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ieee International symposium on Circuits and Systems (ISCAS)

作者： Fanxi Yang Yuhan He Ning Ma Lirong Zheng Zhuo Zou School of Information Science and Technology Fudan University Shanghai China Guangdong Institute of Intelligence Science and Technology Zhuhai China

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

The connection matrix requires significant memory capacity in large-scale Spiking Neural Networks (SNNs). However, the sparsity of connections in cortical models leads to memory capacity and energy inefficiencies. This paper proposes Ternary Content Addressable Memory (TCAM)-based Sparse Connection Memory (TSCM) architecture in neuromorphic computing systems for cortical simulation. The architecture consists of a TCAM for searching existing synaptic connections, a Static Random Access Memory (SRAM) for storing synapse addresses, and a three-stage circuit for memory access control. By leveraging the sparsity, the proposed memory architecture demonstrates improved area and energy efficiency compared to the conventional Direct Mapped Full-Address Memory (DMFAM) architecture. A TSCM macro is designed, simulated using UMC 40-nm CMOS technology, and evaluated across various scales of classical cortical models. Experimental results demonstrate that the TSCM architecture reduces area by 27.6% to 75.6% and energy consumption by 15.8% to 96.0% in cortical simulation with neurons ranging from 100k to 10M compared to DMFAM architecture.

关键词： Energy consumption Associative memory Neuromorphic engineering computational modeling Memory architecture Neurons Memory management

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Utilizing the fuzzy logic algorithm for cartesian robot control system in conditions of mechanical damage transmission

Utilizing the fuzzy logic algorithm for cartesian robot cont...

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Annual Conference of Industrial Electronics Society

作者： Olga Dunaeva Siarhei Autsou Karolina Kudelina Mare Roosileht Virumaa College Tallinn University of Technology Kohla-Järve Estonia Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology Tallinn Estonia

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

This study delves into the intricate realm of adaptive control systems, highlighting their indispensable role across many industries, including robotics, automation, and manufacturing. Amidst industrial environments' dynamic and often unpredictable nature, the seamless fusion of fuzzy logic principles with cutting-edge computational methodologies, such as artificial intelligence and machine learning, emerges as a beacon of efficiency and reliability. Within this context, the research unveils the profound impact of fuzzy logic algorithms in steering Cartesian robots through mechanically challenging scenarios, where transmission impairments pose significant hurdles. By orchestrating meticulous parameter adjustments, these algorithms exhibit a remarkable ability to not only mitigate structural vibrations but also to optimize operational performance in real time. Moreover, the study underscores the inherent adaptability and versatility of fuzzy logic-based control systems, empowering industrial ecosystems to navigate the complexities of ever-evolving operational landscapes with unparalleled resilience. As such, the findings shed light on the transformative potential of adaptive control systems, offering a glimpse into a future where intelligent algorithms seamlessly harmonize with mechanical systems to drive innovation and efficiency in industrial settings.

关键词： Fuzzy logic Vibrations Torque Machine learning algorithms Service robots Complexity theory Servomotors Grippers Adaptive control Robots

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Design of Chinese Smart Kitchen Based on Users' Behavior 14

Design of Chinese Smart Kitchen Based on Users' Behavior

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14th International symposium on computational intelligence and Design, ISCID 2021

作者： Yuan, Xiaofang Deng, Fenghui Liu, Zheng Wuhan University of Technology School of Art and Design Wuhan China Design Innovation Center of CAA China Academy of Art Zhejiang Provincial Key Laboratory of Integration of Healthy Smart Kitchen System Hangzhou China

ISBN: (纸本)9781665438568

The concept of smart kitchens has become a hot topic for Chinese families as IoT technology in smart homes has matured. Current smart kitchen includes a variety of smart products which are controlled via mobile terminals. However, the accumulation of smart items that focus on solving a single pain point reduces the available space in the kitchen, and decreases the efficiency of kitchen cooking. As a result, encouraging the systematization and integration of single-product smart kitchens is a critical design issue to be solved immediately. Based on behavioral research, this paper employs quantitative and qualitative methods to investigate the common behavioral characteristics and pain points of smart kitchen target user groups. According to the study of user behavior, requirements and smart kitchen technology, a systematic design goals of Chinese smart kitchens with emotional communication and all-in-one interaction are proposed, which solves the problems of trivial interaction and fragmented usage scenes in existing smart kitchens, providing constructive meaning for the human-centered design direction of Chinese smart kitchens. © 2021 ieee.

关键词： automation

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Event-Triggered control of Multi-Player Zero-Sum Games via Adaptive Dynamic Programming 3

Event-Triggered Control of Multi-Player Zero-Sum Games via A...

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3rd International Conference on Industrial Artificial intelligence, IAI 2021

作者： Zhang, Yongwei Zhang, Shunchao Zhao, Bo Wu, Qiuye Liu, Derong Guangdong University of Technology School of Automation Guangzhou510006 China Beijing Normal University School of Systems Science Beijing100875 China

ISBN: (纸本)9781665435178

This paper investigates zero-sum game problems of nonlinear multi-player systems by using adaptive dynamic programming-based event-triggered control method. To begin with, a cost function which contains all the control inputs and the disturbance is designed. For the purpose of reducing the computation and communication burdens, a novel triggering condition which is suitable to multiple controllers is derived by using Lyapunov's direct method. It is noticed that the control laws and the disturbance laws are updated when the triggering condition is violated only to save computational resources. Theoretical analysis shows that the developed triggering condition guarantees the uniform ultimate boundedness of the closed-loop system. Finally, simulation example is provided to validate the effectiveness of the developed method. © 2021 ieee.

关键词： Closed loop systems

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An Earth Observation Satellite Mission Planning Method Based on Deep Q-Learning 6

An Earth Observation Satellite Mission Planning Method Based...

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6th International symposium on Computer and Information Processing Technology, ISCIPT 2021

作者： Chen, Tianyuan Wang, Hongfei Liu, Hao Wu, Peng University of Chinese Academy of Sciences Key Laboratory of Space Utilization Technology and Engineering Center for Space Utilization Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence Beijing China

ISBN: (纸本)9781665441377

With the increasing number of earth observation satellites and observation demands, satellite mission planning is facing huge challenges. For traditional satellite mission planning methods, there are problems such as difficulty in modeling, high computational complexity, and low scalability. This paper proposes a satellite mission planning method based on Deep Q-Learning. Firstly, a hybrid satellite mission planning model is established that combines the constraint-satisfaction model, the 0-1 knapsack model and the Markov decision model. Then, the decision algorithm based on Deep Q-Learning is used to solve the problem, so that the satellite can make full use of the past mission planning experience to learn the optimal planning strategy. Finally, several traditional satellite mission planning methods-branch and bound algorithm, genetic algorithm, simulated annealing algorithm are compared, and various performances of the algorithms are tested and analyzed through simulation experiments. The superiority of this method is verified. © 2021 ieee.

关键词： Satellites

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Model Predictive control of Autonomous Driving using Unscented Kalman Filter with Sparse Spectrum Gaussian Processes

Model Predictive Control of Autonomous Driving using Unscent...

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2021 International symposium on Networks, Computers and Communications, ISNCC 2021

作者： Zhang, Shitian Cui, Yunduan Deng, Naitian Li, Huiyun Shenzhen Institutes Of Advanced Technology Chinese Academy Of Sciences Shenzhen China

ISBN: (纸本)9780738113166

In this paper, a model predictive control (MPC) approach that combines sparse spectrum Gaussian processes model and unscented Kalman Filter is proposed for path tracking task in autonomous driving. To tackle the difficulty of balancing control performance and computational cost in MPC with Gaussian processes model, the proposed approach employs the sparse spectrum Gaussian processes (SSGP) to efficiently model the vehicle, and utilizes unscented Kalman filter (UKF) to naturally propagate model uncertainties during multiple step prediction of MPC. The proposed approach is evaluated in both a numerical driving simulation and a mature driving simulation CARLA. The results indicate that the proposed method achieves a robust driving performance with a significant reduction of computational complexity. © 2021 ieee.

关键词： Model predictive control

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A Wavelet Guided Attention Module for Skin Cancer Classification with Gradient-Based Feature Fusion

A Wavelet Guided Attention Module for Skin Cancer Classifica...

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ieee International symposium on Biomedical Imaging

作者： Ayush Roy Sujan Sarkar Sohom Ghosal Dmitrii Kaplun Asya Lyanova Ram Sarkar Department of Electrical Engineering Jadavpur University Kolkata India Department of Computer Science and Engineering Jadavpur University Kolkata India Department of Electronics and Communication Engineering International Institute of Information Technology Naya Raipur Chhattisgarh India Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China Department of Automation and Control Processes Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Skin cancer is a highly dangerous type of cancer that requires an accurate diagnosis from experienced physicians. To help physicians diagnose skin cancer more efficiently, a computer-aided diagnosis (CAD) system can be very helpful. In this paper, we propose a novel model, which uses a novel attention mechanism to pinpoint the differences in features across the spatial dimensions and symmetry of the lesion, thereby focusing on the dissimilarities of various classes based on symmetry, uniformity in texture and color, etc. Additionally, to take into account the variations in the boundaries of the lesions for different classes, we employ a gradient-based fusion of wavelet and soft attention-aided features to extract boundary information of skin lesions. We have tested our model on the multi-class and highly class-imbalanced dataset, called HAM10000, and achieved promising results, with a 91.17% F1-score and 90.75% accuracy. The code is made available at: https://***/AyushRoy2001/WAGF-Fusion.

关键词： Solid modeling Image color analysis Biological system modeling Melanoma Medical services Feature extraction Skin

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Bluetooth Communications in Educational Robotics 23

Bluetooth Communications in Educational Robotics

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23rd International Conference on control Systems and Computer Science Technologies, CSCS 2021

作者： Oprea, Marin Mocanu, Mariana University Politehnica of Bucharest Calarasi Romania Faculty of Automatic Control and Computer Science Computer Department University Politehnica of Bucharest Bucharest Romania

ISBN: (纸本)9781665439398

In a world in a continuous and rapid change, it is absolutely necessary for our students to keep up with the rapid progress of new technologies: Internet of Things (IoT), Robotics, Artificial intelligence (AI), Virtual Reality (VR), Augmented Reality (AR) etc. The rapid evolution and diversification of these emerging technologies has recently led to their introduction into the educational offer of the school curriculum for the gymnasium. The discipline of Information and Communication Technology (ICT) has already been implemented, a discipline that involves both the formation of skills to use new technologies and the formation of computational thinking necessary for the efficient and intelligent use of these technologies. In order to teach and learn Physics from a STEM (Science, Technology, Engineering and Mathematics) educational perspective, we initiated optional school courses of IoT, Robotics and AI (approached through Machine Learning). These courses stimulate, at the level of students, computational thinking, creativity and innovation and lead, from an interdisciplinary perspective, to the development of emerging specializations such as Mathematics-Physics-automation, Mathematics-Physics-Electronics, Mathematics-Physics-Informatics-Robotics etc. In this paper we presented a method of approaching, in the school educational space, the study of wireless communication technologies between smart devices, through an Educational Robotics project. The project consisted of creating a wireless controlled mobile robotic platform (robot car) via a Bluetooth module connected to an Arduino Uno board. © 2021 ieee.

关键词： Students

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Two-Dimensional Broad Learning System for Data Analytic

IEEE Transactions on Artificial Intelligence

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ieee Transactions on Artificial intelligence 2021年第6期2卷 594-607页

作者： Dai, Wei Zhang, Rui Wang, Qianjin Cheng, Yuhu Wang, Xuesong The Engineering Research Center of Intelligent Control for Underground Space Ministry of Education China University of Mining and Technology Xuzhou221116 China The School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China The School of Electrical Engineering Yancheng Institute of Technology Yancheng221051 China

Recently, a novel learning algorithm called the broad learning system (BLS) has been established by using the theory of pseudoinverse and compressed sensing technology. As an alternative to deep learning, BLS has gained extensive attention in data analytics. Unlike the existing deep structures based learning tools (such as deep neural networks), it is able to rapidly achieve incremental learning, and does not require tedious retraining to remodel the system. However, given image data modeling tasks, 1-D BLS requires a conventional vectorization operation, the dimension of input will be quite large for high resolution image. This operation may result in huge computational complexity, thereby increasing the time of model construction. To resolve this issue, a 2-D version of BLS, namely 2-D-BLS, is first proposed to fast construct randomized learner models by using matrix inputs. Specifically, the proposed method employs left and right projecting vectors to replace the usual high dimensional input weight. Moreover, the theoretical analyses on the superiority of 2-D-BLS against BLS are presented in terms of the algorithm complexity and the difference of random parameter space. Empirical results on MNIST dataset, NORB 3-D object image recognition dataset, ORL dataset, YaleB dataset, and handwritten digit dataset demonstrate that the proposed 2-D-BLS outperforms the existing extensions of BLS and state-of-the-art 2-D machine learning methods in terms of the learning efficiency, showing good potential of 2-D-BLS for image data analytics. Impact Statement-as a novel learning tool, BLS has achieved great success in many fields. Image recognition is one of the most widely used fields of artificial intelligence. But, BLS is a 1-D model, the vectorization operation is necessary to convert matrix input data into a row or a column vector. This operation will lead to "explosion of dimensionality" and increase the time of model construction when it is coming to image data analytic

关键词： Learning systems

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computational Structure Design of a Bio-Inspired Armwing Mechanism

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ieee ROBOTICS AND automation LETTERS 2020年第4期5卷 5929-5936页

作者： Sihite, Eric Kelly, Peter Ramezani, Alireza Northeastern Univ Dept Elect & Comp Engn SiliconSynapse Lab Boston MA 02119 USA

Bat membranous wings possess unique functions that make them a good example to take inspiration from and transform current aerial drones. In contrast with other flying vertebrates, bats have an extremely articulated musculoskeletal system which is key to their energetic efficiency with impressively adaptive and multimodal locomotion. Biomimicry of this flight apparatus is a significant engineering ordeal and we seek to achieve mechanical intelligence through sophisticated interactions of morphology. Such morphological computation or mechanical intelligence draws our attention to the obvious fact that there is a common interconnection between the boundaries of morphology and closed-loop feedback. In this work, we demonstrate that several biologically meaningful degrees of freedom can be interconnected to one another by mechanical intelligence and, as a result, the responsibility of feedback-driven components (e.g., actuated joints) is subsumed under computational morphology. The results reported in this work significantly contribute to the design of bio-inspired Micro Aerial Vehicles (MAVs) with articulated body and attributes such as efficiency, safety, and collision-tolerance.

关键词： Biomimetics soft robot materials and design mechanism design

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