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IEEE International Conference on Robotics and Automation (ICRA)

作者： Hamed Damirchi Roohollah Khorrambakht Hamid D. Taghirad Behzad Moshiri Advanced Robotics and Automated Systems Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering New York University New York USA School of ECE University College of Engineering University of Tehran Tehran Iran

Conventionally, deep odometry networks use objective functions that only penalize short-term deviations from the true path. Since such an objective does not impose any constraints on the long-term deviations from the path, a second consistency-based loss term may be added to lower long-term drift. However, maintaining a balance between the two loss terms is challenging and often treated as a design hyperparameter. To mitigate this balancing issue, we propose to use the uncertainty over both odometry and the long-term transformations in a maximum likelihood setting and allow the network to tune the weighting between the two loss terms. To this end, we derive the odometry uncertainty alongside the pose outputs using the network itself and to derive the covariance matrix over the integrated transformation, we propose to propagate the odometry uncertainty through each iteration. This formulation provides an adaptive and statistically consistent method to weigh the incremental and integrated loss terms against each other, noting the increase in uncertainty as more steps are integrated over. We show that our approach to consistency-based losses allows the network to surpass the accuracy of the state-of-the-art visual odometry approaches. Then, the efficacy of the derived uncertainty as weighting medium is visualized and the performance benefits of uncertainty quantification are shown in a pose-graph based localization scenario.

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Graph-Based Local Planning with Spatiotemporal Risk Assessment for Risk-Bounded and Prediction-Aware Autonomous Driving

Graph-Based Local Planning with Spatiotemporal Risk Assessme...

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International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Abdulrahman Ahmad Majid Khonji Ameena Al-Sumaiti Jorge Dias Khaled Elbassioni Department of Computer Science Khalifa University Abu Dhabi UAE Khalifa University Center for Autonomous Robotic Systems (KUCARS) Abu Dhabi UAE Department of Electrical Engineering Smart OR Lab Advanced Power Energy Center (APEC) Khalifa University Abu Dhabi UAE Department of Computer and Information Engineering Khalifa University Abu Dhabi UAE

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

Risk-bounded motion planning for autonomous driving in dynamic environments presents significant research challenges. Ensuring continuous navigation towards a destination while making real-time decisions is a nonconvex problem. This paper presents a graph-based local planning method constrained by user-specific driving preference, represented as a risk-bound criterion for motion planning. First, we propose a lattice graph construction method that adheres to the vehicle's curvature constraints. Then, we formulate the trajectory planning problem as an integer-linear programming task, addressed by our novel risk-bounded and prediction-aware constrained shortest path. Our solution accounts for both static and dynamic obstacles in urban settings, adhering to traffic regulations. At the core of our approach is a conservative spatiotemporal risk assessment mechanism, which evaluates collisions considering the uncertain delay from speed control of the ego vehicle and predicted trajectories of dynamic obstacles. We implemented our solution using the CARLA simulator and the ROS2 platform, within a comprehensive framework encompassing global planning, local planning, and vehicle control. The effectiveness of our approach is demonstrated through notable collision avoidance, improved path-tracking, and enhanced risk-bounded planning capabilities.

关键词： Trajectory planning Dynamics Velocity control Planning Spatiotemporal phenomena Trajectory Risk management Vehicle dynamics Collision avoidance Autonomous vehicles

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Novel Dielectric Fluids for Superconducting Electric Aircraft

Novel Dielectric Fluids for Superconducting Electric Aircraf...

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2021 AIAA/IEEE Electric Aircraft Technologies Symposium, EATS 2021

作者： Mensah, Paul Herrera, H.L. Cheetham, Peter Kim, Chul Pamidi, Sastry Florida State University Center for Advanced Power Systems TallahasseeFL32310 United States FAMU-FSU College of Engineering Department of Electrical & Computer Engineering TallahasseeFL32310 United States

ISBN: (纸本)9781624106118

The need for effective cryogenic dielectric media for achieving superconducting power systems for electric aircraft is discussed. The dielectric fluid, Novec-649 was explored as an option for cryogenic dielectric media both as solid media for superconducting cables and as a liquid for cryogenic power electronic systems and termination interfaces. Measurements of dielectric strength of Novec-649 were performed at room temperature and cryogenic temperatures. The measured dielectric strength of > 15 kV/mm shows promise for electric aircraft applications. The need to maintain the purity of the fluid and prevent cracking and void formation during the freezing process to maintain the dielectric integrity of the fluid is emphasized. © 2021 AIAA.

关键词： Cryogenics

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Impact of Techno-Economic Parameters on Optimal Sizing of EV Fast Charging Stations

Impact of Techno-Economic Parameters on Optimal Sizing of EV...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Anindita Golder Sheldon S. Williamson Department of Electrical and Computer Engineering Smart Transportation Electrification and Energy Research (STEER) Group Advanced Storage Systems and Electric Transportation (ASSET) Laboratory Ontario Tech-Automotive Center of Excellence (ACE) Faculty of Engineering and Applied Science Ontario Tech University Oshawa Canada

ISBN: (数字)9798350317664

ISBN: (纸本)9798350317671

As the adoption for electric vehicles (EV) increases, the need for proper charging infrastructure also increases. As such, it is necessary to ensure proper charging infrastructure to meet the charging demand. Hence, studies concerning the planning of EV charging stations which include the sizing of distributed energy resources (DERs) in the station to reduce the peak demand on the grid. In this paper, EV charging stations were designed keeping in mind factors such as the EV charging load profile (on demand charging versus deferred charging), uncertainties in the load profile as well as the tariff rates. A sensitivity analysis was also carried out in order to examine the impact of several techno-economic parameters on the overall cost of the system.

关键词： Vehicle-to-grid Costs Uncertainty Sensitivity analysis Tariffs Vehicular ad hoc networks Transportation

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Wireless Body Area Networks: Applications and Congestion Control Technologies

Wireless Body Area Networks: Applications and Congestion Con...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Ahmed Shakir Al-Hiti Ratna KZ Sahbudin SW Harun Ammar Naser Obaid Mustafa Maad Hamdi Mahmood A. Al-Shareeda Department of Electrical Engineering Faculty of Engineering University of Anbar Al-Anbar Iraq Department of Computer and Communication Systems Engineering Universiti Putra Malaysia Serdang Selangor Malaysia Department of Electrical Engineering Faculty of Engineering University of Malaya Kuala Lumpur Malaysia Department of computer engineering techniques Al-Maarif University College Al-Anbar Iraq National Advanced IPv6 Centre (NAv6) Universiti Sains Malaysia (USM) Penang Malaysia

Wireless body area networks (WBANs) have been used widely as sensor nodes are implanted into the body, on the body, or around the body. Many methods have been proposed concerning different issues existing in this network. Congestion is one of the vital and earnest problems in the transport layer. So, researchers are looking for a solution to avoid congestion in the network to properly transfer data between the nodes. In this work, we provide a review of WBANs applications and also congestion methods that have been proposed in WBANs. The congestion methods can be optimized through the performance parameters like delay, throughput, packet loss, data rate, and queue length.

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A Material Identification Approach Based on Wi-Fi Signal

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computers, Materials & Continua 2021年第12期69卷 3383-3397页

作者： Chao Li Fan Li Wei Du Lihua Yin Bin Wang Chonghua Wang Tianjie Luo Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510700China PCL Research Center of Cyberspace Security Peng Cheng LaboratoryShenzhen518052China Department of Computer Science and Computer Engineering University of ArkansasFayetteville72701USA College of Electrical Engineering Zhejiang UniversityHangzhou310058China China Industrial Control Systems Cyber Emergency Response Team Beijing100040China

Material identification is a technology that can help to identify the type of target *** approaches depend on expensive instruments,complicated pre-treatments and professional *** is difficult to find a substantial yet effective material identification method to meet the daily use *** this paper,we introduce a Wi-Fi-signal based material identification approach by measuring the amplitude ratio and phase difference as the key features in the material classifier,which can significantly reduce the cost and guarantee a high level *** practical measurement of WiFi based material identification,these two features are commonly interrupted by the software/hardware noise of the channel state information(CSI).To eliminate the inherent noise of CSI,we design a denoising method based on the antenna array of the commercial off-the-shelf(COTS)Wi-Fi *** that,the amplitude ratios and phase differences can be more stably utilized to classify the *** implement our system and evaluate its ability to identify materials in indoor *** result shows that our system can identify 10 commonly seen liquids with an average accuracy of 98.8%.It can also identify similar liquids with an overall accuracy higher than 95%,such as various concentrations of salt water.

关键词： Internet of Things Wi-Fi signal channel state information material identification noise elimination

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A Robust Adversary Detection-Deactivation Method for Metaverse-oriented Collaborative Deep Learning

arXiv

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arXiv 2023年

作者： Li, Pengfei Zhang, Zhibo Al-Sumaiti, Ameena S. Werghi, Naoufel Yeun, Chan Yeob Advanced Power and Energy Center Electrical Engineering and Computer Science Department Khalifa University Abu Dhabi United Arab Emirates Department of Electrical and Computer Engineering Khalifa University Abu Dhabi United Arab Emirates Center for Cyber-Physical Systems Khalifa University Abu Dhabi United Arab Emirates

Metaverse is trending to create a digital circumstance that can transfer the real world to an online platform supported by large quantities of real-time interactions. Pre-trained Artificial Intelligence (AI) models are demonstrating their increasing capability in aiding the metaverse to achieve an excellent response with negligible delay, and nowadays, many large models are collaboratively trained by various participants in a manner named collaborative deep learning (CDL). However, several security weaknesses can threaten the safety of the CDL training process, which might result in fatal attacks to either the pre-trained large model or the local sensitive data sets possessed by an individual entity. In CDL, malicious participants can hide within the major innocent and silently uploads deceptive parameters to degenerate the model performance, or they can abuse the downloaded parameters to construct a Generative Adversarial Network (GAN) to acquire the private information of others illegally. To compensate for these vulnerabilities, this paper proposes an adversary detection-deactivation method, which can limit and isolate the access of potential malicious participants, quarantine and disable the GAN-attack or harmful backpropagation of received threatening gradients. A detailed protection analysis has been conducted on a Multiview CDL case, and results show that the protocol can effectively prevent harmful access by heuristic manner analysis and can protect the existing model by swiftly checking received gradients using only one low-cost branch with an embedded firewall. © 2023, CC BY-NC-SA.

关键词： Generative adversarial networks

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Design and Evaluation of a Low-profile Haptic Interface Based on Surface electrical Nerve Stimulation

Design and Evaluation of a Low-profile Haptic Interface Base...

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Telepresence, IEEE Conference on

作者： Rachel S. Jakes Luis Mesias Veronica J. Santos Michael J. Fu Dustin J. Tyler Human Fusions Institute (HFI) Case Western Reserve University (CWRU) Dept. of Biomedical Engineering CWRU Dept. of Electrical Computer and Systems Engineering CWRU Dept. of Mechanical and Aerospace Engineering University of California Los Angeles (UCLA) Dept. of Physical Medicine & Rehabilitation The MetroHealth System Dept. of VA Northeast Ohio Healthcare System Advanced Platform Technology Center

ISBN: (数字)9798331528249

ISBN: (纸本)9798331528256

Haptic feedback in telepresence applications is vital for remote task performance and object manipulation. To maximize telepresence capabilities, haptic systems need to be integrated with immersive telepresence interfaces such as virtual reality, which offer benefits such as improved spatial awareness and operator mobility. Compatibility with the mobility of these systems and their built-in optical hand tracking require low-profile wearable interfaces. Further, for full functional benefits, haptic systems must be able to elicit spatially congruent sensation without impeding operator movement and physical object interactions. In this paper, we describe the design of a lightweight, compact, and adaptable surface electrical nerve stimulation-based haptic interface. We demonstrate its capacity to consistently generate spatially congruent sensation on the all five fingertips without occlusion, as well as its compatibility with headset-based optical hand tracking.

关键词： Hands Telepresence Tracking Stimulated emission Optical feedback Virtual reality electrical stimulation Haptic interfaces Optical sensors

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A Little Chit-Chat Goes a Long Way: Design and Evaluation of Task-and Person-Oriented Styles for Social Robots

A Little Chit-Chat Goes a Long Way: Design and Evaluation of...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Elie Saad Joost Broekens Mark A. Neerincx Department of Intelligent Systems Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Delft The Netherlands School of Engineering Holy Spirit University of Kaslik Jounieh Lebanon The Leiden Institute of Advanced Computer Science Leiden University Leiden The Netherlands The Netherlands Organization for Applied Scientific Research (TNO) Soesterberg The Netherlands

ISBN: (数字)9798350375022

ISBN: (纸本)9798350375039

Whereas the reception task is a promising application domain for social robots, knowledge is lacking about how to design the appropriate re-usable communication styles for a reception robot. This paper presents the use and evaluation of an iterative interaction-design (ID) method with which task- and person-oriented multi-modal communication styles have been designed for such a robot. First, we report on an evaluation study of the ID-method with Industrial Design students (N =13) who designed these two communication styles for a Pepper robot. This provided a set of distinct designs of the two styles, for which the differences in design parameters were in line with social science theory. The task-oriented style showed a more formal, shorter and less chatty communication. Second, we present findings from a Mechanical Turk study conducted to evaluate the perception of these style designs. Participants (N =301) were presented with videos showing the robot acting as a receptionist and were asked to rate their perception of the robot, the service experience and the orientation of the designs. Overall, the interaction with the robot was appreciated well. The robot with a person-oriented style was perceived to be more animate and likeable. Analysis showed that chit-chat was the main contributor to the perceived difference between the person-oriented and task-oriented styles. This is an important finding as it gives interaction designers a validated best-practice approach to make interaction style more or less personal.

关键词： Service robots Social robots Design tools Behavioral sciences Iterative methods Robots Videos

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Group-equivariant autoencoder for identifying spontaneously broken symmetries

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Physical Review E 2023年第5期107卷 054104-054104页

作者： Devanshu Agrawal Adrian Del Maestro Steven Johnston James Ostrowski Department of Industrial and Systems Engineering University of Tennessee Knoxville Tennessee 37996 USA Department of Physics and Astronomy University of Tennessee Knoxville Tennessee 37996 USA Min H. Kao Department of Electrical Engineering and Computer Science University of Tennessee Knoxville Tennessee 37996 USA Institute for Advanced Materials and Manufacturing University of Tennessee Knoxville Tennessee 37996 USA

We introduce the group-equivariant autoencoder (GE autoencoder), a deep neural network (DNN) method that locates phase boundaries by determining which symmetries of the Hamiltonian have spontaneously broken at each temperature. We use group theory to deduce which symmetries of the system remain intact in all phases, and then use this information to constrain the parameters of the GE autoencoder such that the encoder learns an order parameter invariant to these “never-broken” symmetries. This procedure produces a dramatic reduction in the number of free parameters such that the GE-autoencoder size is independent of the system size. We include symmetry regularization terms in the loss function of the GE autoencoder so that the learned order parameter is also equivariant to the remaining symmetries of the system. By examining the group representation by which the learned order parameter transforms, we are then able to extract information about the associated spontaneous symmetry breaking. We test the GE autoencoder on the 2D classical ferromagnetic and antiferromagnetic Ising models, finding that the GE autoencoder (1) accurately determines which symmetries have spontaneously broken at each temperature; (2) estimates the critical temperature in the thermodynamic limit with greater accuracy, robustness, and time efficiency than a symmetry-agnostic baseline autoencoder; and (3) detects the presence of an external symmetry-breaking magnetic field with greater sensitivity than the baseline method. Finally, we describe various key implementation details, including a quadratic-programming-based method for extracting the critical temperature estimate from trained autoencoders and calculations of the DNN initialization and learning rate settings required for fair model comparisons.

关键词： Phase transitions Structural order parameter Data analysis

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