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IEEE Transactions on Intelligent Vehicles 2024年第9期9卷 5595-5605页

作者： Changxiang Liu Hongshan Yu Qiang Fu Xieyuanli Chen Naveed Akhtar Zhi-Hong Mao College of Electrical and Information Engineering School of Robotics Quanzhou Institute of Industrial Design and Machine Intelligence Innovation Hunan University Changsha China National University of Defense Technology Changsha China School of Computing and Information Systems University of Melbourne Melbourne VIC Australia Department of Electrical and Computer Engineering University of Pittsburgh Pittsburgh PA USA

Visual-inertial SLAM (VINS) stands at the forefront of advancements in computer vision, robotics, and autonomous driving, revolutionizing the way we perceive and navigate the world. The typical approach in optimization-based methods for VINS is to estimate camera poses by minimizing the reprojection errors of all corresponding map points. However, not all map points are suitable for accurate pose estimation. Some map points introduce noise and can compromise the accuracy of the estimation. Current methods primarily focus on removing 2D noise points, which proves to be ineffective since triangulation can increase the uncertainty of map points. To address this problem, we propose a new method for Informative Map Point Selection (IMPS) in VINS systems. IMPS identifies the most informative map points by utilizing mutual and geometric information as the optimization target. We integrate IMPS into a VINS system and evaluate its performance using publicly available EuRoC, TUM and M2DGR datasets, as well as our own data. Experimental results demonstrate that our method surpasses existing VINS methods and achieves state-of-the-art pose estimation performance. Importantly, IMPS functions as an independent module with strong generalization capabilities, allowing for easy integration into other VINS systems and enhancing pose estimation performance. This integration not only elevates pose estimation accuracy but also holds great promise for advancing applications in intelligent driving and unmanned systems.

关键词： Simultaneous localization and mapping Optimization Cameras Pose estimation Robots Mutual information Intelligent vehicles

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Whole Body Balance Control for Bipedal Robots Based on Virtual Model Control 16th

Whole Body Balance Control for Bipedal Robots Based on Virtu...

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16th International Conference on Intelligent robotics and Applications, ICIRA 2023

作者： Gao, Chengzhi Xie, Ye Zhu, Yiting Liang, Dingkun Kong, Lingyu Wang, Xin Xie, Anhuan Gu, Jianjun Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Zhejiang University Zhejiang Hangzhou311100 China Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada

ISBN: (纸本)9789819964918

Due to the lack of accurate stability theoretical basis, the dynamic balance control of bipedal robots is a challenging topic. In this paper, we propose a controller that combines virtual model control and whole body control. In our framework, the whole system is simplified into a spring inverted pendulum model. Decoupling control is carried out for this model, and a virtual model is introduced to establish the relationship between the joint torque of the support leg and the state of the center of mass. The distribution of reaction force is obtained through decoupling closed-loop control. The whole body control part first uses multi task whole body control to determine the kinematics information, and then solves the joint feedforward torque through dynamical model, thus obtaining the desired force position hybrid control. Proposed algorithm improved the problem of incomplete decoupling between states and increased the stiffness of the support leg. The newly designed control framework was tested in Simscape dynamic simulation and verified the anti-interference ability and fast walking ability of Whole Body Balance Control for bipedal robots based on Virtual Model Control. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Inverted pendulum

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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case 63

Optimal Linear Deception Attacks on Remote State Estimation ...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Shang, Jun Zhang, Hanwen Zhou, Jing Chen, Tongwen Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai200092 China University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

ISBN: (纸本)9798350316339

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack's stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback-Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples. © 2024 IEEE.

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Deep Learning based Synthetic Aperture Imaging in the Presence of Phase Errors via Decoding Priors

Deep Learning based Synthetic Aperture Imaging in the Presen...

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IEEE National Conference on Radar

作者： Samia Kazemi Bariscan Yonel Birsen Yazici Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

In this paper, we designed a deep learning (DL) based method for synthetic aperture imaging in the presence of phase errors. Random variations in the transmission medium resulting from unforeseen environmental changes, fluctuations in sensor locations, and multiple scattering effects in the background medium often amount to uncertainties in the assumed data models. Imaging algorithms that rely on back-projected estimates are susceptible to estimation errors under these circumstances. Moreover, under dynamic nature of the medium, collecting high volume of measurements under the same operating conditions may become challenging. Towards this end, our imaging network incorporates DL in three major steps: first, we implement a deep network (DN) for pre-processing the erroneous measurements; second, we implement a DL-based decoding prior by recovering an encoded version of the reflectivity vector associated with the scattering media to reduce sample complexity, which is then mapped to an image estimate by a decoding DN; finally, we consider a fixed step implementation of an iterative algorithm in the form of a recurrent neural network (RNN) by using the unrolling technique that leads to a model-based imaging operator. The parameters of all three DNs are learned simultaneously in a supervised manner. We verified the feasibility of our approach using simulated high fidelity synthetic aperture measurements.

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Leveraging Predictions in Power System Frequency Control: An Adaptive Approach

Leveraging Predictions in Power System Frequency Control: An...

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IEEE Conference on Decision and Control

作者： Wenqi Cui Guanya Shi Yuanyuan Shi Baosen Zhang Department of Electrical and Computer Engineering University of Washington Seattle WA USA Robotics Institute Carnegie Mellon University PA USA Department of Electrical and Computer Engineering University of California San Diego

Ensuring the frequency stability of electric grids with increasing renewable resources is a key problem in power system operations. In recent years, a number of advanced controllers have been designed to optimize frequency control. These controllers, however, almost always assume that the net load in the system remains constant over a sufficiently long time. Given the intermittent and uncertain nature of renewable resources, it is becoming important to explicitly consider net load that is time-varying. This paper proposes an adaptive approach to frequency control in power systems with significant time-varying net load. We leverage the advances in short-term load forecasting, where the net load in the system can be accurately predicted using weather and other features. We integrate these predictions into the design of adaptive controllers, which can be seamlessly combined with most existing controllers including conventional droop control and emerging neural network-based controllers. We prove that the overall control architecture achieves frequency restoration decentralizedly. Case studies verify that the proposed method improves both transient and frequency-restoration performances compared to existing approaches.

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Analysis on the Hesitation and its Application to Decision Making

Decision Making: Applications in Management and Engineering

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Decision Making: Applications in Management and engineering 2024年第2期7卷 15-34页

作者： Yang, Youpeng Lee, Sanghyuk Kim, Kyeong Soo Zhang, Haolan Huang, Xiaowei Pedrycz, Witold School of Advanced Technology Xi’an Jiaotong-Liverpool University Jiangsu Suzhou China Department of Computer Science University of Liverpool Liverpool United Kingdom Department of Computer Science New Uzbekistan University Tashkent Uzbekistan SCDM Centre Zhejiang University Ningbo China Department of Electrical & Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Research Center of Performance and Productivity Analysis Istinye University Istanbul Turkey

A novel score function based on the Poincaré metric is proposed and applied to a decision-making problem. Decision-making on Fuzzy Sets (FSs) has been considered due to the flexibility of the data, and it is applied to the decision-making. However, decisions with FSs are sometimes nondecisive even for different membership degrees. Hence, Intuitionistic Fuzzy Sets (IFSs) data is applied to design a score function for the decision-making with the Poincaré metric. This function is supported by the profound information of IFSs;IFSs include hesitation degree together with membership and non-membership degree. Hence, IFS membership and non-membership degree are expressed as two-dimensional vectors satisfying the Poincaré metric for simplification. At the same time, the proposed approach addresses the hesitation information in the IFS data. Next, a score function is proposed, constructed and provided. The proposed score function has a strict monotonic property and addresses the preference without resorting to the accuracy function. The strict monotonic property guarantees the preference of all attributes. Additionally, the existing problem of score function design in IFSs is addressed: they return zero scores even with different meanings for the same membership and non-membership degree. The advantages of the proposed score function over existing ones are demonstrated through illustrative examples. From the calculation results, the proposed decision score function discriminates between all candidates. Hence, the proposed research provides a solid foundation for the hesitation analysis on the decision-making problem. © 2024 The Authors.

关键词： Decision making

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Robustness of Optimal Circadian Rhythm Entrainment under Model Perturbation

Robustness of Optimal Circadian Rhythm Entrainment under Mod...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Zidi Tao Agung Julius John T. Wen Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY USA

The optimal circadian rhythm entrainment problem has been studied based on mathematical models, e.g. the Kronauer model. In this paper, we study the robustness of light-based circadian rhythm entrainment under model parameter perturbations as well as propose a feedback control law to improve the robustness of the entrainment strategy. Our study finds the model parameter whose perturbations affect the entrainment the most. We also find that feedback control reduces the sensivitity of the entrainment process to model parameter *** relevance— Circadian misalignment has negative impacts on health, such as higher risks of cardiovascular disease and cancer. We present a numerical study of how well optimized circadian rhythm entrainment plans that are derived from a generic mathematical model work on personalized cases.

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Gaussian process-based visual pursuit control with unknown target motion learning in three dimensions

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SICE Journal of Control, Measurement, and System Integration 2021年第1期14卷 116-127页

作者： Omainska, Marco Yamauchi, Junya Beckers, Thomas Hatanaka, Takeshi Hirche, Sandra Fujita, Masayuki Department of Information Physics and Computing The University of Tokyo Tokyo Japan Department of Electrical and Systems Engineering University of Pennsylvania PennsylvaniaPA United States Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo Japan Department of Electrical and Computer Engineering Technical University of Munich Munich Germany

In this paper, we propose an observer-based visual pursuit control integrating three-dimensional target motion learning by Gaussian Process Regression (GPR). We consider a situation where a visual sensor equipped rigid body pursuits a target rigid body whose velocity is unknown but dependent on the target's pose. We estimate the pose from visual information and propose a Gaussian Process (GP) model to predict the target velocity from the pose estimate. We analyse stability of the proposed control by showing that estimation and control errors are ultimately bounded with high probability. Finally, simulations illustrate the performance of the proposed control schemes even if the visual measurement is corrupted by noise. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Gaussian distribution

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Development of a Robotic Hand Glove System for Secure Grasp with AI Wireless Sensor Data 20

Development of a Robotic Hand Glove System for Secure Grasp ...

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20th IEEE International Conference on Mechatronics and Automation, ICMA 2023

作者： Almassri, Ahmed Koyanagi, Ken'Ichi Wada, Chikamune Horio, Keiichi Hasan, Wan Zuha Wan Toyama Prefectural University Department of Intelligent Robotics 5180 Kurokawa Toyama Imizu Japan Kyushu Institute of Technology Department of Life Science and Systems Engineering 2-4 Hibikino Fukuoka Kitakyushu Japan Universiti Putra Malaysia Department of Electrical and Electronic Selangor 43400 Malaysia Gaza Palestine

ISBN: (纸本)9798350320831

Robotic Hand glove is one of the most commonly used technique in the rehabilitation systems. In this paper, we developed a robotic hand system with a proposed sensing mechanism-based AI algorithm, which can acquire grasping forces from human fingers. It is composed of five low-cost force sensors attached to the glove's fingertips and wireless data logger. Several experiments including grasping a plastic bottle and squeezing a tennis ball are implemented to verify the efficiency of the proposed system using the developed glove. As a result, it accurately estimates the forces applied by each finger with the aim of achieving a secure grasp comparison with conventional methods. © 2023 IEEE.

关键词： Robotic arms

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Diamond-based plasmonic terahertz devices

Diamond-based plasmonic terahertz devices

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Proceedings of the IEEE Dallas Circuits and systems Workshop (DCAS)

作者： Muhammad Mahmudul Hasan Yuhiu Zhang Nezih Pala Michael Shur Department of Electrical and Computer Engineering Florida International University Miami USA Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute New York USA

p-diamond is a strong contender for sub-THz and THz applications specifically due to its large hole effective mass, high optical phonon energy, and, therefore, high momentum relaxation time, and high mobility. It has the potential for efficient operation in the 300 GHz band targeted for future 6G communications. We review some of the recent works on p-diamond TeraFETs demonstrating their potential to detect and transmit sub-THz and THz radiation. We also report on the potential of n-diamond TeraFETs or emerging terahertz applications. One of the main factors in our research that account for the plasma wave dampness of the electron stream is the viscosity of the charge carrier medium in the channel.

关键词： Viscosity Electric potential Resonant frequency Voltage Phonons Logic gates Plasmons

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