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.

Heritage Language Maintenance and Biliteracy Development for Immigrants' Children: A Study of Chinese Immigrants' Family Language Policy and Biliteracy Practices

This study reports on research that examines the family language policy (FLP) and biliteracy practices of middle-class Chinese immigrant families in a metropolitan area in the southwest of the U.S. by exploring language practices pattern among family members, language and literacy environment at home, parents’ language management, parents’ language attitudes and ideologies, and biliteracy practices. In this study, I employed mixed methods, including survey and interviews, to investigate Chinese immigrant parents’ FLP, biliteracy practices, their life stories, and their experience of raising and nurturing children in an English-dominant society. Survey questionnaires were distributed to 55 Chinese immigrant parents and interviews were conducted with five families, including mothers and children. One finding from this study is that the language practices pattern at home shows the trend of language shift among the Chinese immigrants’ children. Children prefer speaking English with parents, siblings, and peers, and home literacy environment for children manifests an English-dominant trend. Chinese immigrant parents’ language attitudes and ideologies are largely influenced by English-only ideology. The priority for learning English surpasses the importance of Chinese learning, which is demonstrated by the English-dominant home literacy practices and an English-dominant language policy. Parents invest more in English literacy activities and materials for children, and very few parents implement Chinese-only policy for their children. A second finding from this study is that a multitude of factors from different sources shape and influence Chinese immigrants’ FLP and biliteracy practices. The factors consist of family-related factors, social factors, linguistic factors, and individual factors. A third finding from this study is that a wide variety of strategies are adopted by Chinese immigrant families, which have raised quite balanced bilingual children, to help children maintain Chinese heritage language (HL) and develop both English and Chinese literacy. The close examination and comparison of different families with English monolingual children, with children who have limited knowledge of HL, and with quite balanced bilingual children, this study discovers that immigrant parents, especially mothers, play a fundamental and irreplaceable role in their children’s HL maintenance and biliteracy development and it recommends to immigrant parents in how to implement the findings of this study to nurture their children to become bilingual and biliterate. Due to the limited number and restricted area and group of participant sampling, the results of this study may not be generalized to other groups in different contexts.