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arXiv 2022年

作者： Chen, Hao Kiyokawa, Takuya Wan, Weiwei Harada, Kensuke Department of Systems Innovation Graduate School of Engineering Science Osaka University Osaka Toyonaka Japan

Robotic pick-and-place has been researched for a long time to cope with uncertainty of novel objects and changeable environments. Past works mainly focus on learning-based methods to achieve high precision. However, they have difficulty being generalized for the limitation of specified training models. To break through this drawback of learning-based approaches, we introduce a new perspective of similarity matching between novel objects and a known database based on category-association to achieve pick-and-place tasks with high accuracy and stabilization. We calculate the category name similarity using word embedding to quantify the semantic similarity between the categories of known models and the target real-world objects. With a similar model identified by a similarity prediction function, we preplan a series of robust grasps and imitate them to plan new grasps on the real-world target object. We also propose a distance-based method to infer the in-hand posture of objects and adjust small rotations to achieve stable placements under uncertainty. Through a real-world robotic pick-and-place experiment with a dozen of in-category and out-of-category novel objects, our method achieved an average success rate of 90.6% and 75.9% respectively, validating the capacity of generalization to diverse objects. Copyright © 2022, The Authors. All rights reserved.

关键词： Robot programming

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Probabilistic Tube-based control Synthesis of Stochastic Multi-Agent systems under Signal Temporal Logic

arXiv

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arXiv 2024年

作者： Vlahakis, Eleftherios E. Lindemann, Lars Sopasakis, Pantelis Dimarogonas, Dimos V. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden Thomas Lord Department of Computer Science Viterbi School of Engineering University of Southern California Los AngelesCA90089 United States School of Electronics Electrical Engineering and Computer Science Queen’s University Northern Ireland Belfast United Kingdom

We consider the control design of stochastic discrete-time linear multi-agent systems (MASs) under a global signal temporal logic (STL) specification to be satisfied at a predefined probability. By decomposing the dynamics into deterministic and error components, we construct a probabilistic reachable tube (PRT) as the Cartesian product of reachable sets of the individual error systems driven by disturbances lying in confidence regions (CRs) with a fixed probability. By bounding the PRT probability with the specification probability, we tighten all state constraints induced by the STL specification by solving tractable optimization problems over segments of the PRT, and relax the underlying stochastic problem with a deterministic one. This approach reduces conservatism compared to tightening guided by the STL structure. Additionally, we propose a recursively feasible algorithm to attack the resulting problem by decomposing it into agent-level subproblems, which are solved iteratively according to a scheduling policy. We demonstrate our method on a ten-agent system, where existing approaches are impractical. © 2024, CC BY.

关键词： Stochastic systems

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Navigating A Mobile Robot Using Switching Distributed Sensor Networks

Navigating A Mobile Robot Using Switching Distributed Sensor...

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European control Conference (ECC)

作者： Xingkang He Ehsan Hashemi Karl H. Johansson Ericsson AB Sweden Department of Mechanical Engineering University of Alberta Canada Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden

This paper proposes a method to navigate a mobile robot by estimating its state over a number of distributed sensor networks (DSNs) such that it can successively accomplish a sequence of tasks, i.e., its state enters each targeted set and stays inside no less than the desired time, under a resource-aware, time-efficient, and computation-and communication-constrained setting. We propose a new robot state estimation and navigation architecture, which integrates an event-triggered task-switching feedback controller for the robot and a two-time-scale distributed state estimator for each sensor. With the controller, the robot is able to accomplish a task by following a reference trajectory and switch to the next task when an event-triggered condition is fulfilled. With the estimator, each active sensor is able to estimate the robot state. We provide conditions to ensure that the state estimation error and the trajectory tracking deviation are upper bounded by two time-varying sequences, respectively. Furthermore, we find a sufficient condition for accomplishing a task and provide an upper bound of running time for the task. Numerical simulations of an indoor robot’s localization and navigation are provided to validate the proposed architecture

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Analytical and Experimental Study on a Versatile Landing System with Shock Response Mechanism

SSRN

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SSRN 2024年

作者： Li, Pengcheng Sato, Ryuki Hara, Susumu Department of Electronic and Electrical Engineering Southern University of Science and Technology 1088 Xueyuan Road Nanshan District Guangdong Province Shenzhen518055 China Department of Mechanical and Intelligent Systems Engineering Graduate School of Informatics and Engineering The University of Electro-Communications 1-5-1 Chofugaoka Chofu Tokyo182-8585 Japan Department of Aerospace Engineering Graduate School of Engineering Nagoya University Furo-cho Chikusa-ku Aichi Prefecture Nagoya464-8601 Japan

This paper introduces a versatile, passive-landing system designed for various landing operations such as planetary exploration missions, emergency landings of unmanned aerial vehicles (UAVs), and so on. The system leverages energy and momentum exchange mechanisms, incorporating two spring units and a detachable flyaway component to ensure smooth and safe landings. Initially, the kinetic energy of the lander is converted into potential energy stored in the spring units. A switch mechanism then releases this stored energy, converting it back into kinetic energy and transferring momentum to the flyaway part. This process effectively suppresses rebound and reduces acceleration, ensuring a soft landing. A key advantage of this mechanism is its high robustness against variations in initial-fall height. The energy stored in the spring units adjusts according to the falling height, enhancing the system adaptability. The system performance is evaluated through one-dimensional simulations to assess rebound height and acceleration, and two-dimensional simulations to evaluate its ability to prevent tip-over. An experimental setup further validates the system-rebound suppression capability. Results from both simulations and experiments confirm the superior system performance in minimizing rebound, reducing acceleration, and preventing rotational motion during landing. © 2024, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Dynamic Programming Algorithm using Furniture Industry 0/1 Knapsack Problem 5

Dynamic Programming Algorithm using Furniture Industry 0/1 K...

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5th International Conference on Cybernetics and Intelligent systems, ICORIS 2023

作者： Anditta, Mietha Amartya, Natashya Warnars, Laurens Spits Warnars, Harco Leslie Hendric Spits Ramadhan, Arief Siswanto, Teddy Mantoro, Teddy Noordin, Nurulhuda Bina Nusantara University School of Computer Science Computer Science Departement Jakarta11530 Indonesia Bina Nusantara University School of Information Systems Information Systems Departement Jakarta11530 Indonesia Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Departement Jakarta11530 Indonesia Telkom University Pjj Informatika Bandung40257 Indonesia Trisakti University Information Systems Department Jakarta11440 Indonesia Sampoerna University Faculty of Engineering and Technology Jakarta12760 Indonesia Universiti Teknologi Mara School of Computing Sciences College of Computing Informatics and Mathematics Selangor Malaysia

ISBN: (纸本)9798350369489

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset. © 2023 IEEE.

关键词： Dynamic programming

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Hybrid Deep Learning Model for Short-Term Wind Speed Forecasting Based on Time Series Decomposition and Gated Recurrent Unit

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Complex System Modeling and Simulation 2021年第4期1卷 308-321页

作者： Changtong Wang Zhaohua Liu Hualiang Wei Lei Chen Hongqiang Zhang School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China Department of Automatic Control and Systems Engineering the University of SheffieldSheffieldS13JDUK.

Accurate wind speed prediction has been becoming an indispensable technology in system security,wind energy utilization,and power grid dispatching in recent ***,it is an arduous task to predict wind speed due to its variable and random *** the objective to enhance the performance of forecasting short-term wind speed,this work puts forward a hybrid deep learning model mixing time series decomposition algorithm and gated recurrent unit(GRU).The time series decomposition algorithm combines the following two parts:(1)the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),and(2)wavelet packet decomposition(WPD).Firstly,the normalized wind speed time series(WSTS)are handled by CEEMDAN to gain pure fixed-frequency components and a residual *** WPD algorithm conducts the second-order decomposition to the first component that contains complex and high frequency signal of raw ***,GRU networks are established for all the relevant components of the signals,and the predicted wind speeds are obtained by superimposing the prediction of each *** from two case studies,adopting wind data from laboratory and wind farm,respectively,suggest that the related trend of the WSTS can be separated effectively by the proposed time series decomposition algorithm,and the accuracy of short-time wind speed prediction can be heightened significantly mixing the time series decomposition algorithm and GRU networks.

关键词： deep learning complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN) gated recurrent unit(GRU) short term wavelet packet decomposition wind speed prediction

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Distributed controller Design for Discrete-Time systems Via the Integration of Extended LMI and Clique-Wise Decomposition

arXiv

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arXiv 2024年

作者： Fushimi, Sotaro Watanabe, Yuto Sakurama, Kazunori Department of Systems Science Graduate School of Informatics Kyoto University Yoshida-Honmachi Sakyo-ku Kyoto606-8501 Japan Department of Electrical and Computer Engineering University of California San Diego San DiegoCA92093 United States Department of System Innovation Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Toyonaka Osaka560-8531 Japan

This study addresses a distributed controller design problem for discrete-time systems using linear matrix inequalities (LMIs). Sparsity constraints on control gains of distributed controllers result in conservatism via the convexification of the existing methods such as the extended LMI method. In order to mitigate the conservatism, we introduce a novel LMI formulation for this problem, utilizing the clique-wise decomposition method from our previous work on continuous-time systems. By reformulating the sparsity constraint on the gain matrix within cliques, this method achieves a broader solution set. Also, the analytical superiority of our method is confirmed through numerical examples. Copyright © 2024, The Authors. All rights reserved.

关键词： Continuous time systems

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False Data Injection Attack Detection Based on Wavelet Packet Decomposition and Random Forest in Smart Grid 23

False Data Injection Attack Detection Based on Wavelet Packe...

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23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data science and systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Chen, Zhenyu Yuan, Shuai Wu, Longfei Guan, Zhitao Du, Xiaojiang School of Control and Computer Engineering North China Electric Power University China Brock University Department of Finance Operations and Information Systems ON Canada Fayetteville State University Department of Mathematics and Computer Science Fayetteville United States Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ United States

ISBN: (纸本)9781665494571

As one of the critical infrastructures, the safety and reliability of the smart grid are directly associated with the development and stability of society. However, studies have shown that the power grid is at risk when the parameters are manipulated and cyber-attacks are generated against the state estimation, i.e., under false data injection attack (FDIA). Currently, a rich body of literature has studied on the FDIA defense methods, but most of them focus on the direct current (DC) scenario. This paper proposes a novel detection model that combines the wavelet packet decomposition (WPD) technique with the random forest (RF) algorithm. The WPD is able to capture the deviation of parameters from the normal conditions, whereas the RF is developed to classify these features and effectively identify the malicious data. The proposed model is also evaluated using real-world data on IEEE 118-bus power system. The results demonstrate excellent performance on precision rate and recall rate under varying scenarios. © 2021 IEEE.

关键词： Radio frequency Training data Interference Power system stability Feature extraction Data models Wavelet packets

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Artificial intelligence in cancer target identification and drug discovery

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Signal Transduction and Targeted Therapy 2022年第6期7卷 1951-1974页

作者： Yujie You Xin Lai Yi Pan Huiru Zheng Julio Vera Suran Liu Senyi Deng Le Zhang College of Computer Science Sichuan UniversityChengdu 610065China Laboratory of Systems Tumor Immunology Friedrich-Alexander-Universität Erlangen-Nürnberg(FAU)and Universitätsklinikum ErlangenErlangen 91052Germany Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesRoom D5131068 Xueyuan AvenueShenzhen University TownShenzhen 518055China School of Computing Ulster UniversityBelfast BT151EDUK Institute of Thoracic Oncology Department of Thoracic SurgeryWest China HospitalSichuan UniversityChengdu 610065China Key Laboratory of Systems Biology Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesChinese Academy of SciencesHangzhou 310024China Key Laboratory of Systems Health Science of Zhejiang Province Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China

Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying human diseases such as ***,we review and discuss how to employ artificial intelligence approaches to identify novel anticancer targets and discover ***,we describe the scope of artificial intelligence biology analysis for novel anticancer target ***,we review and discuss the basic principles and theory of commonly used network-based and machine learning-based artificial intelligence ***,we showcase the applications of artificial intelligence approaches in cancer target identification and drug *** together,the artificial intelligence models have provided us with a quantitative framework to study the relationship between network characteristics and cancer,thereby leading to the identification of potential anticancer targets and the discovery of novel drug candidates.

关键词： drugs cancer drug

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A Centimeter-Scale Inspection Robot for Locomotion in Viscous Fluids

A Centimeter-Scale Inspection Robot for Locomotion in Viscou...

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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Jun Zhang Zaiyang Liu Zhenxuan Ma Yang Tian Shugen Ma Zhongkui Wang Graduate School of Science and Engineering Ritsumeikan University Kusatsu Shiga Japan Department of Robotics Ritsumeikan University Kusatsu Shiga Japan Robotics & Autonomous Systems Thrust Systems Hub The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China

ISBN: (数字)9798350372601

ISBN: (纸本)9798350372618

Nature has inspired many designs for micro-robot locomotion, particularly helical propulsion inspired by Escherichia coli and spermatozoa, which has found widespread applications in medical micro-robots for generating thrust at low Reynolds numbers. However, the design and fabrication of small robots for inspection tasks, especially in industrial settings filled with highly viscous liquids, remain challenging. In this paper, we propose a robot capable of locomotion in constrained environments filled with high-viscosity fluids. The robot is propelled by two helical propellers, enabling it to move effectively at low Reynolds numbers. The optimal parameters for the helical propellers are analyzed using Resistive Force Theory (RFT), and structures are designed and experimentally validated accordingly. Finite element analysis is employed to determine the suitable body for the robot. The robot prototype is fabricated using 3D printing. Finally, locomotion experiment was conducted to validate the feasibility of the robot moving in viscous liquid.

关键词： Fabrication Liquids Service robots Propellers Shape Computational modeling Prototypes

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