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IEEE International Conference on robotics and Automation (ICRA)

作者： Alireza Sarmadi Prashanth Krishnamurthy Farshad Khorrami Department of Electrical and Computer Engineering Control/Robotics Research Laboratory (CRRL) NYU Tandon School of Engineering Brooklyn NY

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In this paper, we propose a method to automatically and efficiently tune high-dimensional vectors of controller parameters. The proposed method first learns a mapping from the high-dimensional controller parameter space to a lower dimensional space using a machine learning-based algorithm. This mapping is then utilized in an actor-critic framework using Bayesian optimization (BO). The proposed approach is applicable to complex systems (such as quadruped robots). In addition, the proposed approach also enables efficient generalization to different control tasks while also reducing the number of evaluations required while tuning the controller parameters. We evaluate our method on a legged locomotion application. We show the efficacy of the algorithm in tuning the high-dimensional controller parameters and also reducing the number of evaluations required for the tuning. Moreover, it is shown that the method is successful in generalizing to new tasks and is also transferable to other robot dynamics.

关键词： Legged locomotion Machine learning algorithms Heuristic algorithms Dynamics Aerospace electronics Vectors Quadrupedal robots

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Degradable Tracking System based on Hardware Multi-Model Estimators

Degradable Tracking System based on Hardware Multi-Model Est...

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2022 Resilience Week, RWS 2022

作者： Kiriakidis, Kiriakos Croteau, Brien Severson, Tracie Rodriguez-Seda, Erick Robucci, Ryan Islam, Riadul Rahman, Saad United States Naval Academy Department of Weapons Robotics and Control Engineering Department of Cyber Science United States University of Maryland Department of Computer Science and Electrical Engineering United States

ISBN: (数字)9781665488198

ISBN: (纸本)9781665488198

Sensing systems onboard unmanned vehicles operate in an environment of constrained computational resources. A cyber-Attack may primarily aim to degrade these computing devices and, ultimately, incapacitate the sensing system itself. To prepare a prototype tracking system for degradation, this paper proposes distributed hardware implementation of a Multiple Model estimator on two FPGA units and, after an attack, adaptation of the estimator by leveraging Dynamic Partial Reconfiguration of the single surviving FPGA. The method ensures that the most likely models of the estimator are loaded on to the fabric of the surviving FPGA with minimal interruption. © 2022 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Human-Centered Design and Development of an Elderly Care Robot

Human-Centered Design and Development of an Elderly Care Rob...

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Ali Sajid Muhammad Noor Sultan Muhammad Muaviz Ishfaq Ali Raza Department of Mechatronics and Control Engineering Human Centered Robotics Lab of NCRA University of Engineering and Technology Lahore Lahore Pakistan

ISBN: (数字)9798350355703

ISBN: (纸本)9798350355710

Constituting to the demographic age shift in many regions of the world, technological advancement in the care sector, to deliver quality services to the elders, is now in more demand than ever. One such advancement is the evolution of socially assistive and care robots that promise sustainable, reliable, and safe human-robot interaction to meet geriatric needs. This paper presents the design and development of Silver Companion: a geriatric care robot for the elderly. The target audience chosen for the research phase is the socially isolated elderly community of East Asia and Central Europe which make up about 45% of their total elderly population. Considering the human-centered design paradigm, the technical and psychological aspects of the robot have been devised. The form and functions of the robot have been based on the product design principles. The whole development journey has been subjected to the identified elderly needs and the robot has been tested under multiple use-case scenarios, ideated for possibly fulfilling those needs. The robot has been equipped with assistive and interactive features like voice interaction, complementing micro-gestures and robot expressions, seamless navigation, and robot perception enhanced by a tilt-pan mechanism, all contributing towards making the robot capable of uplifting the well-being and quality of life of seniors.

关键词： Industries Silver Service robots Navigation Psychology Human-robot interaction Product design Reliability Older adults Geriatrics

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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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Compact camera module cover defect classification using quadtree decomposition based deep learning

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Journal of Institute of control, robotics and Systems 2021年第8期27卷 626-632页

作者： Ha, Min-Ho 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

Compact camera modules are used in many small electronic devices. Defect detection is essential because the cover protecting the module is exposed to the environment outside. It also defects classification to provide feedback to the production process and prevent further defects from occurring. Since the size of the defect is small compared to the size of the module, we adopted the method of extracting the inspection patch. To reduce the inspection time, we employed the compact camera module defect classification system using quadtree decomposition. The module area was detected using template matching, and the unnecessary background was deleted through bit operation. By binarizing the detected module areas, defect candidates were found through quadtree decomposition. The defects were then classified through deep learning. Compared to the previously proposed patch-based method, the inspection time could be reduced. © ICROS 2021.

关键词： Defects

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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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