eduardo Benitez Meijering, Erik Cruz, Francisco School of Computer Science and Engineering University of New South Wales Sydney Australia School of Art and Design Creative Robotics Lab University of New South Wales Sydney Australia Escuela de Ingenieŕıa Universidad Central de Chile Santiago Chile

Pose estimation is a critical task in computer vision with a wide range of applications from activity monitoring to human-robot interaction. However, most of the existing methods are computationally expensive or have complex architecture. Here we propose a lightweight attention based pose estimation network that utilizes depthwise separable convolution and Convolutional Block Attention Module on an hourglass backbone. The network significantly reduces the computational complexity (floating point operations) and the model size (number of parameters) containing only about 10% of parameters of original eight stack Hourglass network. Experiments were conducted on COCO and MPII datasets using a two stack hourglass backbone. The results showed that our model performs well in comparison to six other lightweight pose estimation models with an average precision of 72.07. The model achieves this performance with only 2.3M parameters and 3.7G FLOPs. © 2024, CC BY.

关键词： Convolution

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CURIOSITY-DRIVEN REINFORCEMENT LEARNING AGENT for MAPPING UNKNOWN INDOOR ENVIRONMENTS 24

CURIOSITY-DRIVEN REINFORCEMENT LEARNING AGENT for MAPPING UN...

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2021 24th ISPRS Congress "Imaging Today, Foreseeing Tomorrow", Commission I

作者： Botteghi, N. Schulte, R. Sirmacek, B. Poel, M. Brune, C. Robotics and Mechatronics Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands Smart Cities School of Creative Technology Saxion University of Applied Sciences Netherlands Datamanagement and Biometrics Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands Applied Analysis Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands

Autonomously exploring and mapping is one of the open challenges of robotics and artificial intelligence. Especially when the environments are unknown, choosing the optimal navigation directive is not straightforward. In this paper, we propose a reinforcement learning framework for navigating, exploring, and mapping unknown environments. The reinforcement learning agent is in charge of selecting the commands for steering the mobile robot, while a SLAM algorithm estimates the robot pose and maps the environments. The agent, to select optimal actions, is trained to be curious about the world. This concept translates into the introduction of a curiosity-driven reward function that encourages the agent to steer the mobile robot towards unknown and unseen areas of the world and the map. We test our approach in explorations challenges in different indoor environments. The agent trained with the proposed reward function outperforms the agents trained with reward functions commonly used in the literature for solving such tasks. © Author(s) 2021.

关键词： Reinforcement learning

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On the Analytical Investigation of Hybrid Transmission NOMA (H-NOMA) 14th

On the Analytical Investigation of Hybrid Transmission NOMA ...

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14th International Conference on Applications of Fuzzy Systems, Soft Computing, and Artificial Intelligence Tools, ICAFS 2020

作者： Haci, Hüseyin Ghosh, Joydev Department of Electrical and Electronic Engineering Near East University Mersin 10 Turkey School of Computer Science and Robotics National Research Tomsk Polytechnic University Tomsk Russia

ISBN: (纸本)9783030640576

Non-orthogonal multiple access (NOMA) is shown to be the optimal channel access method and a strong candidate to be employed at the fifth generation (5G) and beyond networks. This paper studies direct transmission (DT) and cooperative transmission (CT) modes of operations in NOMA communications and proposes an investigation on evolving a cooperative transmission NOMA (C-NOMA) into a Hybrid transmission NOMA (H-NOMA) that can be used for design and deployment of relay based wireless networks, such as networks for Internet of Things (IoT) applications. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Internet of things

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Bayesian Parameter Estimation for Partially Observed McKean-Vlasov Diffusions Using Multilevel Markov chain Monte Carlo

arXiv

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arXiv 2025年

作者： Jasra, Ajay Wu, Amin School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this article we consider Bayesian estimation of static parameters for a class of partially observed McKean-Vlasov diffusion processes with discrete-time observations over a fixed time interval. This problem features several obstacles to its solution, which include that the posterior density is numerically intractable in continuous-time, even if the transition probabilities are available and even when one uses a time-discretization, the posterior still cannot be used by adopting well-known computational methods such as Markov chain Monte Carlo (MCMC). In this paper we provide a solution to this problem by using new MCMC algorithms which can solve the aforementioned issues. This MCMC algorithm is extended to use multilevel Monte Carlo (MLMC) methods. We prove convergence bounds on our parameter estimators and show that the MLMC-based MCMC algorithm reduces the computational cost to achieve a mean square error versus ordinary MCMC by an order of magnitude. We numerically illustrate our results on two models. Copyright © 2025, The Authors. All rights reserved.

关键词： Channel estimation

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LiDAR Simulation for Performance Evaluation of UAS Detect and Avoid

LiDAR Simulation for Performance Evaluation of UAS Detect an...

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2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021

作者： Riordan, James Manduhu, Manduhu Black, Julie Dow, Alexander Dooly, Gerard Matalonga, Santiago Almada Research Centre School of Computing Engineering and Physical Science University of the West of Scotland Lanarkshire United Kingdom Centre for Robotics and Intelligent Systems University of Limerick Department of Electronic and Computer Engineering

ISBN: (纸本)9780738131153

The solution to mitigating risks associated with beyond Visual Line of Sight (BVLOS) operations of Unmanned Aerial System (UAS) generally focuses on the use of advanced Unmanned Traffic Management (UTM) systems. However, this solution does not take into account other uncooperative objects in the airspace. A more robust approach is to have UTM integrations coupled with onboard machine vision which is tied to automated collision avoidance systems. Future BVLOS regulations in urban situations may require robust embedded software that is capable of detecting air collision hazards in realtime at near and far ranges as uncooperative small aircraft and other unpredictable small objects with fast-changing and unscheduled trajectories pose significant hazards to UAS. This work presents the concept and initial prototyping of a Digital Twin to evaluate the capability of UAS mounted LiDAR to detect small-object air collision risks. A Digital Twin of the Port of Hamburg is augmented with typical port and harbour aerial hazards such as birds, drones, helicopters, and low flying aircraft. The use case scenarios are created in Maya and Unity, with Optix ray tracing of typical LiDAR imaging configurations used to replicate the cause and effect relationship between different LiDAR specifications and their response to small flying objects. Our results demonstrate the inhomogeneous point clouds generated at different spatial-temporal parts of the LiDAR scanning cycle and field of view. These results confirm the challenges of detecting small uncooperative objects by LiDAR. © 2021 IEEE.

关键词： Hazards

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arXiv

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arXiv 2024年

作者： Lin, Zhenchao He, Li Yang, Hongqiang Sun, Xiaoqun Zhang, Guojin Chen, Weinan Guan, Yisheng Zhang, Hong School of Electromechanical Engineering Guangdong University of Technology Guangzhou China Department of Electronic and Electrical Engineering Southern University of Science and Technology China Shenzhen Key Laboratory of Robotics and Computer Vision China Meituan Technology Co. Ltd Shenzhen China

Large-scale point cloud consists of a multitude of individual objects, thereby encompassing rich structural and underlying semantic contextual information, resulting in a challenging problem in efficiently segmenting a point cloud. Most existing researches mainly focus on capturing intricate local features without giving due consideration to global ones, thus failing to leverage semantic context. In this paper, we propose a Similarity-Weighted Convolution and local-global Fusion Network, named SWCF-Net, which takes into account both local and global features. We propose a Similarity-Weighted Convolution (SWConv) to effectively extract local features, where similarity weights are incorporated into the convolution operation to enhance the generalization capabilities. Then, we employ a downsampling operation on the K and V channels within the attention module, thereby reducing the quadratic complexity to linear, enabling Transformer to deal with large-scale point cloud. At last, orthogonal components are extracted in the global features and then aggregated with local features, thereby eliminating redundant information between local and global features and consequently promoting efficiency. We evaluate SWCF-Net on large-scale outdoor datasets SemanticKITTI and Toronto3D. Our experimental results demonstrate the effectiveness of the proposed network. Our method achieves a competitive result with less computational cost, and is able to handle large-scale point clouds efficiently. The code is available at https://***/Sylva-Lin/SWCF-Net Copyright © 2024, The Authors. All rights reserved.

关键词： Convolution

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QTER: QoS-Aware Three-Dimensional Efficient and Reliable Routing for LEO Satellite Networks

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IEEE Internet of Things Journal 2025年

作者： Zheng, Jinkai Luan, Tom H. Li, Guanjie Zhang, Yanfeng Yuan, Mingfeng Pan, Jianping Dongguan University of Technology School of Electrical Engineering and Intelligentization China Xi’an Jiaotong University China Xidian University School of Cyber Engineering China Singapore University of Technology and Design Information Systems Technology and Design Pillar Singapore University of Toronto Institute for Aerospace Studies University of Toronto Robotics Institute Canada University of Victoria Department of Computer Science Canada

Low Earth Orbit (LEO) satellite networks offer a promising approach for achieving global coverage and high-speed Internet access. However, the existing communication frameworks within these networks may result in low robustness and reliability. This paper introduces QTER, a novel and lightweight routing framework specifically designed for LEO networks, aimed at addressing these challenges. Our contributions are threefold. First, QTER establishes a cost-effective and reliable routing framework that accommodates a variety of applications with distinct Quality of Service (QoS) requirements. By enabling multi-path routing, the framework minimizes costs while ensuring end-to-end reliability, thus enhancing adaptability to diverse service demands. Second, we leverage the unique structural characteristics of LEO satellite networks by modeling the satellite constellation as a three-dimensional network, wherein higher-shell satellites serve as management satellite nodes (MSNs) to coordinate routing strategies among lower-shell satellites. This architecture significantly improves system efficiency and adaptability. Third, we propose a failure recovery mechanism that allows MSNs to relay packets when lower-orbit satellites are rendered unavailable due to environmental factors, thereby enhancing system robustness. Extensive simulations demonstrate that QTER exhibits resilience to node failures and dynamic network conditions, achieving reductions in average cost and delay by 59.4% and 38.9%, respectively, compared to baselines. © 2014 IEEE.

关键词： Resource allocation

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