Estimating wind fields using drones in a network: Estimating hyperlocal wind fields with on-board sensors on quadcopters

Charting hyperlocal wind using a drone is a challenge of increased attention as it unlocks potential in a variety of fields. In context of the METeo Sensors In the Sky project, this study proposes a method to estimate the magnitude and direction of wind using a quadcopter in hover and cruise without a dedicated wind sensor. Only on-board sensors...

Performance Analysis of Monte Carlo Localization Algorithm

One of the key problems of swarm robotics is how the mobile robots can navigate accurately in a given environment. To achieve this, the mobile robots need to accurately determine where they are globally, or relative to other robots and landmarks. This paper is going to be an investigation of the Monte Carlo Localization algorithm in an...

Analysis of object tracking algorithms performance on event-based datasets

The event-based camera represents a revolutionary concept, having an asynchronous output. The pixels of dynamic vision sensors react to the brightness change, resulting in streams of events at very small intervals of time. This paper provides a model to track objects in neuromorphic datasets, using clustering. In addition, a non-linear filter is...

Adaptive particle-aided cubature Kalman filtering for GNSS/INS-based vehicle localization

Accurate vehicle localization is considered to be a key element in future automated driving systems. A network of multiple sensors is employed to deliver information for this localization process. Loosely coupled integration of global navigation satellite systems (GNSS) and inertial navigation systems (INS) data is a common sensor-fusion method...

Indoor Localization through Pedestrian Dead Reckoning and Activity Recognition: A smartphone-based proof of concept

Pedestrian indoor localization is a problem yet to have a solution that is as generally accepted as the Global Positioning System is for outdoor localization. An infrastructure-independent option is to leverage the data from Inertial Measurement Unit (IMU) sensors to determine position. An advantage of this approach is that these sensors are...

Bayesian estimation in a bidimensional Ornstein-Uhlenbeck process

The goal of this thesis is to estimate parameters in a bidimensional Ornstein-Uhlenbeck process, namely a diffusion model which can be found in Favetto and Samson (2010), which considers plasma and interstitium concentrations. We first look at a general linear stochastic differential equation and some properties. Then we simulate possible paths...

Particle Filter based Speaker Tracking in Distributed Pairwise Microphone Networks

The particle filter (PF) algorithm is appropriate to solve the problem of speaker tracking in a reverberant and noisy environment using distributed pairwise microphone networks. First, complete the tracking task based on PF algorithm in centralized manner, a processing center is required to collect the signal from all microphones to carry out...

Human presence detection using a particle filter on ultrasonic micro-Doppler measurements for assisting rescue work in large buildings

When the re brigade arrives at a burning building, it is of vital importance that people who are still inside can quickly be found. In this thesis we contribute to an ultrasonic sound sensor for human presence detection in smoke-lled spaces. This type of sensor could assist the re brigade when evacuating a large building by directing them to the...

Energy disaggregation: Nonintrusive load monitoring: The search for practical methods

In this MSc. thesis steady-state disaggregation methods for the Non-Intrusive Load Monitoring are researched. The main target is to find methods that have the potential to be practically applicable. These methods are characterized by the fact that they use data that is collected by smart meters, since smart meters are more and more the standard...

Stochastic Nodal Analysis: EnKF and PF applied to petroleum production systems

A petroleum production system is generally modelled based on the concept of nodal analysis, where the entire system is broken down into discrete elements such as near-well bore, tubing, surface choke and flow line. Operating flow rates and pressures can be estimated with a nodal analysis procedure by calculation of the intersection of...

Swarm robot localization from noisy distance measurements

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SLAMming with Spheros: An impact-based approach to Simultaneous Localization and Mapping

The Simultaneous Localization and Mapping (SLAM) problem for mobile robots aims at consistently building a map of an unknown environment while simultaneously determining its position within this map. From a control-theoretic viewpoint, it is somehow analogous to simultaneously estimating the states and output map of the system. In the robotics...

Model-based Classification of Human Motion: Using a Particle Filter Approach

Automatic detection of humans is an important part of many security and surveillance applications. Automatic processing diminishes the effect of human errors on the detection and allows extensive analysis after detection. Radar has certain advantages for human detection because of its all-weather and day and night capability, as well the fact it...

Adapting Particle Filter Algorithms to the GPU Architecture

The particle filter is a Bayesian estimation technique based on Monte Carlo simulations. The non-parametric nature of particle filters makes them ideal for non-linear non-Gaussian systems. This greater filtering accuracy, however, comes at the price of increased computational complexity which limits their practical use for real-time applications...