Engineering Commons^™

Improving Autonomous Vehicles Operational Performance Using Resilience Engineering, Johan Fanas Rojas

Dissertations

Autonomous vehicles are expected to revolutionize the transportation industry by providing a safer and more efficient means of transportation. However, as autonomous vehicles are deployed on public roads, they are exposed to significant risks, both in terms of safety and system performance. Recent studies have highlighted a range of errors and accidents associated with autonomous vehicles, underscoring the need for a systematic approach to improve their operational resilience. Resilience engineering, a discipline focused on designing and analyzing complex systems to better cope with unexpected events and disruptions, offers a promising framework for addressing these challenges. Despite the potential benefits of …

Viability And Performance Of Rf Source Localization Using Autocorrelation-Based Fingerprinting, Joseph L. Ipson

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Finding the source location of a radio-frequency (RF) transmission is a useful capability for many civilian, industrial, and military applications. This problem is particularly challenging when done “Blind,” or when the transmitter was not designed with finding its location in mind, and relatively little information is available about the signal before-hand. Typical methods for this operation utilize the time, phase, power, and frequency viewable from received signals. These features are all less predictable in indoor and urban environments, where signals undergo transformation from multiple interactions with the environment. These interactions imprint structure onto the received signal which is dependent on …

Botsitter, Maria Hatzis, Gregory Blondheim Jr., Marian Bonto, Brett Jacobsen

Williams Honors College, Honors Research Projects

As society progresses into an era where both parents work, whether it is online or in person, children in the home may be put in dangerous situations if they are not given the attention they need. The BotSitter is an automated system that follows the child around and makes an audio alarm to alert both the child and the nearby guardian. Using RSSI trilateration, predetermined danger areas, and embedded controls, the BotSitter will be able to follow the child. The device can manage to keep track of the child for the guardian while being almost completely automated outside of setup.

Analysis Of Localization Algorithms For Wireless Sensor Networks Using Binary Data, Alexander Joseph Hart

Graduate Research Theses & Dissertations

The detection, localization, and tracking of environmental and physical conditions can be accomplished using wireless sensor networks (WSNs). Recent advancements in sensors, processors, and wireless communications have improved the quality and acquisition speed of data in WSNs. However, the data gathered by a WSN is inherently random due to component and environmental variations. Thus, statistical signal processing algorithms are needed to analyze the random data in a robust way. Though many algorithms for the analysis of random data are established and available, they are problem-specific and must be adapted to the application. This thesis provides an analysis of established localization …

Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries

Dissertations, Master's Theses and Master's Reports

Safe and robust operation of autonomous ground vehicles in all types of conditions and environment necessitates complex perception systems and unique, innovative solutions. This work addresses automotive lidar and maximizing the performance of a simultaneous localization and mapping stack. An exploratory experiment and an open benchmarking experiment are both presented. Additionally, a popular SLAM application is extended to use the type of information gained from lidar characterization, demonstrating the performance gains and necessity to tightly couple perception software and sensor hardware. The first exploratory experiment collects data from child-sized, low-reflectance targets over a range from 15 m to 35 m. …

Localization Of People In Gnss-Denied Environments Using Neural-Inertial Prediction And Kalman Filter Correction, Lauren N. Cash

Graduate Theses, Dissertations, and Problem Reports

This thesis presents a method based on neural networks and Kalman filters for estimating the position of a person carrying a mobile device (i.e., cell phone or tablet) that can communicate with static UWB sensors or is carried in an environment with known landmark positions. This device is used to collect and share inertial measurement unit (IMU) information — which includes data from sensors such as accelerometers, gyroscopes, and magnetometers — and UWB and landmark information. The collected data, in combination with other necessary initial condition information, is input into a pre-trained deep neural network (DNN) which predicts the movement …

Exploiting The Advantages And Overcoming The Challenges Of The Cable In A Tethered Drone System, Rogerio Rodrigues Lima

Graduate Theses, Dissertations, and Problem Reports

This dissertation proposes solutions for motion planning, localization, and landing of tethered drones using only tether variables. A tether-based multi-model localization framework for tethered drones is proposed. This framework comprises three independent localization strategies based on a different model. The first strategy uses simple trigonometric relations assuming that the tether is taut; the second method relies on a set of catenary equations for the slack tether case; the third estimator is a neural network-based predictor that can cover different tether shapes. Multi-layer perceptron networks previously trained with a dataset comprised of the tether variables (i.e., length, tether angles on the …

Robust State Estimation Methods For Robotics Applications, Shounak Das

Graduate Theses, Dissertations, and Problem Reports

State estimation is an integral component of any autonomous robotic system. Finding the correct position, velocity, and orientation of an agent in its environment enables it to do other tasks like mapping and interacting with the environment, and collaborating with other agents. State estimation is achieved by using data obtained from multiple sensors and fusing them in a probabilistic framework. These include inertial data from Inertial Measurement Unit (IMU), images from camera, range data from lidars, and positioning data from Global Navigation Satellite Systems (GNSS) receivers. The main challenge faced in sensor-based state estimation is the presence of noisy, erroneous, …

Deep Learning Based Localization Of Zigbee Interference Sources Using Channel State Information, Dylan Kensler

All Theses

As the field of Internet of Things (IoT) continues to grow, a variety of wireless signals fill the ambient wireless environment. These signals are used for communication, however, recently wireless sensing has been studied, in which these signals can be used to gather information about the surrounding space. With the development of 802.11n, a newer standard of WiFi, more complex information is available about the environment a signal propagates through. This information called Channel State Information (CSI) can be used in wireless sensing. With the help of Deep Learning, this work attempts to generate a fingerprinting technique for localizing a …

The Network Link Outlier Factor (Nlof) For Localizing Network Faults, Christopher Mendoza

Open Access Theses & Dissertations

This work presents the Network Link Outlier Factor (NLOF), a data analytics pipeline for network fault detection and localization solution that consists of four stages. In the first stage, flow record throughput values are clustered in two sub-stages: using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and then a novel domain-specific ThroughPut Cluster (TPCluster) technique. In the second stage, Flow Outlier Factor (FOF) scores are computed for each flow. In the third stage, flows are traced onto the network. Finally, in the fourth stage, each link is given a Network Link Outlier Factor (NLOF) score which is the ratio …

Underwater Source Localization Based On Modal Propagation And Acoustic Signal Processing, Luca Saeid

Electronic Theses and Dissertations

Acoustic localization plays a pivotal role in underwater vehicle systems and marine mammal detection. Previous efforts adopt synchronized arrays of sensors to extract some features like direction of arrival (DOA) or time of flight (TOF) from the received signal. However, installing and synchronizing several hydrophones over a large area is costly and challenging. To tackle this problem, we use a single-hydrophone localization system which relies on acoustic signal processing methods rather than multiple hydrophones. This system takes modal dispersion into consideration and estimates the distance between sound source and receiver (range) based on dispersion curves. It is shown that the …

Localization Of Stationary Source Of Floor Vibration Using The Steered Response Power Method, Mohammad Royvaran

Theses and Dissertations--Civil Engineering

If the generated vibration in a building exceeds the acceptable limit design for a floor system, it is necessary to identify the source of vibration, a process known as localization. The objective of this study is the localization of stationary vibration sources, and the approach used is the steered response power (SRP) method. This method has already been shown to work well for wireless and acoustical applications to locate transmitter and sound sources, respectively. To the writer’s knowledge, this study is the first application of the SRP method to locate vibration sources using floor vibration measurements. However, because waves behave …

Planning Algorithms Under Uncertainty For A Team Of A Uav And A Ugv For Underground Exploration, Matteo De Petrillo

Graduate Theses, Dissertations, and Problem Reports

Robots’ autonomy has been studied for decades in different environments, but only recently, thanks to the advance in technology and interests, robots for underground exploration gained more attention. Due to the many challenges that any robot must face in such harsh environments, this remains an challenging and complex problem to solve.

As technology became cheaper and more accessible, the use of robots for underground ex- ploration increased. One of the main challenges is concerned with robot localization, which is not easily provided by any Global Navigation Services System (GNSS). Many developments have been achieved for indoor mobile ground robots, making …

Localization Algorithms For Gnss-Denied And Challenging Environments, Chizhao Yang

Graduate Theses, Dissertations, and Problem Reports

In this dissertation, the problem about localization in GNSS-denied and challenging environments is addressed. Specifically, the challenging environments discussed in this dissertation include two different types, environments including only low-resolution features and environments containing moving objects. To achieve accurate pose estimates, the errors are always bounded through matching observations from sensors with surrounding environments. These challenging environments, unfortunately, would bring troubles into matching related methods, such as "fingerprint" matching, and ICP. For instance, in environments with low-resolution features, the on-board sensor measurements could match to multiple positions on a map, which creates ambiguity; in environments with moving objects included, the …

Planetary Rover Inertial Navigation Applications: Pseudo Measurements And Wheel Terrain Interactions, Cagri Kilic

Graduate Theses, Dissertations, and Problem Reports

Accurate localization is a critical component of any robotic system. During planetary missions, these systems are often limited by energy sources and slow spacecraft computers. Using proprioceptive localization (e.g., using an inertial measurement unit and wheel encoders) without external aiding is insufficient for accurate localization. This is mainly due to the integrated and unbounded errors of the inertial navigation solutions and the drifted position information from wheel encoders caused by wheel slippage. For this reason, planetary rovers often utilize exteroceptive (e.g., vision-based) sensors. On the one hand, localization with proprioceptive sensors is straightforward, computationally efficient, and continuous. On the other …

Uncertainty Estimation For Stereo Visual Odometry, Derek W. Ross

Graduate Theses, Dissertations, and Problem Reports

Over the past few decades, unmanned aerial vehicles (UAVs) have been increasingly popular for use in locations that are lacking, or have unreliable global navigation satellite system (GNSS) availability. One of the more popular localization techniques for quadrotors is the use of visual odometry (VO) through monocular, RGB-D, or stereo cameras. With primary applications in the context of Simultaneous Localization And Mapping (SLAM) and indoor navigation, VO is largely used in combination with other sensors through Bayesian filters, namely Extended Kalman Filter (EKF) or Particle Filter. This work investigates the accuracy of two standard covariance estimation techniques for a feature-based …

Uav 6dof Simulation And Kalman Filter For Localizing Radioactive Sources, John G. Goulet

Electronic Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) expand the available mission-space for a wide range of budgets. Using MATLAB, this project has developed a six degree of freedom (6DOF) simulation of UAV flight, an Extended Kalman Filter (EKF), and an algorithm for localizing radioactive sources using low-cost hardware. The EKF uses simulated low-cost instruments in an effort to estimate the UAV state throughout simulated flight.

The 6DOF simulates aerodynamics, physics, and controls throughout the flight and provides outputs for each time step. Additionally, the 6DOF simulation offers the ability to control UAV flight via preset waypoints or in realtime via keyboard input.

Using …

Comparison Of Visual Simultaneous Localization And Mapping Methods For Fixed-Wing Aircraft Using Slambench2, Patrick R. Latcham

Theses and Dissertations

Visual Simultaneous Localization and Mapping (VSLAM) algorithms have evolved rapidly in the last few years, however there has been little research evaluating current algorithm's effectiveness and limitations when applied to tracking the position of a fixed-wing aerial vehicle. This research looks to evaluate current monocular VSLAM algorithms' performance on aerial vehicle datasets using the SLAMBench2 benchmarking suite. The algorithms tested are MonoSLAM, PTAM, OKVIS, LSDSLAM, ORB-SLAM2, and SVO, all of which are built into the SLAMBench2 software. The algorithms' performance is evaluated using simulated datasets generated in the AftrBurner Engine. The datasets were designed to test the quality of each …

Pedestrian Navigation Using Artificial Neural Networks And Classical Filtering Techniques, David J. Ellis

Theses and Dissertations

The objective of this thesis is to explore the improvements achieved through using classical filtering methods with Artificial Neural Network (ANN) for pedestrian navigation techniques. ANN have been improving dramatically in their ability to approximate various functions. These neural network solutions have been able to surpass many classical navigation techniques. However, research using ANN to solve problems appears to be solely focused on the ability of neural networks alone. The combination of ANN with classical filtering methods has the potential to bring beneficial aspects of both techniques to increase accuracy in many different applications. Pedestrian navigation is used as a …

V-Slam And Sensor Fusion For Ground Robots, Ejup Hoxha

Dissertations and Theses

In underground, underwater and indoor environments, a robot has to rely solely on its on-board sensors to sense and understand its surroundings. This is the main reason why SLAM gained the popularity it has today. In recent years, we have seen excellent improvement on accuracy of localization using cameras and combinations of different sensors, especially camera-IMU (VIO) fusion. Incorporating more sensors leads to improvement of accuracy,but also robustness of SLAM. However, while testing SLAM in our ground robots, we have seen a decrease in performance quality when using the same algorithms on flying vehicles.We have an additional sensor for ground …

Indoor Navigation For Visually Impaired Person Using Inertial And Geomagnetic Information, Jayanth Ammanabrolu

All Graduate Theses, Dissertations, and Other Capstone Projects

Motivated by the need for assistance of indoor guidance for visually impaired persons (VIPs), a sensing system using inertial and geo-magnetic information has been developed to navigate a VIP person indoor. Orientation estimation, which is critical for indoor localization, is conducted using the information of the angular velocity, acceleration and geomagnetic field. By analyzing the characters of human gait, a method to eliminate the accumulated drift introduced by double integrations is introduced. By attaching the inertial sensor to the foot, the periodic stationary state will facilitate the drift correction. Also, the distinctive distortion of the geomagnetic field, which contains spatial …

Convolutional Neural Network Architecture Study For Aerial Visual Localization, Jedediah M. Berhold

Theses and Dissertations

In unmanned aerial navigation the ability to determine the aircraft's location is essential for safe flight. The Global Positioning System (GPS) is the default modern application used for geospatial location determination. GPS is extremely robust, very accurate, and has essentially solved aerial localization. Unfortunately, the signals from all Global Navigation Satellite Systems (GNSS) to include GPS can be jammed or spoofed. To this response it is essential to develop alternative systems that could be used to supplement navigation systems, in the event of a lost GNSS signal. Public and governmental satellites have provided large amounts of high-resolution satellite imagery. These …

Indoor-Wireless Location Techniques And Algorithms Utilizing Uhf Rfid And Ble Technologies, Ann M. Whitney

Theses and Dissertations--Mechanical Engineering

The work presented herein explores the ability of Ultra High Frequency Radio Frequency (UHF RF) devices, specifically (Radio Frequency Identification) RFID passive tags and Bluetooth Low Energy (BLE) to be used as tools to locate items of interest inside a building. Localization Systems based on these technologies are commercially available, but have failed to be widely adopted due to significant drawbacks in the accuracy and reliability of state of the art systems. It is the goal of this work to address that issue by identifying and potentially improving upon localization algorithms.

The work presented here breaks the process of localization …

Acoustic Localization Techniques For Application In Near-Shore Arctic Environments, Miles B. Penhale

Dissertations, Master's Theses and Master's Reports

The Arctic environment has undergone significant change in recent years. Multi-year ice is no longer prevalent in the Arctic. Instead, Arctic ice melts during summer months and re-freezes each winter. First-year ice, in comparison to multi-year ice, is different in terms of its acoustic properties. Therefore, acoustic propagation models of the Arctic may no longer be valid. The open water in the Arctic for longer time periods during the year invites anthropogenic traffic such as civilian tourism, industrial shipping, natural resource exploration, and military exercises. It is important to understand sound propagation in the first-year ice environment, especially in near-shore …

Community Detection In Complex Networks And Application To Dense Wireless Sensor Networks Localization, Sakineh Yazdanparast

Dissertations, Master's Theses and Master's Reports

Complex network analysis is applied in numerous researches. Features and characteristics of complex networks provide information associated with a network feature called community structure. Naturally, nodes with similar attributes will be more likely to form a community. Community detection is described as the process by which complex network data are analyzed to uncover organizational properties, and structure; and ultimately to enable extraction of useful information. Analysis of Wireless Sensor Networks (WSN) is considered as one of the most important categories of network analysis due to their enormous and emerging applications. Most WSN applications are location-aware, which entails precise localization of …

Effect Of Sensor Errors On Autonomous Steering Control And Application Of Sensor Fusion For Robust Navigation, Shuvodeep Bhattacharjya

Dissertations, Master's Theses and Master's Reports

Autonomous steering control is one the most important features in autonomous vehicle navigation. The nature and tuning of the controller decides how well the vehicle follows a defined trajectory. A poorly tuned controller can cause the vehicle to oversteer or understeer at turns leading to deviation from a defined path. However, controller performance also depends on the state–feedback system. If the states used for controller input are noisy or has bias / systematic error, the navigation performance of the vehicle is affected irrespective of the control law and controller tuning. In this report, autonomous steering controller analysis is done for …

Gps Denied Localization Using Ultra-Wideband Radios, Joshua P. Vanfleet

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

GPS denied environments cause each unmanned ground vehicle (UGV) in an autonomous convoy to lose positional accuracy which can lead to inoperability, or even damage. In order for autonomous convoy systems to fill the needs of any particular field, a well-performing system must be designed such that a convoy can operate in any environment. Ultra-wideband (UWB) radios are a proposed solution to GPS denied localization. The main objective of this research is to use UWB radios to localize a leader vehicle within a convoy situation while in a GPS denied environment.

A Comparative Study Of Feature Detection Methods For Auv Localization, Andrew Y. Kim

Master's Theses

Underwater localization is a difficult task when it comes to making the system autonomous due to the unpredictable environment. The fact that radio signals such as GPS cannot be transmitted through water makes autonomous movement and localization underwater even more challenging. One specific method that is widely used for autonomous underwater navigation applications is Simultaneous Localization and Mapping (SLAM), a technique in which a map is created and updated while localizing the vehicle within the map. In SLAM, feature detection is used in landmark extraction and data association by examining each pixel and differentiating landmarks pixels from those of the …

Design, Analysis And Optimization Of Visible Light Communications Based Indoor Access Systems For Mobile And Internet Of Things Applications, Sihua Shao

Dissertations

Demands for indoor broadband wireless access services are expected to outstrip the spectrum capacity in the near-term "spectrum crunch". Deploying additional femtocells to address "spectrum crunch" is cost-inefficient due to the "backhaul challenge" and the exorbitant system maintenance. According to an Alcatel-Lucent report, most mobile Internet access traffic happens indoors. To alleviate the "spectrum crunch" and the "backhaul challenge" problems, visible light communication (VLC) emerges as an attractive candidate for indoor wireless access in the 5G architecture. In particular, VLC utilizes LED or fluorescent lamps to send out imperceptible flickering light that can be captured by a smart phone camera …

Rss-Based Device-Free Passive Detection And Localization Using Home Automation Network Radio Frequencies, Tiffany M. Phan

Theses and Dissertations

This research provided a proof of concept for a device-free passive (DfP) system capable of detecting and localizing a target through exploitation of a home automation network’s radio frequency (RF) signals. The system was developed using Insteon devices with a 915 MHz center frequency. Without developer privileges, limitations of the Insteon technology like no intrinsic received signal strength (RSS) field and silent periods between messages were overcome by using software-defined radios to simulate Insteon devices capable of collecting and reporting RSS, and by creating a message generation script and implementing a calibrated filter threshold to reduce silent periods. Evaluation of …