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Autonomous ground vehicles (AGVs) are expected to be used extensively in unstructured, outdoor, undulating environments for tasks such as search and rescue, homeland security, fire fighting, reconnaissance, and surveillance. These tasks will greatly benefit from efficient motion planning for the AGVs, which can only be accomplished by using correct dynamic and power models of the vehicles. Skid-steered vehicles are often used as outdoor mobile robots due to their robust mechanical structure and high maneuverability. Sliding along with rolling is inherent to general curvilinear motion, which makes both dynamic modeling and power modeling difficult. This research focuses on developing and experimentally verifying dynamic models of a skid-steered wheeled vehicle for general planar (2D) motion and for linear 3D motion. These models are characterized by the coefficient of rolling resistance, the coefficient of friction, and the shear deformation modulus, which have terrain-dependent values. The dynamic models also include motor saturation and motor power limitations, which enable correct prediction of saturated velocities when the vehicle works at its maximum velocity or power. This research employs the dynamics models for hill climbing by using Sampling Based Model Predictive Control, a novel motion-planing algorithm designed to use dynamic models. In addition this research also uses the developed dynamic models to derive the power models for skid-steered vehicles. The power models are described from the motor's perspective and include both the mechanical power consumption and electrical power consumption. The power models reveal the interesting phenomenon that the inner motor consumes, generates and consumes power again while the vehicle turning radius decreases. Experiments were conducted to verify the validity of the dynamic models and power models for different scenarios with different trajectory, and also show the advantage of using dynamic models for motion planning that involves climbing hills.
Skid-steered Vehicle, Control, Motion Planning, Dynamic Modeling, Power Modeling, Robot
Date of Defense
July 22, 2010.
Submitted Note
A Dissertation submitted to the Department of Mechanical Engineering in partial fulfillment of the requirements for the degree of Doctor of Philosophy.
Bibliography Note
Includes bibliographical references.
Advisory Committee
Emmanuel G. Collins, Professor Directing Thesis; Chris S. Edrington, University Representative; Jonathan Clark, Committee Member; William S. Oates, Committee Member; Patrick J. Hollis, Committee Member.
Publisher
Florida State University
Identifier
FSU_migr_etd-0913
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