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

作者： Eric Sihite Filip Slezak Ioannis Mandralis Adarsh Salagame Milad Ramezani Arash Kalantari Alireza Ramezani Morteza Gharib The Department of Aerospace Engineering California Institute of Technology Pasadena USA Department of Electrical and Computer Engineering The Silicon Synapse Labs Northeastern University Boston USA The Robotics and Autonomous Systems DATA61 CSIRO Brisbane QLD Australia The Jet Propulsion Laboratory Pasadena USA

Some animals exhibit multi-modal locomotion capability to traverse a wide range of terrains and environments, such as amphibians that can swim and walk or birds that can fly and walk. This capability is extremely beneficial for expanding the animal's habitat range and they can choose the most energy efficient mode of locomotion in a given environment. The robotic biomimicry of this multi-modal locomotion capability can be very challenging but offer the same advantages. However, the expanded range of locomotion also increases the complexity of performing localization and path planning. In this work, we present our morphing multi-modal robot, which is capable of ground and aerial locomotion, and the implementation of readily available SLAM and path planning solutions to navigate a complex indoor environment.

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On the Study of Success Serving Probability for Integrated Sensing and Communication (ISAC) Based on Stochastic Geometry

On the Study of Success Serving Probability for Integrated S...

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IEEE International Conference on Communications (ICC)

作者： Wentao Cheng Zhongyuan Zhao Howard H. Yang Wei Hong Tony Q.S. Quek Zhiguo Ding The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China ZJU-UIUC Institute Zhejiang University Haining China Beijing Xiaomi Mobile Software Beijing China Singapore University of Technology and Design Singapore Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi UAE

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Integrated sensing and communication (ISAC) has been proved as a promising technique to further improve the performance for both the communication and the sensing tasks in wireless networks. However, due to the complicated and dynamic interference circumstances, the performance of ISAC cannot be guaranteed. To provide some insights for keeping a sophisticated balance between communication and sensing with considering co-channel interference, the theoretical performance of ISAC is studied in this paper. First, an analytical system model is provided based on stochastic geometry. Second, the success serving probability (SSP) is defined for both the communication and the sensing tasks based on mutual information, which provided a unified analysis framework for ISAC. The tractable expressions of SSP are also derived. Finally, the simulation results are shown to verify the analytical results of SSP, which can provide some insights for the tradeoff between sensing and communication of ISAC.

关键词： Geometry Measurement Monte Carlo methods Wireless networks Simulation Stochastic processes Integrated sensing and communication

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Deep Learning-aided Parametric Sparse Channel Estimation for Terahertz Massive MIMO systems

arXiv

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arXiv 2024年

作者： Kim, Jinhong Ahn, Yongjun Kim, Seungnyun Shim, Byonghyo Samsung Electronics Seoul06765 Korea Republic of The Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States The Department of Electrical and Computer Engineering The Institute of New Media and Communications Seoul National University Seoul08826 Korea Republic of

Terahertz (THz) communications is considered as one of key solutions to support extremely high data demand in 6G. One main difficulty of the THz communication is the severe signal attenuation caused by the foliage loss, oxygen/atmospheric absorption, body and hand losses. To compensate for the severe path loss, multiple-input-multiple-output (MIMO) antenna array-based beamforming has been widely used. Since the beams should be aligned with the signal propagation path to achieve the maximum beamforming gain, acquisition of accurate channel knowledge, i.e., channel estimation, is of great importance. An aim of this paper is to propose a new type of deep learning (DL)-based parametric channel estimation technique. In our work, DL figures out the mapping function between the received pilot signal and the sparse channel parameters characterizing the spherical domain channel. By exploiting the long short-term memory (LSTM), we can efficiently extract the temporally correlated features of sparse channel parameters and thus make an accurate estimation with relatively small pilot overhead. From the numerical experiments, we show that the proposed scheme is effective in estimating the near-field THz MIMO channel in THz downlink environments. © 2024, CC BY-NC-ND.

关键词： Beamforming

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A Study of Robustness of a Closed-Loop System for Blood Pressure Control

A Study of Robustness of a Closed-Loop System for Blood Pres...

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American Control Conference (ACC)

作者： Taylor E. Baum Bharadwaj Satchidanandan Munther A. Dahleh Emery N. Brown Electrical Engineering and Computer Science Department Massachusetts Institute of Technology MA USA Department of Electrical Engineering and Computer Science The Laboratory for Information & Decision Systems The Institute for Data Systems and Society at the Massachusetts Institute of Technology MA USA Department of Anesthesia Critical Care and Pain Medicine The Massachusetts General Hospital MA USA The Picower Institute for Learning and Memory The Massachusetts Institute of Technology MA USA The Division of Sleep Medicine Harvard Medical School MA USA

Wide variability of patient response to vasoactive drugs, and mechanical limits of infusion pumps lead to difficulties in achieving robust Closed-Loop Blood Pressure Control (CLBPC). Our goal is to refine a previously proposed CLBPC system which emphasizes the incorporation of mechanistic cardiovascular models, design simple Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) controllers, and assess their robustness to estimation errors in physiological parameters of patients that are expected to vary widely within a patient population. A pharmacokinetic-pharmacodynamic (PK-PD) model that quantifies the impact of drugs, phenylephrine and nicardipine, on a patient’s blood pressure is provided. A state space model is then formulated which incorporates the full dynamics of a patient’s blood pressure. We then implement MPC and PID control to simulate regulation of blood pressure and explore the robustness of such controllers to errors in estimates of patient physiological parameters.

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Green Routing Game: Strategic Logistical Planning using Mixed Fleets of ICEVs and EVs

Green Routing Game: Strategic Logistical Planning using Mixe...

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IEEE Conference on Decision and Control

作者： Hampei Sasahara György Dán Saurabh Amin Henrik Sandberg Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Tokyo Japan Division of Network and Systems Engineering School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge MA USA Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper introduces a “green” routing game between multiple logistic operators (players), each owning a mixed fleet of internal combustion engine vehicle (ICEV) and electric vehicle (EV) trucks. Each player faces the cost of delayed delivery (due to charging requirements of EVs) and a pollution cost levied on the ICEVs. This cost structure models: 1) limited battery capacity of EVs and their charging requirement; 2) shared nature of charging facilities; 3) pollution cost levied by regulatory agency on the use of ICEVs. We characterize Nash equilibria of this game and derive a condition for its uniqueness. We also use the gradient projection method to compute this equilibrium in a distributed manner. Our equilibrium analysis is useful to analyze the trade-off faced by players in incurring higher delay due to congestion at charging locations when the share of EVs increases versus a higher pollution cost when the share of ICEVs increases. A numerical example suggests that to increase marginal pollution cost can reduce inefficiency of equilibria.

关键词： Costs Pollution Green products Internal combustion engines Games Routing Planning

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Autonomous nanorobots with powerful thrust under dry solid-contact conditions by photothermal shock

Research Square

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Research Square 2023年

作者： Gu, Zhaoqi Zhu, Runlin Shen, Tianci Dou, Lin Liu, Hongjiang Liu, Yifei Liu, Xu Liu, Jia Zhuang, Songlin Gu, Fuxing Laboratory of Integrated Opto-Mechanics and Electronics Shanghai Key Laboratory of Modern Optical System School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China Department of Industrial and Systems Engineering Auburn University AuburnAL36849 United States

Nanorobotic motion on solid substrates is greatly hindered by strong nanofriction, and powerful nanomotors‒the core components for nanorobotic motion‒are still lacking. Optical actuation addresses power and motion control issues simultaneously, while conventional technologies with small thrust usually apply to fluid environments. Here, we demonstrate micronewton-thrust nanomotors that enable the autonomous nanorobots working like conventional robots with precise motion control on dry surfaces by a photothermal-shock technique. We build a pulsed laser-based actuation and trapping platform, termed photothermal-shock tweezers, for general motion control of metallic nanomaterials and assembled nanorobots with nanoscale precision. The thrust-to-weight ratios up to 107 enable nanomotors output forces to interact with external micro/nano-objects. Leveraging machine vision and deep learning technologies, we assemble the nanomotors into autonomous nanorobots with complex structures, and demonstrate multi-degree-of-freedom motion and sophisticated functions. Our photothermal shock-actuation concept fundamentally addresses the nanotribology challenges and expands the nanorobotic horizon from fluids to dry solid surfaces. © 2023, CC BY.

关键词： Nanorobotics

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Feature-Based Aggregation and Deep Reinforcement Learning:A Survey and Some New Implementations

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 1-31页

作者： Dimitri P.Bertsekas the Department of Electrical Engineering and Computer Science and the Laboratory for Information and Decision SystemsMassachusetts Institute of Technology

In this paper we discuss policy iteration methods for approximate solution of a finite-state discounted Markov decision problem, with a focus on feature-based aggregation methods and their connection with deep reinforcement learning schemes. We introduce features of the states of the original problem, and we formulate a smaller "aggregate" Markov decision problem, whose states relate to the features. We discuss properties and possible implementations of this type of aggregation, including a new approach to approximate policy iteration. In this approach the policy improvement operation combines feature-based aggregation with feature construction using deep neural networks or other calculations. We argue that the cost function of a policy may be approximated much more accurately by the nonlinear function of the features provided by aggregation, than by the linear function of the features provided by neural networkbased reinforcement learning, thereby potentially leading to more effective policy improvement.

关键词： Reinforcement learning dynamic programming Markovian decision problems aggregation feature-based architectures policy iteration deep neural networks rollout algorithms

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Multi-energy systems: Modelling approaches and energy storage potential 12

Multi-energy systems: Modelling approaches and energy storag...

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12th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, MEDPOWER 2020

作者： Vomva, Styliani A. Christoforidis, Georgios C. Papagiannis, Grigoris K. Power Systems Laboratory School of Electrical and Computer Engineering Aristotle University of Thessaloniki Greece Department of Electrical and Computer Engineering University of W. Macedonia Kozani Greece

ISBN: (纸本)9781839535635

The decarbonization of energy systems implies the further exploitation of renewable energy resources. To facilitate their integration into the existing systems, while also improving their efficiency, multi-energy systems could play a vital role, accompanied also by the integration of storage components. In such an approach, electricity, thermal energy and gas infrastructures collaborate to meet the overall energy demand. The modelling and optimization of such systems are complex, as multiple heterogeneous variables and parameters should be considered when designing the system and time-scheduling its operation. This paper presents an overview of modelling approaches in this framework. Moreover, storage potential that arises through the collaboration of multiple energy forms is introduced. To enhance the usage of such approaches by policymakers, dedicated tools must be developed, incorporating networks limitations and components constraints. © 2020 Institution of engineering and Technology. All rights reserved.

关键词： Renewable energy resources

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Experimental implementation of chaos-based video encryption using visible light communication technology

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Applied Optics 2025年第9期64卷 C101-C118页

作者： Fotso, Sorel Bagio Nono Mbé, Jimmi Hervé Talla Takotue, Jean Ernest Takougang, Armand Cyrille Nzeukou Ndjiongue, Alain Richard Research Unit of Condensed Matter Electronics and Signal Processing Department of Physics University of Dschang P.O. Box 67 Dschang Cameroon Research Unit of Automation and Applied Computer Department of Electrical Engineering IUT-FV Bandjoun University of Dschang P.O. Box: 134 Bandjoun Cameroon Laboratory of Industrial Systems and Environmental Engineering Fotso Victor University Institute of Technology University of Dschang P.O. Box 134 Bandjoun Cameroon School of Electrical and Information Engineering Faculty of Engineering and the Built Environment University of the Witwatersrand Johannesburg South Africa

Simulations are commonly used to develop and evaluate video encryption algorithms. Although these approaches are useful for demonstrating theoretical feasibility and algorithm performance, they neglect practical challenges and real-world communication conditions. This oversight creates a critical gap in evaluating their effectiveness and security in practical applications. In this paper, we describe a novel, to the best of our knowledge, video encryption scheme that employs a modified chaotic Colpitts oscillator, a customized Josephus problem, and ribonucleic acid (RNA) operations, and is implemented in visible light communication (VLC) environment. The modified Colpitts oscillator reveals significant phenomena, the most prominent for this study being chaos. The encryption scheme involves block scrambling and pixel-level permutation employing a customized Josephus problem and a column and row shifting technique. Diffusion is then achieved through a custom Josephus problem-oriented RNA operation combined with basic RNA operations and cipher block chaining (CBC). Based on the results, we found that the customized Josephus problem-based permutation performed more efficiently than traditional methods, whereas the column and row shifting permutation was more robust. By eliminating key sequence coding and item-to-item operations, the proposed RNA operation reduces computational overhead. This video encryption scheme is proven to be effective and resilient at securing video data transmitted over the VLC channel, and it constitutes a significant advancement in areas such as surveillance, medical imaging, and military communication requiring robust secured video data. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Medical imaging

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A Robust Polyscale Length Complexity Measure for Stochastic Self-Affine Processes

A Robust Polyscale Length Complexity Measure for Stochastic ...

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IEEE International Conference on Cognitive Informatics

作者： Witold Kinsner Department of Electrical and Computer Engineering Cognitive Systems Laboratory University of Manitoba Winnipeg Canada

ISBN: (纸本)9781665421201

Cognitive and other nonlinear systems often involve deterministic differentiable processes and stochastic non-differentiable processes. Measuring the complexity of such processes is important when extracting objective features from the processes for their classification in either reactive, or adaptive, or predictive control. This applies to classifiers based not only to the traditional neural networks, but also to deep learning systems, and particularly in cognitive systems. This paper describes a robust algorithm to measure the length complexity of a self-affine time series using multiscale and polyscale analyses, and provides new insight in the theoretical and practical aspects of extracting the measure.

关键词： Time series analysis Neural networks Length measurement Feature extraction Prediction algorithms Time measurement Complexity theory

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