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Self-supervised learning as an enabling technology for future space exploration robots: ISS experiments 67

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Self-supervised learning as an enabling technology for futur...

67th International Astronautical Congress, IAC 2016

作者： Van Hecke, Kevin De Croon, Guido C.H.E. Hennes, Daniel Setterfield, Timothy P. Saenz-Otero, Alvar Izzo, Dario MAV-Lab. Control and Simulation Faculty of Aerospace Engineering TU Delft Netherlands Advanced Concepts Team of the European Space Agency ESTEC Noordwijk Netherlands Space Systems Lab. Massachusetts Institute of Technology CambridgeMA United States

Future space missions will increasingly rely on the help of robotic systems and in some cases even be performed purely by fully autonomous robots. Currently, robots lack the ability to learn from their environment. Learning is advantageous, since it decreases engineering effort and allows the robot to adapt to specific properties of its potentially yet unknown environment. However, in space robotics machine learning is not yet used, as it introduces extra risk for safety-critical missions. In this talk, we will introduce self-supervised learning as a reliable learning method that allows robots to adapt to their environment. We have previously successfully tested this method for the navigation of autonomous drones on Earth, which showed its potential in terms of reliability for application in space. Here, we will present preliminary results from an ISS test performed with the MIT/NASA SPHERES VERTIGO satellite, which is equipped with a stereo vision system that allows it to see distances and navigate by itself in the ISS. The presented preliminary experiments were performed on October 8th 2015 on board the ISS. In the experiments, the satellite learned by itself how to see distances with a single camera. It did so by using the distance estimates from its stereo vision process as supervised learning targets. The main advantage of this learning method is that the robot becomes robust against losing the images from one of the cameras - it can then still continue to function. The main goals of the experiment were (1) data gathering, and (2) navigation on the basis of stereo vision. First the astronaut Kimya Yui moved the satellite around the Japanese Experiment Module to gather stereo vision data for learning. Subsequently, the satellite freely explored the space in the module based on its (trusted) stereo vision system and a pre-programmed exploration behavior, while simultaneously performing the self-supervised learning on board in the background. The two main goals we

关键词： Satellites

Solving almost all systems of random quadratic equations

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arXiv 2017年

作者： Wang, Gang Giannakis, Georgios B. Saad, Yousef Chen, Jie Digital Technology Center Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States State Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Department of Computer Science and Engineering University of Minnesota MinneapolisMN55455 United States

This paper deals with finding an n-dimensional solution x to a system of quadratic equations of the form yi = jhai;xij2 for 1 ≤ i ≤ m, which is also known as phase retrieval and is NP-hard in general. We put forth a novel procedure for minimizing the amplitude-based least-squares empirical loss, that starts with a weighted maximal correlation initialization obtainable with a few power or Lanczos iterations, followed by successive refinements based upon a sequence of iteratively reweighted (generalized) gradient iterations. The two (both the initialization and gradient flow) stages distinguish themselves from prior contributions by the inclusion of a fresh (re)weighting regularization technique. The overall algorithm is conceptually simple, numerically scalab.e, and easy-to-implement. For certain random measurement models, the novel procedure is shown capable of finding the true solution x in time proportional to reading the data f(ai;yi)g1≤i≤m. This holds with high probability and without extra assumption on the signal x to be recovered, provided that the number m of equations is some constant c > 0 times the number n of unknowns in the signal vector, namely, m > cn. Empirically, the upshots of this contribution are: I) (almost) 100% perfect signal recovery in the high-dimensional (say e.g., n ≥2;000) regime given only an information-theoretic limit number of noiseless equations, namely, m = 2n - 1 in the real-valued Gaussian case;and, ii) (nearly) optimal statistical accuracy in the presence of additive noise of bounded support. Finally, substantial numerical tests using both synthetic data and real images corroborate markedly improved signal recovery performance and computational efficiency of our novel procedure relative to state-of-the-art approaches. Copyright © 2017, The Authors. All rights reserved.

关键词： Computational efficiency

Robust and Scalab.e Power System State Estimation via Composite Optimization

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arXiv 2017年

作者： Wang, Gang Giannakis, Georgios B. Chen, Jie Digital Technology Center and the Electrical and Computer Engineering Department University of Minnesota MinneapolisMN55455 United States State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Tongji University Shanghai200072 China

—In today’s cyber-enabled smart grids, high penetration of uncertain renewables, purposeful manipulation of meter readings, and the need for wide-area situational awareness, call for fast, accurate, and robust power system state estimation. The least-absolute-value (LAV) estimator is known for its robustness relative to the weighted least-squares (WLS) one. However, due to nonconvexity and nonsmoothness, existing LAV solvers based on linear programming are typically slow, hence inadequate for real-time system monitoring. This paper develops two novel algorithms for efficient LAV estimation, which draw from recent advances in composite optimization. The first is a deterministic linear proximal scheme that handles a sequence of (5 ∼ 10 in general) convex quadratic problems, each efficiently solvable either via off-the-shelf toolboxes or through the alternating direction method of multipliers. Leveraging the sparse connectivity inherent to power networks, the second scheme is stochastic, and updates only a few entries of the complex voltage state vector per iteration. In particular, when voltage magnitude and (re)active power flow measurements are used only, this number reduces to one or two, regardless of the number of buses in the network. This computational complexity evidently scales well to large-size power systems. Furthermore, by carefully mini-batching the voltage and power flow measurements, accelerated implementation of the stochastic iterations becomes possible. The developed algorithms are numerically evaluated using a variety of benchmark power networks. Simulated tests corroborate that improved robustness can be attained at comparable or markedly reduced computation times for medium- or large-size networks relative to existing alternatives. Copyright © 2017, The Authors. All rights reserved.

关键词： Electric power transmission networks

Predictive control for an asymmetric multilevel converter for PV energy injection

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Predictive control for an asymmetric multilevel converter fo...

International Conference on Environment and Electrical engineering (EEEIC)

作者： Javier Muñoz Fausto Cadena Patricio Gaisse Marco Rivera Eduardo Espinosa Raúl Gregor Department of Electrical Engineering Universidad de Talca Talca Chile Dept. of Environment and Energy Universidad Católica de la Santisima Concepción Concepcion Chile Lab. of Power and Control Systems Universidad Nacional de Asunción Luque CP Paraguay

ISBN: (纸本)9781538639184

Recent publications on multilevel converters show different topologies and control to obtain an improvement in the sinusoidal current waveform, controlling de DC voltage and the active/reactive power. This paper presents a 27-level asymmetric multilevel converter for photovoltaic injection using a predictive control algorithm that commands the three-phase converter to control the active power injected to the grid. The analyses include the detailed description of the converter valid states as well as the discrete time model of the equivalent circuit. The control strategy considers a master linear controller in charge to track the Maximum Power Point and a slave loop that includes a predictive controller, which is responsible of the current tracking. The proposal is validated through simulated results that illustrates the dynamic behavior of the converter under irradiance changes.

关键词： Mathematical model Prediction algorithms Integrated circuit modeling Topology Voltage control Predictive models Cost function

PSSE Redux: Convex relaxation, decentralized, robust, and dynamic approaches

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arXiv 2017年

作者： Kekatos, Vassilis Wang, Gang Zhu, Hao Giannakis, Georgios B. Bradley Department of Electrical and Computer Engineering Virginia Tech BlacksburgVA24061 United States Department of Electrical and Computer Engineering University of Minnesota MinneapolisMN55455 United States State Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China Department of Electrical and Computer Engineering University of Illinois UrbanaIL61801 United States

Deep transcranial magnetic stimulation using deformed halo-circular assembly coil 7

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Deep transcranial magnetic stimulation using deformed halo-c...

7th Asia-Pacific International Symposium on Electromagnetic Compatibility, APEMC 2016

作者： Lu, Mai Dong, Xu-Wei Ueno, Shoogo Key Lab. of Opt-Electronic Technology and Intelligent Control Lanzhou Jiaotong University Ministry of Education Lanzhou730070 China Department of Applied Quantum Physics Graduate School of Engineering Kyushu University Fukuoka812-8581 Japan

ISBN: (纸本)9781467394949

Direct stimulation of deeper brain tissues by transcranial magnetic stimulation (dTMS) plays an important role in the study of reward and motivation mechanisms, which may be beneficial in the treatment of several neurological and psychiatric disorders. This paper presents numerical simulation of dTMS by considering the deformed Halo-circular assembly coil (dHCA coil). Three-dimensional distributions of the induced magnetic field and electric field in realistic head model by applying the dHCA coil were obtained by impedance method, and the results were compared with the normal Halo-circular assembly coil (HCA coil). The improved stimulation focality with reasonable stimulation depth can be achieved by employing the dHCA coil. © 2016 IEEE.

关键词： Electric fields

Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

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Nature Ecology and Evolution 2025年 1-12页

作者： Pringle, Stephen Dallimer, Martin Goddard, Mark A. Le Goff, Léni K. Hart, Emma Langdale, Simon J. Fisher, Jessica C. Abad, Sara-Adela Ancrenaz, Marc Angeoletto, Fabio Auat Cheein, Fernando Austen, Gail E. Bailey, Joseph J. Baldock, Katherine C. R. Banin, Lindsay F. Banks-Leite, Cristina Barau, Aliyu S. Bashyal, Reshu Bates, Adam J. Bicknell, Jake E. Bielby, Jon Bosilj, Petra Bush, Emma R. Butler, Simon J. Carpenter, Dan Clements, Christopher F. Cully, Antoine Davies, Kendi F. Deere, Nicolas J. Dodd, Michael Drinkwater, Rosie Driscoll, Don A. Dutilleux, Guillaume Dyrmann, Mads Edwards, David P. Farhadinia, Mohammad S. Faruk, Aisyah Field, Richard Fletcher, Robert J. Foster, Chris W. Fox, Richard Francksen, Richard M. Franco, Aldina M. A. Gainsbury, Alison M. Gardner, Charlie J. Giorgi, Ioanna Griffiths, Richard A. Hamaza, Salua Hanheide, Marc Hayward, Matt W. Hedblom, Marcus Helgason, Thorunn Heon, Sui P. Hughes, Kevin A. Hunt, Edmund R. Ingram, Daniel J. Jackson-Mills, George Jowett, Kelly Keitt, Timothy H. Kloepper, Laura N. Kramer-Schadt, Stephanie lab.sko, Jim lab.osse, Frédéric Lawson, Jenna Lecomte, Nicolas de Lima, Ricardo F. Littlewood, Nick A. Marshall, Harry H. Masala, Giovanni L. Maskell, Lindsay C. Matechou, Eleni Mazzolai, Barbara McConnell, Alistair Melbourne, Brett A. Miriyev, Aslan Nana, Eric Djomo Ossola, Alessandro Papworth, Sarah Parr, Catherine L. Payo-Payo, Ana Perry, Gad Pettorelli, Nathalie Pillay, Rajeev Potts, Simon G. Prendergast-Miller, Miranda T. Qie, Lan Rolley-Parnell, Persie Rossiter, Stephen J. Rowcliffe, Marcus Rumble, Heather Sadler, Jon P. Sandom, Christopher J. Sanyal, Asiem Schrodt, Franziska Sethi, Sarab S. Shabrani, Adi Siddall, Robert Smith, Simón C. Snep, Robbert P. H. Soulsbury, Carl D. Stanley, Margaret C. Stephens, Philip A. Stephenson, P.J. Struebig, Matthew J. Studley, Matthew Svátek, Martin Tang, Gilbert Taylor, Nicholas K. Umbers, Kate D. L. Ward, Robert J. White, Patrick J. C. Whittingham, Mark J. Wich, Serge Williams, Christopher D. Yakubu, Ibrahim B. Yoh, Natalie Durrell Institute of Conservation and Ecology (DICE) School of Natural Sciences University of Kent Canterbury United Kingdom Centre for Environmental Policy Imperial College London London United Kingdom Department of Geography and Environmental Sciences Northumbria University Newcastle upon Tyne United Kingdom School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh United Kingdom Synthotech Ltd Milner Court Hornbeam Square Harrogate United Kingdom Mechanical Engineering Department University College London London United Kingdom HUTAN SWD Kota Kinabalu Malaysia Programa de Pós-Graduação em Gestão e Tecnologia Ambiental da Universidade Federal de Rondonópolis Rondonópolis Brazil Department of Engineering Harper Adams University Newport United Kingdom Applied Ecology Research Group School of Life Sciences Anglia Ruskin University Cambridge United Kingdom Centre for Ecology and Hydrology Penicuik United Kingdom Department of Life Sciences Imperial College London Silwood Park Campus Ascot United Kingdom Department of Urban and Regional Planning Faculty of Earth and Environmental Sciences Bayero University Kano Nigeria Greenhood Nepal Kathmandu Nepal Animal Rural & Environmental Sciences Nottingham Trent University Nottinghamshire United Kingdom School of Biological and Environmental Sciences Liverpool John Moores University Liverpool United Kingdom Lincoln Centre for Autonomous Systems University of Lincoln Lincoln United Kingdom Royal Botanic Garden Edinburgh Edinburgh United Kingdom School of Biological Sciences University of East Anglia Norwich Research Park Norwich United Kingdom Digital Ecology Limited Bristol United Kingdom School of Biological Sciences University of Bristol Bristol United Kingdom Department of Computing Imperial College London London United Kingdom Department of Ecology and Evolutionary Biology University of Colorado Boulder CO United States Faculty of Science Technology Engineering

With biodiversity loss escalating globally, a step change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that may substantially advance terrestrial biodiversity monitoring, but this potential is yet to be considered systematically. We used a modified Delphi technique to synthesize knowledge from 98 biodiversity experts and 31 RAS experts, who identified the major methodological barriers that currently hinder monitoring, and explored the opportunities and challenges that RAS offer in overcoming these barriers. Biodiversity experts identified four barrier categories: site access, species and individual identification, data handling and storage, and power and network availab.lity. Robotics experts highlighted technologies that could overcome these barriers and identified the developments needed to facilitate RAS-based autonomous biodiversity monitoring. Some existing RAS could be optimized relatively easily to survey species but would require development to be suitable for monitoring of more ‘difficult’ taxa and robust enough to work under uncontrolled conditions within ecosystems. Other nascent technologies (for instance, new sensors and biodegradable robots) need accelerated research. Overall, it was felt that RAS could lead to major progress in monitoring of terrestrial biodiversity by supplementing rather than supplanting existing methods. Transdisciplinarity needs to be fostered between biodiversity and RAS experts so that future ideas and technologies can be codeveloped effectively. © The Author(s) 2025.

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Decorrelation of neutral vector variables: Theory and applications

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arXiv 2017年

作者： Ma, Zhanyu Xue, Jing-Hao Leijon, Arne Tan, Zheng-Hua Yang, Zhen Guo, Jun Pattern Recognition and Intelligent System Lab. Beijing University of Posts and Telecommunications Beijing China Department of Statistical Science University College London London United Kingdom School of Electrical Engineering Kth - Royal Institute of Technology Stockholm Sweden Department of Electronic Systems Aalborg University Aalborg Denmark College of Computer Science Beijing University of Technology Beijing China

In this paper, we propose novel strategies for neutral vector variable decorrelation. Two fundamental invertible transformations, namely serial nonlinear transformation and parallel nonlinear transformation, are proposed to carry out the decorrelation. For a neutral vector variable, which is not multivariate Gaussian distributed, the conventional principal component analysis (PCA) cannot yield mutually independent scalar variables. With the two proposed transformations, a highly negatively correlated neutral vector can be transformed to a set of mutually independent scalar variables with the same degrees of freedom. We also evaluate the decorrelation performances for the vectors generated from a single Dirichlet distribution and a mixture of Dirichlet distributions. The mutual independence is verified with the distance correlation measurement. The advantages of the proposed decorrelation strategies are intensively studied and demonstrated with synthesized data and practical application evaluations. Copyright © 2017, The Authors. All rights reserved.

关键词： Vectors

Multiple threading strategy for intelligent surveillance system

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Multiple threading strategy for intelligent surveillance sys...

International Conference on control, Automation and systems ( ICCAS)

作者： Wahyono Kang-Hyun Jo Intelligent Systems Lab. University of Ulsan Ulsan Korea School of Electrical Engineering University of Ulsan Ulsan Korea

ISBN: (纸本)9781467390583

In recent years, an intelligent surveillance system is widely developed along with the rapid use of closed circuit television (CCTV) camera in the public area. The system should be able to process multiple source data from different CCTV networks simultaneously and automatically detect any suspicious event on the monitoring area. A low-cost computational time is required to make a fast-enough system in order to prevent any delay in decision-making of the security officer. In this paper, multiple threading based process is proposed to achieve this requirement. In implementation, a four-channels intelligent surveillance system (ISS) is developed. Comparing to existing commercial systems, the ISS provides six surveillance tasks in ensuring a public safety such as unattended object detection, fire and smoke detection, human detection and tracking, sterile zone monitoring, and illegally parked vehicle detection.

关键词： Surveillance Cameras Streaming media Instruction sets Security Detectors