Engineering Commons^™

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 …

Incorporating Histograms Of Oriented Gradients Into Monte Carlo Localization, Michael K. Norris

Master's Theses

This work presents improvements to Monte Carlo Localization (MCL) for a mobile robot using computer vision. Solutions to the localization problem aim to provide fine resolution on location approximation, and also be resistant to changes in the environment. One such environment change is the kidnapped/teleported robot problem, where a robot is suddenly transported to a new location and must re-localize. The standard method of "Augmented MCL" uses particle filtering combined with addition of random particles under certain conditions to solve the kidnapped robot problem. This solution is robust, but not always fast. This work combines Histogram of Oriented Gradients (HOG) …

Mapping And Visualizing Ancient Water Storage Systems With An Rov – An Approach Based On Fusing Stationary Scans Within A Particle Filter, William D. Mcvicker

Master's Theses

This paper presents a new method for constructing 2D maps of enclosed un- derwater structures using an underwater robot equipped with only a 2D scanning sonar, compass and depth sensor. In particular, no motion model or odometry is used. To accomplish this, a two step offline SLAM method is applied to a set of stationary sonar scans. In the first step, the change in position of the robot between each consecutive pair of stationary sonar scans is estimated using a particle filter. This set of pair wise relative scan positions is used to create an estimate of each scan’s position …

State Estimation For Tracking Of Tagged Sharks With An Auv, Christina Forney

Master's Theses

Presented is a method for estimating the planar position, velocity, and orientation states of a tagged shark. The method is designed for implementation on an Autonomous Underwater Vehicle (AUV) equipped with a stereo-hydrophone and receiver system that detects acoustic signals transmitted by a tag. The particular hydrophone system used here provides a measurement of relative bearing angle to the tag, but does not provide the sign (+ or -) of the bearing angle. A particle filter was used for fusing measurements over time to produce a state estimate of the tag location. The particle filter combined with an active control …

Underwater Localization And Tracking Of Physical Systems, Patrick E. Carroll

Master's Theses

In this paper, we investigate the problem of localizing an underwater sensor node basedon message broadcasting from multiple surface nodes. With the time-of-arrival measurementsfrom a DSP-based multicarrier modem, each sensor node localizes itself based on the traveltime differences among multiple senders to the receiver. Using one-way message passing, such asolution can scale to accommodate a large number of nodes in a network. We consider the issuefrom not only the physical layer, but also at the node processing layer by incorporating a trackingsolution. We present simulation results as well as preliminary testing results in a swimming poolwith both stationary and moving …

Monocular Vision And Image Correlation To Accomplish Autonomous Localization, Matthew Paul Schlachtman

Master's Theses

For autonomous navigation, robots and vehicles must have accurate estimates of their current state (i.e. location and orientation) within an inertial coordinate frame. If a map is given a priori, the process of determining this state is known as localization. When operating in the outdoors, localization is often assumed to be a solved problem when GPS measurements are available. However, in urban canyons and other areas where GPS accuracy is decreased, additional techniques with other sensors and filtering are required.

This thesis aims to provide one such technique based on monocular vision. First, the system requires a map be generated, …