Filters








50 Hits in 4.7 sec

Design and Realization of Avionics Integration Simulation System Based on RTX

Liang Wang, Bo Li, Hengxian Tang, E. Bollin, M. Guo, I. Koşalay
2016 MATEC Web of Conferences  
A design and realization method of avionics integration simulation system based on RTX was brought forward to resolve the problem.  ...  All kinds of aircraft avionics system HIL (hardware-in-loop) simulations can be implemented in this platform.  ...  In this paper, a design and realization method of AISS (avionics integration simulation system) based on RTX is introduced to resolve the problem.  ... 
doi:10.1051/matecconf/20165001002 fatcat:frr6hqgqe5ardasppzo5rdh4qu

Multisensory Testing Framework for Advanced Driver Assistant Systems Supported by High-Quality 3D Simulation

Paweł Jabłoński, Joanna Iwaniec, Michał Jabłoński
2021 Sensors  
The first, open-loop experiment explains the real-time capabilities of the system based on the Mobileye 6 camera sensor detections.  ...  The second experiment runs a real-time closed-loop test of a lane-keeping algorithm (LKA) based on the Mobileye 6 line detection.  ...  The real-time performance of Morphee is based on its ability to run processes on the RTX subsystem [20] .  ... 
doi:10.3390/s21248458 pmid:34960548 pmcid:PMC8709301 fatcat:o6f77pvfhng7lfq5kxdx4vj3ea

Scalable real-time controller hardware-in-the-loop testing for multiple interconnected converters

Andreas Avras, Andrew J. Roscoe, Graeme M. Burt
2014 2014 49th International Universities Power Engineering Conference (UPEC)  
The controller prototyping, including the converter switching strategy will be implemented on ADI's rtX and the use of other rapid controller prototyping systems will also be evaluated.  ...  To that end it will focus on real-time representation of converter devices on different platforms, enabling the future coupling of prototyping controllers to power system simulation tools.  ...  The hardware-based real-time approach or Hardware-In the-Loop (HIL) simulation, involves the modelling representation of only a part of the system while the rest is actual hardware.  ... 
doi:10.1109/upec.2014.6934620 fatcat:jpo6k3wkgfewhm7pw76357qqwy

A Framework for Hardware-in-the-Loop Testing of an Integrated Architecture [chapter]

Martin Schlager, Roman Obermaisser, Wilfried Elmenreich
2007 Lecture Notes in Computer Science  
transducers of the ISUT without a probe effect on the ISUT.  ...  Our approach enables a complexity reduction for setting up an HiL simulation and supports a well-designed scalable interface to an integrated architecture.  ...  IST-511764, and DOC [doktorandenprogramm derösterreichischen akademie der wissenschaften]. We would like to thank Bernhard Wenzl for proofreading an earlier version of this paper.  ... 
doi:10.1007/978-3-540-75664-4_16 fatcat:g5dft3ttcfgzbo252h3uj2y5jm

Applications of Real-Time Simulation Technologies in Power and Energy Systems

Xavier Guillaud, M. Omar Faruque, Alexandre Teninge, Ali Hasan Hariri, Luigi Vanfretti, Mario Paolone, Venkata Dinavahi, Pinaki Mitra, Georg Lauss, Christian Dufour, Paul Forsyth, Anurag K. Srivastava (+3 others)
2015 IEEE Power and Energy Technology Systems Journal  
Real-time (RT) simulation is a highly reliable simulation method that is mostly based on electromagnetic transient simulation of complex systems comprising many domains.  ...  This Task Force paper summarizes various applications of digital RT simulation technologies in the design, analysis, and testing of power and energy systems.  ...  ACKNOWLEDGMENT Task Force on Real-Time Simulation Technologies for Power Systems Analysis is with the Working Group on Modeling and Analysis of System Transients Using Digital  ... 
doi:10.1109/jpets.2015.2445296 fatcat:u3hz6kdaf5gcnmlx6pxanh2omi

Air Learning: a deep reinforcement learning gym for autonomous aerial robot visual navigation

Srivatsan Krishnan, Behzad Boroujerdian, William Fu, Aleksandra Faust, Vijay Janapa Reddi
2021 Machine Learning  
We then propose a mitigation technique that uses the hardware-in-the-loop to determine the latency distribution of running the policy on the target platform (onboard compute on aerial robot).  ...  Air Learning assesses the policies' performance under various quality-of-flight (QoF) metrics, such as the energy consumed, endurance, and the average trajectory length, on resource-constrained embedded  ...  Acknowledgements The effort at Harvard University and The University of Texas at Austin was sponsored by support from Intel.  ... 
doi:10.1007/s10994-021-06006-6 fatcat:zvrkocl7arb7vpdnlulhd3gb7u

Cloud2Edge Elastic AI Framework for Prototyping and Deployment of AI Inference Engines in Autonomous Vehicles [article]

Sorin Grigorescu, Tiberiu Cocias, Bogdan Trasnea, Andrea Margheri, Federico Lombardi, Leonardo Aniello
2020 Sensors   pre-print
(SiL) paradigm, while deployment and evaluation on the target ECUs (Electronic Control Units) is performed as Hardware-in-the-Loop (HiL) testing.  ...  The effectiveness of the proposed framework is demonstrated using two real-world use-cases of AI inference engines for autonomous vehicles, that is environment perception and most probable path prediction  ...  Therefore, the main contributions of the paper are: • a simple yet elegant AI Inference Engine concept, based on the SiL and HiL principles; • a data-driven V-Model approach guiding the design of AI-based  ... 
doi:10.3390/s20195450 pmid:32977409 pmcid:PMC7582930 arXiv:2009.11722v1 fatcat:t4zglrnltfdmjnxlemaxwmsjqq

TinyOdom

Swapnil Sayan Saha, Sandeep Singh Sandha, Luis Antonio Garcia, Mani Srivastava
2022 Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies  
However, existing neural inertial dead-reckoning frameworks are not suitable for real-time deployment on ultra-resource-constrained (URC) devices due to substantial memory, power, and compute bounds.  ...  Across different applications, TinyOdom reduces the size of neural inertial models by 31× to 134× with 2.5m to 12m error in 60 seconds, enabling the direct deployment of models on URC devices while still  ...  We also thank Jason Wu from the Networked and Embedded Systems Laboratory at the University of California -Los Angeles for aiding us in the data collection phase during the real-world setup.  ... 
doi:10.1145/3534594 fatcat:n2nbtuf73nbl3jg7qj2cmd36mq

Realtime Rooftop Landing Site Identification and Selection in Urban City Simulation [article]

Jeremy Castagno, Yu Yao, Ella Atkins
2019 arXiv   pre-print
This paper investigates the real-time identification and selection of safe landing zones on rooftops based on LiDAR and camera sensor feedback.  ...  AirSim, a robotic simulator plugin for Unreal, offers drone simulation and control and is capable of outputting video and LiDAR sensor data streams from the simulated Unreal world.  ...  We modified models based on tensorflow implementations [26] and perform training on a system with an Nvidia RTX 2080 GPU.  ... 
arXiv:1903.03829v1 fatcat:p53lmmjvevefnncddg2gfvx3te

SPEED+: Next-Generation Dataset for Spacecraft Pose Estimation across Domain Gap [article]

Tae Ha Park, Marcus Märtens, Gurvan Lecuyer, Dario Izzo, Simone D'Amico
2021 arXiv   pre-print
Autonomous vision-based spaceborne navigation is an enabling technology for future on-orbit servicing and space logistics missions.  ...  SPEED+ is used in the second international Satellite Pose Estimation Challenge co-hosted by SLAB and the Advanced Concepts Team of the European Space Agency to evaluate and compare the robustness of spaceborne  ...  All methods are implemented with PyTorch v1.8.0 and trained on an NVIDIA GeForce RTX 2080 Ti 12GB GPU.First, the training of KRN [4] largely follows the original work, except it instead uses the AdamW  ... 
arXiv:2110.03101v2 fatcat:q2gzjwhcdvdjvcbdu2y6sf7ovu

Report on standardization process and results of analytical studies

Thomas I. Strasser, Felix Lehfuss, Christoph Mayr, Filip Andrén, Georg Lauss, Evangelos Rikos, Eric Lambert, Vasilis Kleftakis, Panos Kotsampopoulos, Alexandros Rigas, Ron Brandl, Iñigo Vidaurrazaga (+7 others)
2013 Zenodo  
One main focus of this last deliverable is on the description of available real-time simulation and Hardware-in-the-Loop equipment available in laboratories of the DERri partners with special focus on  ...  With this document the work in the DERri "JRA3 Real time simulation environment and parameter identification for power systems" will be finished.  ...  The platform allows the user to design a Matlab/Simulink control model, upload it to the Target PC and connect the user's PC to the Target PC to allow real-time control of and interaction with the inverter  ... 
doi:10.5281/zenodo.4316937 fatcat:tonxdqi2ejh4bd7q4vzr5yotyu

A Holistic Robust Motion Controller Framework for Autonomous Platooning [article]

Hong Wang, Li-Ming Peng, Zi-Chun Wei, Kai Yang, Xian-Xu Bai, Luo Jiang, Ehsan Hashemi
2022 arXiv   pre-print
The average conducting time of the proposed method on Speedgoat real-time target machine is 1.1 milliseconds, which meets the real-time requirements.  ...  The vehicle-to-vehicle (V2V) communication delay and the sudden appearance of obstacles will trigger the safety of the intended functionality (SOTIF) issues for autonomous platooning.  ...  The MCF algorithm of one vehicle runs on the Speedgoat real-time target machine (Intel Core i7, 2.5 GHz), while the vehicle dynamic models and traffic scenario is implemented in the Concurrent real-time  ... 
arXiv:2206.04948v1 fatcat:6tcz662txfgutk4jwyz7ipd7ve

Benchmarking Neuromorphic Hardware and Its Energy Expenditure

Christoph Ostrau, Christian Klarhorst, Michael Thies, Ulrich Rückert
2022 Frontiers in Neuroscience  
This model enables the prediction of the energy expenditure of a network on a target system without actually having access to it.  ...  We propose and discuss a platform overarching benchmark suite for neuromorphic hardware.  ...  We thank James Knight from the University of Sussex for support regarding the GeNN implementation.  ... 
doi:10.3389/fnins.2022.873935 pmid:35720731 pmcid:PMC9201569 fatcat:33hyeoi525fondbz3jwblazpom

Massively Digitized Power Grid: Opportunities and Challenges of Use-inspired AI [article]

Le Xie, Xiangtian Zheng, Yannan Sun, Tong Huang, Tony Bruton
2022 arXiv   pre-print
The impact of these three factors on critical functions of power system operation and planning practices are reviewed and illustrated with industrial practice case studies.  ...  It argues that the intricate interplay of data availability, computing capability, and artificial intelligence (AI) algorithm development are the three key factors driving the adoption of digitized solutions  ...  ACKNOWLEDGEMENTS The authors sincerely thank Jimmy Liu, Steven Dennis, and Thomas Wilson for their help on the Oncor use cases presented in this paper.  ... 
arXiv:2205.05180v1 fatcat:ecmq2wqy2nhk7e2zcabwdkhltq

Architecture for modeling and simulation of technical systems along their lifecycle

Tim Schenk, Albert B. Gilg, Monika Mühlbauer, Roland Rosen, Jan C. Wehrstedt
2015 Computing and Visualization in Science  
In this paper, a simulation architecture is presented and discussed on three different industrial applications, which offers a client-server concept to master the challenges of a lifecycle spanning simulation  ...  Due to the fact of increasing complexity of such systems, e.g. plants, cyber-physical systems and infrastructures, system simulation is rapidly gaining impact.  ...  Later on, for virtual commissioning, an emulated PLC, such as SIMATIC S7 PLCSim [20] , SIMATIC WinAC RTX [21] or SIMIT Emulation Platform [22] , is added to the architecture to analyze real PLC software  ... 
doi:10.1007/s00791-015-0256-9 fatcat:7unhx3t6vrdzfd6wnkeiuiuvmq
« Previous Showing results 1 — 15 out of 50 results