TY - THES A1 - Long, Xianchao A2 - Padir, Taskin A2 - Gennert, Michael A. A2 - Torres-Jara, Eduardo AB - This thesis presents an effective approach to study tactile based mobile robot navigation. A Matlab simulator, which can simulate the properties of the tactile sensors, the environment, and the motion of the robot, is developed. The simulator uses an abstraction model of a compliant tactile sensor to represent an array of sensors covering the robot. The tactile sensor can detect normal and shear forces. The simulator has been used by a set of human subjects to drive a robot in an indoor environment to capture data. The details of the implementation and the data collected are presented in this thesis. From the data, some contact features can be extracted. Regarding the features, this thesis uses the Gaussian classifier and Gaussian mixture model to classify the data and build the feature classification model. Comparing the classification results of these two methods, the Gaussian mixture model has better performance. Applying the feature classification model, some contact objects can be detected, such as wall and corner. Based on this classification tool, a simple navigation problem can be solved successfully. DA - 2013/06/13 DB - Digital WPI DP - Worcester Polytechnic Institute ID - etd-061313-134710 KW - tactile sensing KW - Simulator L1 - https://digital.wpi.edu/show/dn39x1713 LA - English LK - https://digital.wpi.edu/ PB - Worcester Polytechnic Institute PY - 2013 T1 - Tactile-Based Mobile Robot Navigation UR - https://digital.wpi.edu/show/5x21tf61x ER -