Date of Award
Bachelor of Science
Engineering (Concentration: Electrical Engineering)
Dr. David J. Ahlgren
A robot was built and programmed to implement a Simultaneous Localization and Mapping (SLAM) Algorithm. Traditional robotic mapping suffers from compounding sensor error, thus resulting in maps that become highly erroneous over time. SLAM combats this problem by taking a probabilistic approach to mapping. By combining odometry data with sensor measurements of surrounding landmarks through a Kalman Filter, the robot was able to accurately map its surrounding environment, and localize itself within that environment.
Norton, Adam T. and McCook, Anson R., "Implementation of a Simultaneous Localization and Mapping Algorithm in an Autonomous Robot". Senior Theses, Trinity College, Hartford, CT 2012.
Trinity College Digital Repository, http://digitalrepository.trincoll.edu/theses/212