Robotics Commons^™

Artificial Neural Network-Based Robotic Control, Justin Ng

Master's Theses

Artificial neural networks (ANNs) are highly-capable alternatives to traditional problem solving schemes due to their ability to solve non-linear systems with a nonalgorithmic approach. The applications of ANNs range from process control to pattern recognition and, with increasing importance, robotics. This paper demonstrates continuous control of a robot using the deep deterministic policy gradients (DDPG) algorithm, an actor-critic reinforcement learning strategy, originally conceived by Google DeepMind. After training, the robot performs controlled locomotion within an enclosed area. The paper also details the robot design process and explores the challenges of implementation in a real-time system.

Corridor Navigation For Monocular Vision Mobile Robots, Matthew James Ng

Master's Theses

Monocular vision robots use a single camera to process information about its environment. By analyzing this scene, the robot can determine the best navigation direction. Many modern approaches to robot hallway navigation involve using a plethora of sensors to detect certain features in the environment. This can be laser range finders, inertial measurement units, motor encoders, and cameras.

By combining all these sensors, there is unused data which could be useful for navigation. To draw back and develop a baseline approach, this thesis explores the reliability and capability of solely using a camera for navigation. The basic navigation structure begins …

Automated Pruning Of Greenhouse Indeterminate Tomato Plants, Joey M. Angeja

Master's Theses

Pruning of indeterminate tomato plants is vital for a profitable yield and it still remains a manual process. There has been research in automated pruning of grapevines, trees, and other plants, but tomato plants have yet to be explored. Wage increases are contributing to the depleting profits of greenhouse tomato farmers. Rises in population are the driving force behind the need for efficient growing techniques. The major contribution of this thesis is a computer vision algorithm for detecting greenhouse tomato pruning points without the use of depth sensors. Given an up-close 2-D image of a tomato stem with the background …

Models For Pedestrian Trajectory Prediction And Navigation In Dynamic Environments, Jeremy N. Kerfs

Master's Theses

Robots are no longer constrained to cages in factories and are increasingly taking on roles alongside humans. Before robots can accomplish their tasks in these dynamic environments, they must be able to navigate while avoiding collisions with pedestrians or other robots. Humans are able to move through crowds by anticipating the movements of other pedestrians and how their actions will influence others; developing a method for predicting pedestrian trajectories is a critical component of a robust robot navigation system. A current state-of-the-art approach for predicting pedestrian trajectories is Social-LSTM, which is a recurrent neural network that incorporates information about neighboring …

A Lidar Based Semi-Autonomous Collision Avoidance System And The Development Of A Hardware-In-The-Loop Simulator To Aid In Algorithm Development And Human Studies, Thomas F. Stevens

Master's Theses

In this paper, the architecture and implementation of an embedded controller for a steering based semi-autonomous collision avoidance system on a 1/10^th scale model is presented. In addition, the development of a 2D hardware-in-the-loop simulator with vehicle dynamics based on the bicycle model is described. The semi-autonomous collision avoidance software is fully contained onboard a single-board computer running embedded GNU/Linux. To eliminate any wired tethers that limit the system’s abilities, the driver operates the vehicle at a user-control-station through a wireless Bluetooth interface. The user-control-station is outfitted with a game-controller that provides standard steering wheel and pedal controls along …

Telepresence: Design, Implementation And Study Of An Hmd-Controlled Avatar With A Mechatronic Approach, Darren Michael Chan

Master's Theses

Telepresence describes technologies that allow users to remotely experience the sensation of being present at an event without being physically present. An avatar exists to represent the user whilst in a remote location and is tasked to collect stimuli from its immediate surroundings to be delivered to the user for consumption. With the advent of recent developments in Virtual Reality technology, viz., head-mounted displays (HMDs), new possibilities have been enabled in the field of Telepresence. The main focus of this thesis is to develop a solution for visual Telepresence, where an HMD is used to control the direction of a …

Stereo Vision System Module For Low-Cost Fpgas For Autonomous Mobile Robots, Connor Citron

Master's Theses

Stereo vision uses two adjacent cameras to create a 3D image of the world. A depth map can be created by comparing the offset of the corresponding pixels from the two cameras. However, for real-time stereo vision, the image data needs to be processed at a reasonable frame rate. Real-time stereo vision allows for mobile robots to more easily navigate terrain and interact with objects by providing both the images from the cameras and the depth of the objects. Fortunately, the image processing can be parallelized in order to increase the processing speed. Field-programmable gate arrays (FPGAs) are highly parallelizable …

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 …

Low Cost Neurochairs, Frankie Pike

Master's Theses

Electroencephalography (EEG) was formerly confined to clinical and research settings with the necessary hardware costing thousands of dollars. In the last five years a number of companies have produced simple electroencephalograms, priced below $300 and available direct to consumers. These have stirred the imaginations of enthusiasts and brought the prospects of "thought-controlled" devices ever closer to reality. While these new devices were largely targeted at video games and toys, active research on enabling people suffering from debilitating diseases to control wheelchairs was being pursued. A number of neurochairs have come to fruition offering a truly hands-free mobility solution, but whether …

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 …

Exploring Trade-Offs In Auv Controller Design For Shark Tracking, Louis James Bertsch Iv

Master's Theses

This thesis explores the use of an Autonomous Underwater Vehicle (AUV) to track and pursue a tagged shark through the water. A controller was designed to take bearing and range to the shark tag and then control the AUV to pursue it.

First, the ability of a particle filter to provide an accurate estimation of the location of the shark relative to the AUV is explored. Second, the ability of the AUV to follow the shark's path through the water is shown. This ability allows for localized environmental sampling of the shark's preferred path. Third, various path weightings are used …

Robust Region Tracking In Multi-Agent Systems Utilizing Sliding Mode Control: Theory And Applications, Mark Bacon

Master's Theses

This thesis presents a methodology to bring controlled agents within a moving region despite agent interaction dynamics, uncertain forces and parameter variation. The logic is derived from traditional Sliding Mode Control theory with an expanded boundary layer which allows position deviation from the region center to specified bounds. As an example of the utility of this control, multiple methods of herding (controlling passive agents by appropriate positioning of controlled agents) are presented.

Intelligent Planning And Assimilation Of Auv-Obtained Measurements Within A Roms-Based Ocean Modeling System, Benjamin J. Davini

Master's Theses

Efforts to learn more about the oceans that surround us have increased dramatically as the technological ability to do so grows. Autonomous Underwater Vehicles (AUVs) are one such technological advance. They allow for rapid deployment and can gather data quickly in places and ways that traditional measurement systems (bouys, profilers, etc.) cannot. A ROMS-based data assimilation method was developed that intelligently plans for and integrates AUV measurements with the goal of minimizing model standard deviation. An algorithm developed for this system is first described that optimizes paths for AUVs that seeks to improve the model by gathering data in high-interest …

Multiple Robot Boundary Tracking With Phase And Workload Balancing, Michael Jay Boardman

Master's Theses

This thesis discusses the use of a cooperative multiple robot system as applied to distributed tracking and sampling of a boundary edge. Within this system the boundary edge is partitioned into subsegments, each allocated to a particular robot such that workload is balanced across the robots. Also, to minimize the time between sampling local areas of the boundary edge, it is desirable to minimize the difference between each robot’s progression (i.e. phase) along its allocated sub segment of the edge. The paper introduces a new distributed controller that handles both workload and phase balancing. Simulation results are used to illustrate …

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, …