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CPL-SLAM: Centralized Collaborative Multi-Robot Visual-Inertial SLAM Using Point-and-Line Features

IEEE Internet of Things Journal 2025年

作者： Liu, Xin Wen, Shuhuan Liu, Huaping Richard Yu, F. Yanshan University Engineering Research Center The Ministry of Education for Intelligent Control System and Intelligent Equipment Key Lab of Intelligent Rehabilitation and Neuroregulation in Hebei Province Department of Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Tsinghua University Department of Computer Science and Technology Beijing100084 China Shenzhen University College of Computer Science and Software Engineering China Carleton University Canada

Traditional visual-inertial SLAM (Simultaneous Localization and Mapping) systems predominantly rely on feature point matching from a single robot to realize the robot pose estimation and environment map construction. However, in complex scenarios, these traditional systems struggle with issues such as tracking failures due to illumination changes, rapid movements, and low-texture environments, and they perform poorly in terms of mapping efficiency and global consistency. To address these challenges, we propose a centralized collaborative SLAM system that employs both point and line features for tracking in the robot and map fusion in the cloud. The proposed system leverages the fusion of point and line features across all instances in the process, which allows our method to achieve higher localization accuracy in structured, low-texture scenes. With the aid of classifying gravity-aligned vertical lines and spatial parallel lines, the proposed system can deliver faster and more accurate odometry in complex scenes. Furthermore, we developed intra-robot and inter-robot loop closure detection methods based on point and line features, generating a globally consistent sparse point cloud and structured scene map in the cloud. Our method is able to build richer maps while improving accuracy compared to existing methods. Experimental results on public datasets and in real-world environments show that, compared to existing advanced methods, our approach demonstrates better performance. © 2014 IEEE.

关键词： SLAM robotics

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Emotional Interaction Between Human and Robot

Emotional Interaction Between Human and Robot

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Ali Nasir Jamilu Umar Yahaya Abdulrazaq Nafiu Abubakar Control & Instrumentation Engineering Department King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Interdisciplinary Research Centre for Intelligent Manufacturing and Robotics King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

With a goal to encourage task compliance and improve well-being, this research proposes a Markov Decision Process (MDP) model for socially assistive robots (SARs) to enable emotionally meaningful interactions with human users. The model considers the emotional states of the robot as well as the emotional and attentional states of the human user together with the effect of other people in the surroundings, therefore affecting the efficacy of the interaction. An adaptive decisionmaking method is provided by using human attention dynamics and emotional transitions to let the robot dynamically change its emotional state and tactics in real-time. This study focuses primarily on the emotional behavior of the human, the future study will entail the detailed set of actions to be executed by the human. The study incorporates an online learning system to dynamically update transition probabilities, therefore adjusting to fluctuations in human emotional reactions. The model was verified using a simulation-based case study to show its capacity to produce an optimum strategy for persuasive encounters under different environmental settings.

关键词： Learning systems Adaptation models Fluctuations Markov decision processes Decision making Human-robot interaction Assistive robots Real-time systems Behavioral sciences Robots

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Comparative Analysis of Different Sliding Mode control Approaches for Load Frequency control in Edge of the Grid system

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IET Generation, Transmission and Distribution 2025年第1期19卷

作者： Aich, Pritom Ahmed, Anis Shah, Rakibuzzaman Islam, Md Rabiul Roy, Naruttam Kumar Nasir, Ali Department of Electrical and Electronic Engineering Daffodil International University Dhaka Bangladesh Department of Electrical and Electronic Engineering Khulna University of Engineering & Technology Khulna Bangladesh Federation University Australia Mt HelenVIC Australia School of Electrical Computer and Telecommunications Engineering University of Wollongong WollongongNSW Australia Control and Instrumentation Engineering Department King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Interdisciplinary Research Center for Intelligent Manufacturing and Robotics King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia

The integration of renewable energy sources (RESs) at the edge of the grid plays a contributory role in advancing the transition to a sustainable energy future. However, this transition introduces significant variability, which challenges the maintenance of frequency stability in power systems. To address the impacts of RES variability, various robust control strategies have been developed. This paper compares the performance of different advanced sliding mode control (SMC) approaches, i.e., super twisting (ST) algorithm-based second order sliding mode control (STSOSMC), second order sliding mode control (SOSMC), double integral sliding mode control (DISMC) and integral sliding mode control (ISMC) with conventional sliding mode control (SMC) for load frequency control with stochastic RESs such as biogas generators (BG) and wind-based doubly fed induction generators (DFIG). The impact of the advanced sliding mode controllers on the voltage and rotor angle stability of the system is also explored. The efficacy of the controllers is tested under different load disturbances, considering nonlinearities such as communication delay (CD), sensor inaccuracy (SI), governor dead band (GDB), and generation rate constraint (GRC). The results demonstrate that STSOSMC achieves superior frequency regulation with minimal chattering and outperforms other controllers in terms of settling time, overshooting, and undershooting in frequency deviation. The result also demonstrates the effectiveness of STSOSMC in managing the variability and disturbances of RESs. Therefore, it could be considered the most robust control mechanism from the edge of the grid system with high penetration of RESs. © 2025 The Author(s). IET Generation, Transmission & Distribution published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Robust control

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A KNOWLEDGE-BASED APPROACH TO MODELING OF ROBOTIC ASSEMBLY CELLS

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ROBOTICA 1991年第1期9卷 31-42页

作者： KIM, DW LEE, BH KO, MS Robotics and Intelligent Systems Laboratory Department of Control and Instrumentation Engineering Seoul National University Seoul 151–742 (Korea)

In this paper, an approach to modelling of a robotic assembly cell is proposed and a method for managing the cell operation is described using a knowledge base. Since the modelling structure is based on the concept of the state variable, the relationships between states are described by the state transition map (STM). The knowledge-bases for state transition and assembly job information are obtained from the STM and the assembly job tree (AJT), respectively. Using the knowledge-base, the system structure is discussed in relation to both managing the cell operation and evaluating the performances. Finally, a simulation algorithm is presented with the simulation results to show the significance of the proposed modelling approach.

关键词： MODELING ASSEMBLY CELLS robotics KNOWLEDGE-BASE STATE TRANSITION

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An intelligent Robot Assisting Medical Practitioners to Aid Potential Covid-19 Patients 6

An Intelligent Robot Assisting Medical Practitioners to Aid ...

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6th International Conference on Image Information Processing, ICIIP 2021

作者： Sowrabh, S. Rameshkumar, Ashith Athira, P.V. Jishnu, T.B. Anish, M.N. UPES MTech in Robotics and Automation School of Engineering Dehradun India NSSCE Bachelor of Technology in Instrumentation Control Engineering Department Palakkad India Assistant System Engineer-trainee TCS Limited Kochi India NSSCE Instrumentation Control Engineering Department Palakkad India

ISBN: (纸本)9781665433617

The purpose of this paper is to develop a robot-nurse capable of assisting human health professionals in a COVID-19 isolation unit such that health care professionals may discontinue wearing the personal protective kit that they previously wore when dealing with patients at isolation units. The robot can perform most of the tasks carried out by human nurses in a hospital. It can take a patient's temperature without touching them, administer medicines at the appropriate time, assist in sanitizing the individual and their hands, and offer a section for sterilizing medical equipment. [14] © 2021 IEEE.

关键词： Nursing

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Fuzzy inference-based reinforcement learning of dynamic recurrent neural networks

Fuzzy inference-based reinforcement learning of dynamic recu...

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SICE Annual Conference

作者： Hyo-Byung Jun Dong-Wook Lee Dae-Joon Kim Kwee-Bo Sim Robotics and Intelligent Control System Lab Department of Control and Instrumentation Engineering Chung-Ang University Seoul South Korea

ISBN: (纸本)0780342089

This paper presents the fuzzy inference-based reinforcement learning algorithm of dynamic recurrent neural network, similar to the psychological learning scheme of the higher animals. The proposed method follows the way linguistic and conceptional expressions have an effect on human's behavior by reasoning reinforcement based on fuzzy rules. The intervals of fuzzy membership functions are found optimally by genetic algorithms. By using the recurrent neural network composed of dynamic neurons as action-generation network, not only the current state but also the past state is considered to make an action in dynamical environment. We show the validity of the proposed learning algorithm by applying it to the inverted pendulum control problem.

关键词： Learning Recurrent neural networks Fuzzy neural networks Heuristic algorithms Inference algorithms Psychology Animals Fuzzy reasoning Genetic algorithms Neurons

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Artificial immune network-based cooperative control in collective autonomous mobile robots

Artificial immune network-based cooperative control in colle...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Dong-Wook Lee Kwee-Bo Sim Robotics and Intelligent Information System Laboratory Department of Control and Instrumentation Engineering Chung Ang University Seoul South Korea

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system (DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying the immune system to DARS, a robot is regarded as a B lymphocyte (B cell), each environmental condition as an antigen and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows: when the environmental condition changes, a robot selects an appropriate behavior strategy, and its behavior strategy is stimulated and suppressed by other robot using communication. Finally, such stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis, and it is used for decision making of an optimal swarm strategy.

关键词： intelligent networks Mobile robots Immune system control systems intelligent robots Mobile communication Decision making Humans Robot sensing systems intelligent systems

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Behavior learning and evolution of collective autonomous mobile robots based on reinforcement learning and distributed genetic algorithms

Behavior learning and evolution of collective autonomous mob...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Hyo-Byung Jun Kwee-Bo Sim Robotics and Intelligent Information System Laboratory Department of Control and Instrumentation Engineering Chung Ang University Seoul South Korea

In this paper, we present the reinforcement learning and distributed genetic algorithm based behavior learning of the distributed autonomous mobile robots. The internal reinforcement signal for the reinforcement learning is generated by fuzzy inference, and dynamic recurrent neural networks are used as action generation module. We adopt the distributed genetic algorithms for the cooperative behavior emergence. We show the validity of the proposed learning and evolution algorithm by computer simulation.

关键词： Mobile robots Learning Genetic algorithms Inference algorithms Signal generators intelligent robots Animals Mobile communication Education intelligent systems

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Explicit fuzzy force control of industrial manipulators with position servo drives

Explicit fuzzy force control of industrial manipulators with...

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IEEE International Workshop on intelligent Robots and systems (IROS)

作者： I.H. Suh K.S. Eom H.J. Yeo B.H. Kang S.-R. Oh B.H. Lee Intelligent Control and Robotics Laboratory Department of Electrvnics Engineering Hanyang University South Korea Samsung Data System Company Limited South Korea Division of Electronics and Infonmation technology KIST Seoul South Korea Robotics and Intelligent Systems Laboratory Department of Control and Instrumentation Engineering Seoul National University South Korea

In this paper, a fuzzy force control algorithm is suggested for commercialized industrial robots equipped with the position servo drives, where control rules of the proposed fuzzy controller are changed according to the magnitude of environmental stiffness in such a way that good force response is maintained regardless of changes of environmental stiffness. Specifically, some fuzzy control rules are designed for several representative environmental stiffness values, and then a control action for a given arbitrary environmental stiffness value is decided by a fuzzy interpolation method. To show the validity of the proposed fuzzy controller, several experimental results are illustrated, where a 5-axis articulated robot manipulator equipped with the wrist force/torque sensor system and our prototype dual robot controller are employed.< >

关键词： Fuzzy control Force control Industrial control Manipulators Torque control control systems Robot sensing systems Commercialization Service robots Servomechanisms

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Implementation of input shaping control to reduce residual vibration in industrial network motion system 15

Implementation of input shaping control to reduce residual v...

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15th International Conference on control, Automation and systems, ICCAS 2015

作者： Ngo, Ha-Quang-Thinh Nguyen, Quoc-Chi Kim, Won-Ho Control and Automation Lab Department of Mechatronics Engineering Ho Chi Minh City University of Technology Viet Nam Department of Mechatronics Engineering Ho Chi Minh City University of Technology Viet Nam Department of Intelligent System Engineering Dong-Eui University Busan Korea Republic of

ISBN: (纸本)9788993215090

In this paper, a method to implement the input shaping control in Mechatrolink-III motion system is introduced. Firstly, the underdamped system is theoretically built by modeling. Then, the motion controller of Mechatrolink-III network is designed to apply the input shaper for reducing residual vibration in manufacturing machine. Later, the experimental beam is set-up to verify the effective performance of input shaping technique. The validity of the control strategy is practically performed by testing ZV, ZVD and ZVDD input shapers. Especially, the successful implementation provides an opportunity to apply the input shaper for multi-axes since Mechatrolink-III motion controller supports up to 32 axes. © 2015 Institute of control, robotics and systems - ICROS.

关键词： Motion control

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