Thesis (M.A. Sc.)--University of Toronto, 2006. / Source: Masters Abstracts International, Volume: 45-03, page: 1549.

Thesis (M.S.)--West Virginia University, 1999. / Title from document title page. Document formatted into pages; contains vii, 122 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 38-39).

Thesis (M.S.)--Oregon State University, 2010. / Printout. Includes bibliographical references (leaves 65-69). Also available on the World Wide Web.

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Thesis (M. S.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Dr. Ayanna Howard; Committee Member: Dr. Patricio Vela; Committee Member: Dr. Yoria Wardi. Part of the SMARTech Electronic Thesis and Dissertation Collection.

The development of a new family of robotic vehicles for use in the exploration of Mars and other remote planets is an ongoing process. Current rovers have to traverse rough terrain and be able to withstand various conditions on Mars. The goal of this project is to design a new Mars rover mobility system that performs to optimum capability. This project will involve the design and control of a robot that will use wheels, as well as legs, allowing the robot to reconfigure itself to adapt to its current environment and traverse various terrains. This new reconfigurable hybrid robotic vehicle, Byrobot (named after the student), will have a six-legged mobility design for walking. Each leg will have 3 degrees of freedom, controlled by 3 separate servos, for the movement of the legs. Byrobot will also have 4 wheels each directly attached to the shaft of a DC motor, for four-wheel differential drive. By having these two mobility systems, Byrobot will be able to operate in various environments, by capitalizing on the advantages of both legged and wheeled robots. The CAD designing for this new robot is done on Pro-Engineer, and mechanisms and animations will be run to test movement of parts. The actual robot hardware will then be constructed in the Georgia Tech MRDC machine shop. The control system for the robot will be run by the Eyebot, which uses a 25MHz 32bit Controller (Motorola 68332), as well as the SSC-32 Servo Controller from Lynxmotion. This new robotic mobility platform will facilitate future Mars exploration.

Wheel slip is a common problem in planetary rover exploration tasks. During the current Mars Exploration Rover (MER) mission, the Spirit rover almost became trapped on a dune because of wheel slip. As rover missions on harsh terrains expand in scope, mission success will depend not only on rover safety, but also alacrity in task completion. Speed combined with exploration of varied and difficult terrains, the risk of slip increases dramatically. We first characterize slip performance of a rover on harsh terrains by implementing a novel High Fidelity Traversability Analysis (HFTA) algorithm in order to provide slip prediction and detection capabilities to a planetary rover. The algorithm, utilizing path and energy cost functions in conjunction with simulated navigation, allows a rover to select the best path through any given terrain by predicting high slip paths. Integrated software allows the rover to then accurately follow a designated path while compensating for slippage, and reach intended goals independent of the terrain over which it is traversing. The algorithm was verified using ROAMS, a high fidelity simulation package, at 3.5x real time speed. We propose an adaptive path following algorithm as well as a human-trained neural network to traverse multiple harsh terrains using slip as an advantage. On a near-real-time system, and at rover speeds 15 times the current average speed of the Mars Exploration Rovers, we show that the adaptive algorithm traverses paths in less time than a standard path follower. We also train a standard back-propagation neural network, using human and path following data from a near-real-time system. The neural network demonstrates it ability to traverse new paths on multiple terrains and utilize slip to minimize time and path error.

Thesis (M.A. Sc.)--University of Toronto, 2004. / Adviser: G.M.T. D'Eleuterio.

Thesis (Ph. D.)--University of California, San Diego, 2008. / Title from first page of PDF file (viewed September 22, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 202-225).