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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Filip Zorić Alejandro Suarez Goran Vasiljević Matko Orsag Zdenko Kovačić Anibal Ollero Laboratory for Robotics and Intelligent Control Systems (LARICS) Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia GRVC Robotics Lab University of Seville Sevilla Spain

This paper presents a comparative performance evaluation of three different teleoperation interfaces for very low weight (<3 kg) anthropomorphic dual arms intended to conduct complex manipulation tasks involving a certain level of dexterity, accuracy and agility, either in ground service or in aerial manipulation applications. A visual human pose estimation system is developed to obtain the Cartesian and joint values of the user, which are mapped to the corresponding pose of the dual arm manipulator exploiting the equivalent human-robot kinematics. A leader-follower scheme is also presented, using a reduced scale dual arm that can replicate directly the joint positions of the leader arms to the follower arms. A 6-DOF (degrees of freedom) joystick is proposed to generate linear motions more accurately. A total of 60 ground tests were conducted involving 10 participants to determine the accuracy and time performance in two benchmarks (box edges and S contour tracking). Finally, the visual and leader-follower interfaces were evaluated with the dual arm aerial manipulator on flight tests, reporting several findings derived from the system evaluation.

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Marker or Markerless? Mode-Switchable Optical Tactile Sensing for Diverse Robot Tasks

arXiv

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arXiv 2024年

作者： Ou, Ni Chen, Zhuo Luo, Shan The State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China The Robot Perception Lab. Centre for Robotics Research Department of Engineering King’s College London LondonWC2R 2LS United Kingdom

Optical tactile sensors play a pivotal role in robot perception and manipulation tasks. The membrane of these sensors can be painted with markers or remain markerless, enabling them to function in either marker or markerless mode. However, this uni-modal selection means the sensor is only suitable for either manipulation or perception tasks. While markers are vital for manipulation, they can also obstruct the camera, thereby impeding perception. The dilemma of selecting between marker and markerless modes presents a significant obstacle. To address this issue, we propose a novel mode-switchable optical tactile sensing approach that facilitates transitions between the two modes. The marker-to-markerless transition is achieved through a generative model, whereas its inverse transition is realized using a sparsely supervised regressive model. Our approach allows a single-mode optical sensor to operate effectively in both marker and markerless modes without the need for additional hardware, making it well-suited for both perception and manipulation tasks. Extensive experiments validate the effectiveness of our method. For perception tasks, our approach decreases the number of categories that include misclassified samples by 2 and improves contact area segmentation IoU by 3.53%. For manipulation tasks, our method attains a high success rate of 92.59% in slip detection. Code, dataset and demo videos are availab.e at the project website https://***/Marker-Markerless-Transition/ Copyright © 2024, The Authors. All rights reserved.

关键词： Tactile sensors

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Development of an Adaptive Technology for Distance Learning of Microprocessor Technology Based on Immunological Homeostasis

Development of an Adaptive Technology for Distance Learning ...

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2023 International Conference on Industrial engineering, Applications and Manufacturing, ICIEAM 2023

作者： Samigulina, Galina Samigulina, Zarina Porubov, Dmitriy Institute of Information and Computing Technologies Lab. Intellectual Control Systems and Forecasting Almaty Kazakhstan Kazakh - British Technical University School of Information Technologies and Engineering Almaty Kazakhstan East Kazakhstan Technical University Named after D. Serikbayev Competence and Technology Transfer Center in the Field of Automation and Mechatronics Ust-Kamenogorsk Kazakhstan

ISBN: (纸本)9781665475952

At present, with the development of modern IT technologies and artificial intelligence methods, it is relevant to develop adaptive distance education systems for students of technical specialties capable of providing a personalized cognitive approach to the process of obtaining knowledge and timely adjustment of the learning trajectory. Particular difficulties arise when teaching the principles of operation of complex industrial equipment based on microprocessor technology, the basics of programming and the development of automatic control systems based on them. The problems associated with the complexity of adapting technical training courses for specific students and the peculiarities of information perception in the absence of direct contact with the teacher can be successfully solved with the introduction of algorithms based on a unified artificial immune system (UAIS). An innovative e-learning technology is proposed for students of engineering specialties in order to obtain high-quality technical professional education in a short time on real industrial equipment. When creating the technology and predicting the learning outcomes of students, immunological homeostasis was used to quickly correct the learning process. UAIS was developed on the basis of modified clonal selection, negative selection and immune network algorithms in order to identify the most effective of them in predicting multivariate dynamic data about students and forming an adequate immune response to maintain immunological homeostasis. The main stages and advantages of the proposed technology are given. The simulation results were obtained with the participation of students of the Faculty of Information Technology on the basis of the Kazakh-British Technical University. © 2023 IEEE.

关键词： engineering education

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Distributed Online Convex Optimization with Time-Varying Constraints: Tighter Cumulative Constraint Violation Bounds under Slater's Condition

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IEEE Transactions on Automatic control 2025年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Hong, Yiguang Chai, Tianyou Johansson, Karl H. National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai Institute of Intelligent Science and Technology China Ministry of Education Frontiers Science Center for Intelligent Autonomous Systems China Massachusetts Institute of Technology Lab for Information & Decision Systems CambridgeMA02139 United States Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Nanyang Technological University School of Electrical and Electronic Engineering 50 Nanyang Avenue 639798 Singapore Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online convex optimization with time-varying constraints. In this setting, a network of agents makes decisions at each round, and then only a portion of the loss function and a coordinate block of the constraint function are privately revealed to each agent. The loss and constraint functions are convex and can vary arbitrarily across rounds. The agents collab.rate to minimize static network regret and network cumulative constraint violation. A novel distributed online algorithm with a vanishing stepsize is proposed and it achieves an O(Tmax {c,1-c}) static network regret bound and an O(T1-c/2) network cumulative constraint violation bound, where T is the number of rounds and c∈ (0,1) is a user-defined trade-off parameter. When Slater's condition holds (i.e, there is a point that strictly satisfies the inequality constraints), the network cumulative constraint violation bound is reduced to O(T1-c). Moreover, if the loss functions are strongly convex, then static network regret bound is reduced to O(log (T)), and the network cumulative constraint violation bound is reduced to O(√log (T)T) and O(log (T)) without and with Slater's condition, respectively. To the best of our knowledge, this paper is the first to achieve tighter (network) cumulative constraint violation bounds for (distributed) online convex optimization with time-varying constraints under Slater's condition. Finally, the theoretical results are verified through numerical simulations. © 1963-2012 IEEE.

关键词： Convex optimization

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Consensus-driven Deviated Pursuit for Guaranteed Simultaneous Interception of Moving Targets

arXiv

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arXiv 2024年

作者： Sinha, Abhinav Mukherjee, Dwaipayan Kumar, Shashi Ranjan GALACxIS Lab Department of Aerospace Engineering and Engineering Mechanics University of Cincinnati OH45221 United States Department of Electrical Engineering Indian Institute of Technology Bombay Powai Mumbai400076 India Intelligent Systems & Control Lab Department of Aerospace Engineering Indian Institute of Technology Bombay Powai Mumbai400076 India

This work proposes a cooperative strategy that employs deviated pursuit guidance to simultaneously intercept a moving (but not manoeuvring) target. As opposed to many existing cooperative guidance strategies which use estimates of time-to-go, based on proportional-navigation guidance, the proposed strategy uses an exact expression for time-to-go to ensure simultaneous interception. The guidance design considers nonlinear engagement kinematics, allowing the proposed strategy to remain effective over a large operating regime. Unlike existing strategies on simultaneous interception that achieve interception at the average value of their initial time-to-go estimates, this work provides flexibility in the choice of impact time. By judiciously choosing the edge weights of the communication network, a weighted consensus in time-to-go can be achieved. It has been shown that by allowing an edge weight to be negative, consensus in time-to-go can even be achieved for an impact time that lies outside the convex hull of the set of initial time-to-go values of the individual interceptors. The bounds on such negative weights have been analysed for some special graphs, using Nyquist criterion. Simulations are provided to vindicate the efficacy of the proposed strategy. © 2024, CC BY-NC-ND.

关键词： Navigation

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A Reinforcement Learning Algorithm for Underwater Environment Search 2

A Reinforcement Learning Algorithm for Underwater Environmen...

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2022 2nd International Conference on Artificial Intelligence, Big Data and Algorithms, CAIBDA 2022

作者： Xiong, Minglei Xie, Guangming State Key Laboratory for Turbulence and Complex Systems Intelligent Biomimetic Design Lab. College of Engineering Peking University Beijing100871 China Peng Cheng Laboratory Shenzhen518055 China Robot Technology Co. Ltd. Beijing100176 China

ISBN: (纸本)9783800760268

Known as an intelligent learning algorithm that can be employed without any sufficient prior information, the reinforcement learning algorithm has been widely used recently. The underwater unknown 3D environment search is a typical application scenario lacking any prior knowledge. This study proposes an algorithm framework including one agent and an intelligent swarm based on the idea of reinforcement learning. This learning algorithm can be adopted to train only one individual. Many of such individuals will then create an intelligent group which can efficiently and completely search underwater unknown 3D environments. Moreover, the proposed algorithm needs no further prior knowledge of the unknown environment. Even if the algorithm fails to reach the optimal level in the use of reinforcement learning, the results confirm the applicability prospect of reinforcement learning in this field and provide an appealing direction. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Learning algorithms

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Design of Variance-Constrained H∞State Estimation Algorithm for Delayed Memristive Neural Networks with Attacks: An Adaptive Event-Triggered Approach 8

Design of Variance-Constrained H∞State Estimation Algorithm...

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8th IEEE International Conference on Cloud Computing and Intelligence systems, CCIS 2022

作者： Gao, Yan Hu, Jun Yu, Hui Jia, Chaoqing Harbin University of Science and Technology Department of Mathematics Harbin150080 China Harbin University of Science and Technology School of Automation Harbin150080 China Harbin University of Science and Technology Heilongjiang Prov. Key Lab. of Optimization Control and Intelligent Analysis for Complex Systems Harbin150080 China

ISBN: (纸本)9781665477352

This paper studies the algorithm design of variance-constrained H∞ state estimation problem for delayed memristive neural networks with adaptive event-triggered mechanism. The denial-of-service attacks are modeled by a series of random variables obeying the Bernoulli distribution with known probability. In addition, the adaptive event-triggered mechanism is introduced into the sensor-to-estimator to avoid unnecessary resource consumption. Our purpose is to construct a finite-horizon state estimation algorithm, and sufficient condition is obtained for the estimation error system satisfying the H∞ performance requirement and the error variance boundedness. Finally, a numerical example is used to illustrate the feasibility of the presented H∞ state estimation algorithm. © 2022 IEEE.

关键词： State estimation

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Development and application of multi purpose gateway for swarm intelligent building 4

Development and application of multi purpose gateway for swa...

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4th World Conference on Computing and Communication Technologies, WCCCT 2021

作者： Zhang, Zexin Li, Lun Zhao, Liang Zhao, Tianyi School of Control Science and Engineering Dalian University of Technology Dalian China Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Dalian University of Technology Dalian China School of Civil Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9780738144986

Aiming at the problem of the architecture of the automation control system of traditional buildings, Tsinghua University proposed swarm intelligence building technology. However, most of the electrical equipment in completed buildings is not designed for swarm intelligence technology, and a large number of heterogeneous devices can't communicate with Swarm Intelligence Computing network platform, which leads to the difficulty of the system promotion. This paper develops a multi-purpose gateway for swarm intelligence. On the basis of solving the data interaction between terminal equipment of swarm intelligence control system and computing network, it reduces the requirement of network bandwidth through preprocessing of data, and completes the feasibility test of gateway in lighting unit. © 2021 IEEE.

关键词： intelligent buildings

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An Efficient Smoke Detection Approach Based on Dual-Channel Neural Network

An Efficient Smoke Detection Approach Based on Dual-Channel ...

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2022 International Symposium on intelligent Signal Processing and Communication systems, ISPACS 2022

作者： Zhou, Chengxu Wang, Dongxia Cai, Haoran School of Electronics and Information Engineering Liaoning University of Technology China Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Jinzhou Dalian China School of Electronics and Information Engineering Tianjin University of Technology and Education Tianjin China School of Electronics and Information Engineering Liaoning University of Technology Jinzhou China

ISBN: (纸本)9798350332421

Smoke is the key feature of fire detection in its early age. Thus, an efficient smoke detection approach (i. e. an accurate and rapid method) is essential important to prevent fires. However, it is difficult to obtain an efficient method due to non-obvious details and monotonous color of smoke images. Moreover, traditional methods of smoke detection based on CNN contains lots of parameters and operations, which severely influents the computing efficiency in practical applications. Thus, we propose an efficient dual-channel neural network (EDCNN) on the basis of the state-of-The-Art DCNN. Concretely, we use the linear inverted bottleneck (LIB) to replace the traditional convolution layers on DCNN to build a light weight deep neural network. The introduction of the LIB block can efficiently trade off between accuracy and latency. Moreover, ReLU6 is used as the activation function, because it is more suitable for low-precision hardware devices. We then use some experimental results to demonstrate the effectiveness of EDCNN compared with the competitors for smoke detection in terms of model and computational complexity. © 2022 IEEE.

关键词： Smoke

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Synchronized UAV Group Flight control under Data Rate Limitations and Actuator Saturation

Synchronized UAV Group Flight Control under Data Rate Limita...

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School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR)

作者： Boris Andrievsky Luliia Zaitceva Department of Applied Cybernetics Control of Complex Systems Lab. Institute for Problems in Mechanical Engineering of RAS St. Petersburg State University Saint Petersburg Russia Department of Applied Cybernetics Control of Complex Systems Lab. Institute for Problems in Mechanical Engineering of RAS St. Petersburg State University St. Petersburg Electrotechnical University ’’LETI" Saint Petersburg Russia

This work specifically addresses the challenges associated with information transfer between agents in pursuit of desired control objectives. Seamless communication is crucial, especially during formation synchronization, as delays can lead to disintegration. Additionally, large-scale systems may face string or mesh instability, where state deviations increase. This work aims to advance decentralized control in multi-agent systems with complex information graph structures, considering nonlinear limitations on the control signal. A sequential nonlinear corrective unit is employed to mitigate this effect. The present study incorporates data rate limitations on information exchange between UAVs in formation. An adaptive coding/decoding procedure is utilized for data transfer, and the minimal data transmission rate required for maintaining formation stability is numerically evaluated.

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