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Full-Text Articles in Engineering
Robust Uncertainty Estimation Framework In Deep Reinforcement Learning For Active Slam, Bryan Joseph Pedraza
Robust Uncertainty Estimation Framework In Deep Reinforcement Learning For Active Slam, Bryan Joseph Pedraza
Theses and Dissertations
Autonomous mobile robots are essential in various domains such as industry, manufacturing and healthcare. Navigating autonomously and avoiding obstacles are crucial tasks that involve localizing the robot to explore and map unknown environments without prior knowledge. Simultaneous localization and mapping (SLAM) present significant challenges. In this study, we introduce a new approach to address robust navigation and mapping of robot actions using Bayesian Actor-Critic (A2C) reinforcement learning. The A2C framework combines policy-based and value-based learning by dividing the model into two components: (1) the policy model (Actor) determines the actions based on the state, and (2) the value model (Critic) β¦
Uncertainties In Retrieval Of Remote Sensing Reflectance From Ocean Color Satellite Observations, Eder I. Herrera Estrella
Uncertainties In Retrieval Of Remote Sensing Reflectance From Ocean Color Satellite Observations, Eder I. Herrera Estrella
Dissertations, Theses, and Capstone Projects
Ocean Color radiometry uses remote sensing to interpret ocean dynamics by retrieving remote sensing reflectance (π ππ ) from satellite imagery at different scales and over different time periods. π ππ spectrum characterizes the ocean color that we observe, and from which we can discern concentrations of chlorophyll, organic and inorganic particles, and carbon fluxes in the ocean and atmosphere. π ππ is derived from the total radiance at the top of the atmosphere (TOA). However, it only represents up to ten percent of the total signal. Hence, the retrieval of π ππ from the total radiance at TOA involves the application of atmospheric correction β¦
Addressing The Challenged Of Dcop Based Decision-Making Algorithms In Modern Power Systems, Luis Daniel Ramirez Burgueno
Addressing The Challenged Of Dcop Based Decision-Making Algorithms In Modern Power Systems, Luis Daniel Ramirez Burgueno
Open Access Theses & Dissertations
Natural disasters have been determined as the leading cause of power outages, causing not only huge economic losses, but also the interruption of crucial welfare activities and the arise of security concerns. Because of the later, decision-making considering grid modernization, power system economics, and system resiliency has been a crucial theme in power systemsΓ’?? research. The need to better withstand catastrophic events and reducing the dependency of bulky generating units has propelled the development and better management of behind-the-meter generation or distributed energy resources (DERs). DERs can assist in the grid in different manners, not only by meeting energy demand β¦
Evaluation Of Lidar Uncertainty And Applications Towards Slam In Off-Road Environments, Zachary D. Jeffries
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. β¦