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Image Segmentation System of Soft Capsules Based on Deep Learning

Journal of Institute of control, robotics and Systems 2024年第6期30卷 607-613页

作者： Jung, Young-Gil Park, Tae-Hyoung Department of Control and Robot Engineering Chungbuk National University Korea Republic of Department of Intelligent Systems and Robotics Chungbuk National University Korea Republic of

Pharmacists in conventional pharmacies and hospitals prepare and visually inspect medications before dispensing these medications to patients, thereby posing risks of exposure through skin contact or inhalation, as well as the potential for generating compounding errors such as incorrect medication types or quantities. To address the limitations of the manual compounding processes, automated compounding and medication-verification systems have been introduced and implemented. The automated compounding system prepares medications in pouch units based on prescriptions written by doctors, whereas the medication verification system verifies whether the types and quantities of the medication dispensed in these pouches match the prescription information. Medications are categorized broadly into solid tablets, hard capsules, and soft capsules. Color and shape information is used to classify medication types;solid tablets and hard capsules can be classified using rule-based image processing techniques such as image binarization. However, extracting shape information from soft capsules through which light passes is impossible via image binarization alone;therefore pattern matching is employed. Nevertheless, soft capsules change their forms, causing significant variations in pattern-matching similarity;therefore the detection accuracies of these capsules are low. To address this issue, this paper proposes a deep learning-based method for detecting soft capsules. © ICROS 2024.

关键词： Pattern matching

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Output Tracking control of a Nonlinear System Based on Takagi-Sugeno Fuzzy Model: Generalized Partial Eigenstructure Assignment Approach

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IEEE Access 2024年 12卷 18520-18535页

作者： Soltanian, Farzad Shasadeghi, Mokhtar Mobayen, Saleh Skruch, Pawel University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2M9 Canada Shiraz University of Technology Electrical Engineering Faculty Shiraz71557-13876 Iran National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Yunlin Douliu64002 Taiwan AGH University of Science and Technology Department of Automatic Control and Robotics Kraków30-059 Poland

This paper introduces an innovative optimal control approach to achieve output tracking while incorporating H2-performance specifications in a specific class of nonlinear dynamics modeled by the Takagi-Sugeno fuzzy model (TSFM). The primary innovation lies in extending partial eigenstructure assignment to TSFM-based nonlinear systems within the framework of sliding mode control (SMC). We propose a two-step methodology for designing optimal sliding surface gains. Initially, optimal state feedback gains are computed for each rule consequence containing a linear subsystem, adhering to predetermined eigenvalues and satisfying H2-performance criteria. Subsequently, using a convex combination, the overall state feedback gain is calculated and utilized to design sliding matrix gains. The sliding matrix gains are then determined by strategically combining previously calculated state-feedback gains in a convex optimization problem. We reframe the output tracking strategy as a stabilization problem using a virtual control input and reformulate the optimization task concerning tracking state errors. This process yields state feedback gains, sliding gains, and the formulation of the virtual control input. The effectiveness of our approach is verified through comprehensive simulations, emphasizing its capability in addressing output tracking challenges within nonlinear systems. © 2013 IEEE.

关键词： Transient analysis

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Improving Collision-Free Success Rate For Object Goal Visual Navigation Via Two-Stage Training With Collision Prediction

arXiv

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arXiv 2025年

作者： Lian, Shiwei Zhang, Feitian Robotics and Control Laboratory Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory of Turbulence and Complex Systems Peking University Beijing100871 China

The object goal visual navigation is the task of navigating to a specific target object using egocentric visual observations. Recent end-to-end navigation models based on deep reinforcement learning have achieved remarkable performance in finding and reaching target objects. However, the collision problem of these models during navigation remains unresolved, since the collision is typically neglected when evaluating the success. Although incorporating a negative reward for collision during training appears straightforward, it results in a more conservative policy, thereby limiting the agent’s ability to reach targets. In addition, many of these models utilize only RGB observations, further increasing the difficulty of collision avoidance without depth information. To address these limitations, a new concept—collision-free success is introduced to evaluate the ability of navigation models to find a collision-free path towards the target object. A two-stage training method with collision prediction is proposed to improve the collision-free success rate of the existing navigation models using RGB observations. In the first training stage, the collision prediction module supervises the agent’s collision states during exploration to learn to predict the possible collision. In the second stage, leveraging the trained collision prediction, the agent learns to navigate to the target without collision. The experimental results in the AI2-THOR environment demonstrate that the proposed method greatly improves the collision-free success rate of different navigation models and outperforms other comparable collision-avoidance methods. Copyright © 2025, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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Motion Planning of Planar Snake Robots in Viscous Environments

Motion Planning of Planar Snake Robots in Viscous Environmen...

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2022 American control Conference, ACC 2022

作者： Itani, Omar Shammas, Elie Jaoude, Dany Abou American University of Beirut Vision and Robotics Lab Department of Mechanical Engineering Beirut Lebanon American University of Beirut Control and Optimization Lab Department of Mechanical Engineering Beirut Lebanon

ISBN: (数字)9781665451963

ISBN: (纸本)9781665451963

In this paper, a systematic motion planning algorithm for planar under-actuated hyper-redundant snake robots in viscous environments is presented. The proposed algorithm generates shape trajectories, i.e., continuous trajectories in the base (shape) space of the snake, that ensure the tracking of desired trajectories defined in the fiber (motion) space of the snake. The proposed motion planning algorithm is formulated as an optimization problem which minimizes the joint velocities. This cost function is also utilized to avoid singular configurations. Finally, the proposed algorithm is validated through simulations using a five-link snake robot. © 2022 American Automatic control Council.

关键词： Trajectories

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Marine Surface Layer Optical Turbulence Measurements Over a Vertical Path with Mobile Aerial Platforms

Marine Surface Layer Optical Turbulence Measurements Over a ...

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2024 Laser Applications Conference, LAC 2024

作者： Maa, Winston Avramov-Zamurovic, Svetlana Lee, Peter Solie, John van Iersel, Miranda Weapons Robotics and Control Engineering Department United States Naval Academy Hopper Hall 597 McNair Rd AnnapolisMD21402 United States Klipsch School of Electrical and Computer Engineering New Mexico State University Las CrucesNM88003 United States

A mobile aerial platform is used in a laboratory environment at a distance of up to 4 meters to record the Gaussian laser light intensity fluctuations from a downlink and calculate scintillation index. © 2024 The... 详细信息

关键词： Laser recording

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A Review on Inverse kinematics Solution of Robotic Arm Movement 17

A Review on Inverse kinematics Solution of Robotic Arm Movem...

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17th International Conference on Signal-Image Technology and Internet-Based Systems, SITIS 2023

作者： Singh, Gurjeet Banga, Vijay Kumar Yingthawornsuk, Thaweesak Lovely Professional University School of Electrical and Electronics Engineering Department of Robotics and Control Punjab India Chandigarh University Chandigarh India King Mongkut's University of Technology Thonburi Department of Media Technology Bangkok Thailand

ISBN: (纸本)9798350370911

Across industries, ROBOTS are frequently utilized. A significant part of the numerous uses of robotics and many countries deciding that whether it's possible to give identity to the anthropomorphic robots. Different industries hospitals are using the robots. The robots are not limited to these two applications even different sectors are using the different robots according to their needs. Mostly robots are performing the tasks which are difficult for human being. The basic robotic arms, known as three link manipulators, are still in use in micro-to-macro applications, such as chip production. In the field of robotics, robotic instrumentation is essential because without sensors, actuators, and detectors, robots cannot interact with their surroundings. In this paper soft computing also discussed in detail. In this paper the disturbance occur in the closed loop also being discussed. There have been tests, comparisons, and simulations *** doesn't have to be an expert in the system. Even in cases when the population is quite big, the evolutionary process converges too soon. The robotic arm reaches the desired location within the simulated time, demonstrating good performance. Since the evolution function thoroughly tests all potential input spaces, the performance is ideal across the board. Soft computing help in trajectory planning and obstacle avoidance has been discussed in detail. The role of hybrid techniques also discussed. The dynamic nature of the robot also been discussed in detail in this paper. The paper has been sub parted in 9 parts and the modelling of the 2,3, and 5 DOF robots has been discussed din detail. © 2023 IEEE.

关键词： End effectors

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TinyML Speech Classification Embedded Ai Module for Hand Rehabilitation Device 3

TinyML Speech Classification Embedded Ai Module for Hand Reh...

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3rd International Conference on Mechatronics, control and robotics, ICMCR 2025

作者： Numsomran, Arkorn Numsomran, Arjin Chaoraingern, Jutarut Triam Udom Suksa Pattanakarn Suvarnabhumi School Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Instrumentation and Control Engineering Bangkok Thailand School of Engineering King Mongkut's Institute of Technology Ladkrabang Department of Robotics and AI Engineering Bangkok Thailand

ISBN: (纸本)9798331544546

Recent advancements in artificial intelligence and machine learning have significantly improved healthcare, especially in the development of assistive technologies for rehabilitation. This paper introduces a method for hand rehabilitation that utilizes the capabilities of tiny machine learning to enhance speech classification in a rehabilitation device. The proposed method employs a CNN model capable of classifying speech signals that are indicative of different hand movement patterns. Patients emit these speech signals during prescribed hand exercises, which are crucial for their rehabilitation process. The main focus of this study is on training and deploying a speech classification system that can work in the resource-limited environment of TinyML platforms. We detail the process of capturing speech data, preprocessing it, and extracting the most features relevant to different hand movements. Our results show that using TinyML to help with hand rehabilitation works. The method we came up with shows how TinyML could change the way rehabilitative devices are controlled, and it also shows us what personalized and easy-to-use rehabilitation tools might look like in the future. © 2025 IEEE.

关键词： Human rehabilitation equipment

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Coverage Path Planning of Agricultural Spraying Drones with Graph Convolutional Network

Coverage Path Planning of Agricultural Spraying Drones with ...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Amirmasood Khaloujini Amin Talaeizadeh Alireza Taheri Aria Alastya Advanced Research Lab for Control and Agricultural Robotics Department of Mechanical Engineering Social and Cognitive Robotics Lab. Sharif University of Technology Tehran Iran

ISBN: (数字)9798331529734

ISBN: (纸本)9798331529741

Optimal route planning for autonomous robots is a crucial element of contemporary agriculture, especially for activities like spraying and pollination. This paper presents a Graph Convolutional Network (GCN) model especially developed to address the Coverage Path Planning (CPP). The aim of this paper is to convert the CPP problem into a Traveling Salesman Problem (TSP), so that by solving the TSP using the proposed neural network, an optimal route can be extracted for each agricultural field in the shortest possible time and with sufficient accuracy, ensuring full coverage of the field's area. The proposed model is a GCN, augmented with a transformer layer and a Multi-Layer Perceptron (MLP), was trained using datasets produced by a Genetic Algorithm (GA) Method. The model obtained a network error of 0.12 while solving TSP cases with 20 points. It showed robust generalization skills, as evidenced by validation and test errors of 0.1261 and 0.1264, respectively. Significantly, the GCN model reduces the solution time to approximately one-tenth compared to conventional approaches, a benefit that increases as the number of points increases. The effectiveness of the model in producing ideal coverage routes highlights its potential for wider use in optimization and coverage path planning, especially in dynamic and extensive agricultural environments.

关键词： Training Accuracy Graph convolutional networks Neural networks Spraying Traveling salesman problems Transformers Path planning Vehicle dynamics Genetic algorithms

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Towards Efficient Path Finding and Moving Stability-Focused Trajectory Planning for Mobile Robots

Towards Efficient Path Finding and Moving Stability-Focused ...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Hou, Muyang Lei, Zhenya Hu, Haidong Wang, Zhong Wang, Yong Xie, Le Wang, Hesheng Shanghai Jiao Tong University Department of Automation Shanghai200240 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China Beijing Institute of Control Engineering Beijing100190 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Department of Automation Shanghai200240 China

ISBN: (纸本)9781665481090

Nowadays, mobile robots play an important role in a variety of service scenarios. They need to plan and track trajectories to accomplish tasks such as delivery or guided tours. In such tasks, there are two remaining challenges: on one hand, the time and memory consumption of present path planners are still significant;on the other hand, service robots, which have a higher center of gravity, demand greater moving stability than that of current trajectory planners provide. To address these two challenges. Firstly, we propose a safety boundary first A∗ which fully utilizes environmental obstacle information to create a safety boundary and searches in it to quickly find an initial path. Secondly, we formulate the trajectory optimization problem as a nonlinear optimization problem, where the smoothness, safety, feasibility, and moving stability of the robot are taken into account. Furthermore, to constrain the robot's lateral acceleration, we design a time allocation algorithm based on non-uniform B-spline, enhancing the quality of the resulting trajectory. Simulations and real-world experiments demonstrate that our algorithms significantly improve path search efficiency, enhance moving stability, reduce the difficulty of tracking, and improve the quality of task completion. © 2024 IEEE.

关键词： Trajectories

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control Contraction Metrics on Submanifolds 63

Control Contraction Metrics on Submanifolds

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Wu, Dongjun Yi, Bowen Manchester, Ian R. Lund University Department of Automatic Control Box 118 LundSE-221 00 Sweden Polytechnique Montreal Department of Electrical Engineering & Gerad QCH3T 1J4 Canada The University of Sydney Australian Centre for Robotics School of Aerospace Mechanical and Mechatronic Engineering Australia

ISBN: (纸本)9798350316339

In this paper, we extend the control contraction metrics (CCM) approach, which was originally proposed for the universal tracking control of nonlinear systems, to those that evolves on submanifolds. We demonstrate that the search for CCM on submanifolds can be reformulated as convex conditions. In particular, since Lie groups can be viewed as submanifolds in Euclidean space, the results are directly applicable to this setting. © 2024 IEEE.

关键词： Nonlinear simulations

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