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检索条件"任意字段=3rd International Conference on Informatics in Control, Automation and Robotics"

共 2674 条记录，以下是11-20 订阅

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A Hybrid Nut Sorting System: Utilizing Machine Vision and Augmented Information for Efficient Human-Robot Collaboration 3

A Hybrid Nut Sorting System: Utilizing Machine Vision and Au...

引用

3rd international conference on Mechatronics, control and robotics, ICMCR 2025

作者： Sangchai, Kanisorn Adirekkittikun, Wongsakorn Vivatanaprasert, Kevin Boonpun, Methasit Chokthitirath, Wongpakorn Thipyophat, Nutdanai International School of Engineering Chulalongkorn University Robotics and Artificial Intelligence Faculty of Engineering Bangkok Thailand

ISBN: (纸本)9798331544546

Efficient sorting and classification of nuts is a critical task in various industries, yet current methods often rely on machine vision systems that inspect each nut individually, making the process time-consuming and inefficient. Additionally, most processes are fully automated, lacking the option for human monitoring or intervention. The novelty of this paper lies in the development of a hybrid nut sorting system that combines machine vision with augmented information to facilitate efficient human-robot collaboration. Unlike traditional fully automated systems that exclude human involvement, our approach integrates a projector-based visual aid to provide real-time, easily interpretable information for manual or semi-automated sorting. Additionally, the system incorporates a CoreXY robot path and mechanism, enabling collaboration between humans and robots. The detection system consistently identifies nuts of different sizes with reliable accuracy, particularly for simultaneous multi-object detection compared to singular detection methods. As a hybrid sorting system, our solution also allows humans to manually sort nuts at a faster rate than the machine while utilizing the system's assistance. © 2025 IEEE.

关键词： Collaborative robots

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2025 3rd international conference on Mechatronics, control and robotics

2025 3rd International Conference on Mechatronics, Control a...

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Mechatronics, control and robotics (ICMCR), international conference on

2025 3rd international conference on Mechatronics, control and robotics.

ISBN: (数字)9798331544546

ISBN: (纸本)9798331544553

2025 3rd international conference on Mechatronics, control and robotics.

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Designing Energy-Efficient Embedded Systems with CNNs for Real-Time control in Autonomous robotics 3

Designing Energy-Efficient Embedded Systems with CNNs for Re...

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3rd IEEE international conference on automation and Computation, AUTOCOM 2025

作者： Kumar, Sanjay Sharma, Priti Kalinga University Department of Cs & It Raipur India

ISBN: (纸本)9798331542375

This research proposes an energy-aware paradigm for the implementation of deep learning using CNN for real-time control in autonomous robotics for embedded systems. The overall power efficiency of the proposed system is achieved through efficient control of power consumption, latency, and runtime while has minor degradation in terms of accuracy through a number of approaches including model pruning, quantization, and adaptive CNN scaling. Studies show that power consumption has been cut down to as low as 47.3% thereby making the optimized system's power consumption in obstacle avoidance tasks as low as 2.8 W, the base system consuming up to 5.0 W power The delay was also lowered to 47.1% in key tasks from 20 ms, thus ensuring more immediate decisions in real time activities. Also, the system up time was enhanced by 40% to perform operations including object identification and sensors integration. Accuracy stayed over 92% in all tasks;the fully optimized CNN design was 0.6% less accurate than an ideal 95.0%, with a 92.4% score. These results endorse that much energy savings and performance improvement are realizable whilst incurring moderate costs on the precision of RTAS, which makes this approach perfect for battery operated, constraint embedded systems in 'smart' robotics. © 2025 IEEE.

关键词： Energy utilization

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Zonotope-based fault estimation for Lipschitz nonlinear systems 3

Zonotope-based fault estimation for Lipschitz nonlinear syst...

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2024 3rd international conference on Aerospace and control Engineering, ICoACE 2024

作者： Ma, Siyuan Zhang, Wei Jiang, Qiang Gao, Sheng School of Automatic and Electrical Engineering Shenyang Ligong University Shenyang110158 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China China-Portugal Belt and Road Joint Laboratory on Space & Sea Technology Advanced Research Shanghai200120 China

An estimation of fault intervals using a T-N-L structured observer is suggested for Lipschitz nonlinear systems. By augmenting state vectors, the augmentation system and its observer are established, enabling the observer to concurrently estimate fault and system states. The L∞ performance is applied to enhance the resilience of the fault interval estimation to external disturbances and unanticipated inputs. An adequate requirement for the observer design is also presented. The interval estimation of states and faults is ultimately created by using a zonotope. The proposed method exhibits advantages and feasibility when compared to existing simulation techniques. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Nonlinear systems

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The Impact of Ultra-Wideband Sensors in Industrial automation and robotics Applications 3

The Impact of Ultra-Wideband Sensors in Industrial Automatio...

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3rd IEEE international conference on automation and Computation, AUTOCOM 2025

作者： Chaudhary, Pavan Sidhu, Amritpal Nayak, Chinmayee Das, Sidhant Kantharaj, I.K. Thapa, K.Naresh Kumar Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Centre for Artificial Intelligence and Machine Learning Odisha Bhubaneswar India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh Baddi174103 India Karnataka Bangalore India Sathyabama Institute of Science and Technology Department of Electrical and Electronics Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331542375

Ultra-Wideband Technology has garnered a reputation as an enabler of advancing industrial automation and robotics applications. UWB sensors emit short pulses of electromagnetic radiation to measure and can deliver highly accurate and real-time data over long distances. Compared to other sensing technologies, UWB sensors have a remarkably broad frequency spectrum and provide high data rates at low power. There are several advantages of UWB sensors implemented in industrial automation and robotics. These are done in a lab with some reference;you can take the data offline. UWB sensors can complement and be used in integration with other technologies, such as lidar or vision systems, to achieve higher performance results for a complete perception of the environment. This allows better and more efficient decision-making for autonomous systems. UWB sensors deliver highly accurate and repeatable measurements for robotic movement monitoring and control. They are also used for asset monitoring and inventory control, which finally help logistics & SCM. UWB sensors also improve workplace safety by warning about potential collisions or other hazardous conditions. © 2025 IEEE.

关键词： Electromagnetic pulse

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Sugar Cane Yield Prediction Using Drone Data Processed by LSTM Algorithm 3

Sugar Cane Yield Prediction Using Drone Data Processed by LS...

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3rd international conference on Mechatronics, control and robotics, ICMCR 2025

作者： Arakawa, Kotetsu Shimizu, Ryusei Kikuchi, Shota Capi, Genci Hosei University Graduate School of Science and Engineering Dept. of Mechanical Eng. Tokyo Japan

ISBN: (纸本)9798331544546

Sugarcane is an essential crop in southwestern Japan, particularly in Okinawa and Kagoshima, where it sustains local economies and supports large-scale sugar production. Traditional yield prediction relies on labor-intensive field surveys and is increasingly challenged by a shortage of skilled labor, resulting in potential inaccuracies. This work proposes an innovative approach to sugarcane yield prediction by combining Long Short-Term Memory (LSTM) models with Genetic Algorithms (GA) to optimize model performance. Drone-based data collection methods are also explored, leveraging aerial imagery to provide additional predictive features. The proposed model demonstrates the effectiveness of integrating time-series and spatial data, offering a scalable and accurate solution for improving yield forecasting and supporting efficient operations in sugarcane production. © 2025 IEEE.

关键词： 3D Map building Drone navigation Sugar cane yield prediction

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Latent 3D Scene Graph with Aligned Visual-Language Perception for Object-Goal Navigation 3

Latent 3D Scene Graph with Aligned Visual-Language Perceptio...

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3rd international conference on Mechatronics, control and robotics, ICMCR 2025

作者： Zhang, Jianwei Zhou, Kang Yang, Junjie Li, Xiaojian College of Engineering Southern University of Science and Technology Shen Zhen China School of Computer Science City University of Hong Kong Hong Kong Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shen Zhen China

ISBN: (纸本)9798331544546

Object-goal navigation requires agents to accurately locate and navigate to specified target objects in complex indoor environments. Existing methods primarily rely on single visual observations or simple semantic matching, making it difficult to effectively understand 3D scene relationships between target objects, which leads to inefficient path planning during navigation. Furthermore, the feature discrepancy between visual and language modalities poses challenges for accurate target identification. To address these issues, we propose Latent 3D Scene Graph with Aligned Visual-Language Perception (LSGAP), a novel approach that explicitly models 3D scene relationships between objects through depth perception and latent 3D scene graph construction. Meanwhile, we leverage multimodal pretraining strategies to achieve effective visual-language feature alignment, enhancing the model's target recognition capabilities. This end-to-end architectural design improves spatial cognition ability and enables more efficient navigation decision-making. We conduct extensive experimental evaluations in the AI2THOR interactive environment to validate the effectiveness of our navigator. © 2025 IEEE.

关键词： Depth perception

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Modeling and Nonlinear Coordinated Stabilizing control for Dual Ship-Mounted Cranes Subject to Roll and Heave Motions 17th

Modeling and Nonlinear Coordinated Stabilizing Control for D...

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17th international conference on Intelligent robotics and Applications

作者： Yang, Ling Ma, Xin He, Xin Zhang, Lei Yang, Xue Shandong Univ Sch Control Sci & Engn Engn Res Ctr Intelligent Unmanned Syst Ctr RobotMinist Educ 17923 Jingshi Rd Jinan 250061 Peoples R China Shandong Marine Grp Ltd 7000 Jingshi Rd Jinan 250022 Peoples R China Shandong Marine Grp Technol Co Ltd 300 Changjiang Rd Yantai 264006 Peoples R China

ISBN: (纸本)9789819607976;9789819607983

Wave-induced ship heave and roll motions pose great challenges for the design of control systems of dual ship-mounted cranes (DSCs) along with complicated nonlinearities and physical constraints. Aiming at the above issues, this paper establishes the dynamic model of DSCs subject to ship roll and heave motions and proposes a nonlinear coordinated stabilizing controller which could achieve precise positioning and swing-elimination. First, the DSCs dynamic model considering ship roll and heave motions is built by utilizing the Lagrange method. On the basis of the dynamic model, the system energy function consisting of the kinetic and potential energy is introduced. With the first-order derivation of the energy function, explicit expressions of ship-to-ship interaction forces caused by ship motions are derived. These forces are then incorporated into the controller to mitigate the effects between the two ships, thereby achieving coordinated control of the two cranes during payload transportation. Lyapunov techniques are used to rigorously prove the stability of the control system. Finally, numerous simulations verify the effectiveness of the proposed controller.

关键词： Dual ship-mounted crane systems Boom crane Nonlinear systems Motion control Wave disturbances

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Adaptive Reduced Fuzzy Decoupling control for Lower Limb Exoskeleton with Uncertainties 3rd

Adaptive Reduced Fuzzy Decoupling Control for Lower Limb Exo...

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3rd international conference on Advances in Information and Communication Technology, ICTA 2024

作者： Nguyen, Van-Truong Tran, Duc-Duong Le, Ngoc-Duy Dang, Van-Truong School of Mechanical and Automotive Engineering Hanoi University of Industry Hanoi Viet Nam Faculty of Engineering Technology Hung Vuong University Viet Tri Viet Nam

ISBN: (纸本)9783031809422

In this paper, an adaptive reduced fuzzy decoupling controller is developed for a lower limb rehabilitation exoskeleton robot (2-DOF) in the case of uncertainties. With decoupled control, the initial overall MIMO system is separated into a set of individual MISO subsystems for independent control. A simplified adaptive fuzzy is proposed to reduce computation time, addressing the issues of traditional fuzzy systems. The controller has good control quality, tracking the human gait motion trajectory with uncertainty. Simulation results show that the proposed controller performs better than the traditional fuzzy controller. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Exoskeleton (robotics)

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Neural Network-Based Adaptive Tracking control for Marine Lifting Arm System 17th

Neural Network-Based Adaptive Tracking Control for Marine Li...

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17th international conference on Intelligent robotics and Applications

作者： Wang, Kai Ma, Xin He, Xin Zhang, Lei Yang, Xue Shandong Univ Minist Educ Engn Res Ctr Intelligent Unmanned Syst Ctr RobotSch Control Sci & Engn 17923 Jingshi Rd Jinan 250061 Peoples R China Shandong Marine Grp Ltd 7000 Jingshi Rd Jinan 250022 Peoples R China Shandong Marine Grp Technol Co Ltd 300 Changjiang Rd Yantai 264006 Peoples R China

ISBN: (纸本)9789819607976;9789819607983

The marine lifting arm system is a novel type of lifting equipment for the dismantling of large offshore platforms. In practical application, the marine lifting arm system is commonly subject to unexpected disturbances such as persistent vessel-induced disturbances, uncertain dynamics, and physical constraints, posing significant challenges for controller system design. This paper proposes a neural network (NN) based adaptive tracking control method with state constraints for the marine lifting arm system to effectively compensate for vessel motions induced by wave disturbances. First, the dynamic model of a marine lifting system is established by employing Lagrange's method. Subsequently, a nonlinear controller is developed based on the dynamic model to compensate for 3-DOF vessel motions, including heave, roll, and pitch motion. By constructing constrained terms, the nonlinear controller effectively restricts the lifting arm's motion within the predefined range, ensuring the safety of lifting operations even under adverse sea conditions. The neural network is employed to estimate parameter/structure uncertainties and the nonlinear input dead zones for lifting arm systems. In particular, the designed update law of the neural network considers physical constraints, thereby further ensuring that the lifting arm operates within the safe range. The theoretical stability of the proposed control system is rigorously proven using the Lyapunov technique. Finally, the practicality and effectiveness of the proposed method are verified by the hardware experiments on a self-built offshore lifting system.

关键词： Marine lifting system Tracking control Nonlinear controller State constraint

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