Estimating general motion and intensity from event cameras

Robotic vision algorithms have become widely used in many consumer products which enabled technologies such as autonomous vehicles, drones, augmented reality (AR) and virtual reality (VR) devices to name a few. These applications require vision algorithms to work in real-world environments with extreme lighting variations and fast moving objects. However, robotic vision applications rely often on standard video cameras which face severe limitations in fast-moving scenes or by bright light sources which diminish the image quality with artefacts like motion blur or over-saturation. To address these limitations, the body of work presented here investigates the use of alternative sensor devices which mimic the superior perception properties of human vision. Such silicon retinas were proposed by neuromorphic engineering, and we focus here on one such biologically inspired sensor called the event camera which offers a new camera paradigm for real-time robotic vision. The camera provides a high measurement rate, low latency, high dynamic range, and low data rate. The signal of the camera is composed of a stream of asynchronous events at microsecond resolution. Each event indicates when individual pixels registers a logarithmic intensity changes of a pre-set threshold size. Using this novel signal has proven to be very challenging in most computer vision problems since common vision methods require synchronous absolute intensity information. In this thesis, we present for the first time a method to reconstruct an image and es- timation motion from an event stream without additional sensing or prior knowledge of the scene. This method is based on coupled estimations of both motion and intensity which enables our event-based analysis, which was previously only possible with severe limitations. We also present the first machine learning algorithm for event-based unsu- pervised intensity reconstruction which does not depend on an explicit motion estimation and reveals finer image details. This learning approach does not rely on event-to-image examples, but learns from standard camera image examples which are not coupled to the event data. In experiments we show that the learned reconstruction improves upon our handcrafted approach. Finally, we combine our learned approach with motion estima- tion methods and show the improved intensity reconstruction also significantly improves the motion estimation results. We hope our work in this thesis bridges the gap between the event signal and images and that it opens event cameras to practical solutions to overcome the current limitations of frame-based cameras in robotic vision.Open Acces

Resilience-oriented control and communication framework for cyber-physical microgrids

Climate change drives the energy supply transition from traditional fossil fuel-based power generation to renewable energy resources. This transition has been widely recognised as one of the most significant developing pathways promoting the decarbonisation process toward a zero-carbon and sustainable society. Rapidly developing renewables gradually dominate energy systems and promote the current energy supply system towards decentralisation and digitisation. The manifestation of decentralisation is at massive dispatchable energy resources, while the digitisation features strong cohesion and coherence between electrical power technologies and information and communication technologies (ICT). Massive dispatchable physical devices and cyber components are interdependent and coupled tightly as a cyber-physical energy supply system, while this cyber-physical energy supply system currently faces an increase of extreme weather (e.g., earthquake, flooding) and cyber-contingencies (e.g., cyberattacks) in the frequency, intensity, and duration. Hence, one major challenge is to find an appropriate cyber-physical solution to accommodate increasing renewables while enhancing power supply resilience. The main focus of this thesis is to blend centralised and decentralised frameworks to propose a collaboratively centralised-and-decentralised resilient control framework for energy systems i.e., networked microgrids (MGs) that can operate optimally in the normal condition while can mitigate simultaneous cyber-physical contingencies in the extreme condition. To achieve this, we investigate the concept of "cyber-physical resilience" including four phases, namely prevention/upgrade, resistance, adaption/mitigation, and recovery. Throughout these stages, we tackle different cyber-physical challenges under the concept of microgrid ranging from a centralised-to-decentralised transitional control framework coping with cyber-physical out of service, a cyber-resilient distributed control methodology for networked MGs, a UAV assisted post-contingency cyber-physical service restoration, to a fast-convergent distributed dynamic state estimation algorithm for a class of interconnected systems.Open Acces

Enhancing low mass dark matter mediator resonance searches with improved triggering in the ATLAS detector

Dark matter comprises a significant component of our universe, but its particle nature has evaded particle detectors thus far. Dark matter may be produced in proton collisions at the Large Hadron Collider through the production of a mediator that couples the Standard Model to the dark sector. With no hint of new particles in the most accessible mass range, new search strategies aim to access the challenging phase space that lies at low masses, where current trigger bandwidth limitations have strongly constrained the sensitivity owing to the many low energy interactions that occur within proton collisions. One particular search strategy is the Trigger-object Level Analysis, which circumvents bandwidth limitations by recording only objects reconstructed from partial event information at trigger-level and is therefore intimately linked to the capabilities of the trigger system. The body of work herein encompasses various improvements of the triggering capabilities of the ATLAS detector in order to retain and enhance the sensitivity to new physics. A new bunch-crossing identification algorithm is commissioned for highly saturated pulses, extending the triggerable energy range of the first-level trigger to the new high energies of the LHC Run 2. The algorithm is successfully commissioned and permanently activated for Run 2 data taking. The capability of the high-level jet trigger is expanded in order to utilise trigger-level track reconstruction from the input of a new trigger upgrade. It is demonstrated how this will improve the sensitivity to low mass dark matter resonances in the Trigger-object Level Analysis in future data taking runs of the LHC

Measurement of the W → ev cross section with early data from the CMS experiment at CERN

The Compact Muon Solenoid (CMS) is a general purpose detector designed to study proton-proton collisions, and heavy ion collisions, delivered by the Large Hadron Collider (LHC) at the European Laboratory for High Energy Physics (CERN). This thesis describes a measurement of the inclusive W → ev cross section at 7 TeV centre of mass energy with 2:88 ± 0:32 pb-1 of LHC collision data recorded by CMS between March and September 2010. W boson decays are identified by the presence of a high-pT electron that satisfies selection criteria in order to reject electron candidates due to background processes. Electron selection variables are studied with collision data and found to be in agreement with expectations from simulation. A fast iterative technique is developed to tune electron selections based on these variables. Electron efficiency is determined from simulation and it is corrected from data using an electron sample from Z decays. The number of W candidates is corrected for remaining background events using a fit to the missing transverse energy distribution. The measured value for the inclusive W production cross section times the branching ratio of the W decay in the electron channel is: σ(pp → W+X)xBR(W → ev) = 10.04±0.10(stat)±0.52(syst)±1.10(luminosity) nb; which is in excellent agreement with theoretical expectations

The CMS experiment at the CERN LHC

The Compact Muon Solenoid (CMS) detector is described. The detector operates at the Large Hadron Collider (LHC) at CERN. It was conceived to study proton-proton (and leadlead) collisions at a centre-of-mass energy of 14 TeV (5.5 TeV nucleon-nucleon) and at luminosities up to 1034 cm-2s-1 (1027 cm-2s-1). At the core of the CMS detector sits a high-magnetic field and large-bore superconducting solenoid surrounding an all-silicon pixel and strip tracker, a lead-tungstate scintillating-crystals electromagnetic calorimeter, and a brass-scintillator sampling hadron calorimeter. The iron yoke of the flux-return is instrumented with four stations of muon detectors covering most of the 4π solid angle. Forward sampling calorimeters extend the pseudorapidity coverage to high values (|η| ≤ 5) assuring very good hermeticity. The overall dimensions of the CMS detector are a length of 21.6 m, a diameter of 14.6 m and a total weight of 12500 t

Motional sideband spectra and Coulomb crystals in a Penning trap

Laser cooled ions in a Penning trap can be isolated from the environment by placing them in vacuum and only interacting with them through optical and RF fields. The number of trapped particles can be varied from a single ion up to thousands. Confinement is provided by a static homogeneous magnetic field and a quadrupole electric potential. In the natural frame of the ions, this appears as a 3D simple harmonic potential. Therefore three dimensional structures can be formed in the absence of any additional RF field which may lead to heating as is the case with RF traps. There are 3N different motional modes for N particles. I present an analysis of the motion of a single particle showing that the energy levels for all three modes are equally spaced. I also describe the interaction between a trapped two level atom and an optical field. During my time in the lab the laser and computer control of the experiment has been significantly improved. In addition, an existing trap was modified to provide greater optical access and fluorescence collection. This allowed the vibrational levels superimposed on the internal states of a single 40Ca+ ion to be resolved via a narrow linewidth, electric quadrupole transition. This is the first observation of magnetron and modified cyclotron sidebands on an optical transition. When more than one calcium ion is laser cooled, and their temperature reduced below 5mK, they form a Coulomb crystal. The locations of the ions minimise the total potential energy which is comprised of the Coulomb repulsion and trap potential. The fluorescence collection optics have been arranged to resolve individual ions in these crystals. Information about the motion of the ions is deduced by comparing photos from the experiment to numerical simulations. Previously, only two ions have ever been aligned along the magnetic field in a Penning trap. I present strings of up to 29 particles and suggest the only limitation, apart from the electrode structure, is the overlap of the laser beams with the ions