CONCURRENT LOCALIZATION AND MAPPING WITH SONAR SENSORS AND CONSIDERATION OF VEHICLE MOTION

Simultaneous Localization and Mapping (SLAM) is a procedure used to determine the location of a mobile vehicle in an unknown environment, while constructing a map of the unknown environment at the same time. Mobile platforms, which make use of SLAM algorithms, have industrial applications in autonomous maintenance, such as the inspection of flaws and defects in oil pipelines and storage tanks. A typical SLAM consists of four main components, namely, experimental setup (data gathering), vehicle pose estimation, feature extraction, and filtering. Feature extraction is the process of realizing significant features from the unknown environment such as corners, edges, walls, and interior features. In this work, an original feature extraction algorithm specific to distance measurements obtained through SONAR sensor data is presented. This algorithm has been constructed by combining the SONAR Salient Feature Extraction Algorithm and the Triangulation Hough Based Fusion with point-in-polygon detection. The reconstructed maps obtained through simulations and experimental data with the fusion algorithm are compared to the maps obtained with existing feature extraction algorithms. Based on the results obtained, it is suggested that the proposed algorithm can be employed as an option for data obtained from SONAR sensors in environment, where other forms of sensing are not viable. The algorithm fusion for feature extraction requires the vehicle pose estimation as an input, which is obtained from a vehicle pose estimation model. For the vehicle pose estimation, the author uses sensor integration to estimate the pose of the mobile vehicle. Different combinations of these sensors are studied (e.g., encoder, gyroscope, or encoder and gyroscope). The different sensor fusion techniques for the pose estimation are experimentally studied and compared. The vehicle pose estimation model, which produces the least amount of error, is used to generate inputs for the feature extraction algorithm fusion. In the experimental studies, two different environmental configurations are used, one without interior features and another one with two interior features. Numerical and experimental findings are discussed. Finally, the SLAM algorithm is implemented along with the algorithms for feature extraction and vehicle pose estimation. Three different cases are experimentally studied, with the floor of the environment intentionally altered to induce slipping. Results obtained for implementations with and without SLAM are compared and discussed. The present work represents a step towards the realization of autonomous inspection platforms for performing concurrent localization and mapping in harsh environments.

Applications of Photoinduced Electron Transfer Chemistry: Photoremovable Protecting Groups and Carbon Dioxide Conversion

Traditional organic chemistry has long been dominated by ground state thermal reactions. The alternative to this is excited state chemistry, which uses light to drive chemical transformations. There is considerable interest in using this clean renewable energy source due to concerns surrounding the combustion byproducts associated with the consumption of fossil fuels. The work presented in this text will focus on the use of light (both ultraviolet and visible) for the following quantitative chemical transformations: (1) the release of compounds containing carboxylic acid and alcohol functional groups and (2) the conversion of carbon dioxide into other useable chemicals. Chapters 1-3 will introduce and explore the use of photoremovable protecting groups (PPGs) for the spatiotemporal control of molecular concentrations. Two new PPGs are discussed, the 2,2,2-tribromoethoxy group for the protection of carboxylic acids and the 9-phenyl-9-tritylone group for the protection of alcohols. Fundamental interest in the factors that affect C–X bond breaking has driven the work presented in this text for the release of carboxylic acid substrates. Product analysis from the UV photolysis of 2,2,2-tribromoethyl-(2′-phenylacetate) in various solvents results in the formation of H–atom abstraction products as well as the release of phenylacetic acid. The deprotection of alcohols is realized through the use of UV or visible light photolysis of 9-phenyl-9-tritylone ethers. Central to this study is the use of photoinduced electron transfer chemistry for the generation of ion diradicals capable of undergoing bond-breaking chemistry leading to the release of the alcohol substrates. Chapters 4 and 5 will explore the use of N-heterocyclic carbenes (NHCs) as a catalyst for the photochemical reduction of carbon dioxide. Previous experiments have demonstrated that NHCs can add to CO2 to form stable zwitterionic species known as N-heterocylic-2-carboxylates (NHC–CO2). Work presented in this text illustrate that the stability of these species is highly dependent on solvent polarity, consistent with a lengthening of the imidazolium to carbon dioxide bond (CNHC–CCO2). Furthermore, these adducts interact with excited state electron donors resulting in the generation of ion diradicals capable of converting carbon dioxide into formic acid.