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dc.contributor.advisor Ferrari, Silvia en_US
dc.contributor.author Swingler, Ashleigh en_US
dc.date.accessioned 2012-05-25T20:18:41Z
dc.date.available 2012-05-25T20:18:41Z
dc.date.issued 2012 en_US
dc.identifier.uri http://hdl.handle.net/10161/5542
dc.description Thesis en_US
dc.description.abstract <p>This thesis develops a novel solution method for the problem of collision-free, optimal control of a robotic vehicle in an obstacle populated environment. The technique presented combines the well established approximate cell decomposition methodology with disjunctive programming in order to address both geometric and kinematic trajectory concerns. In this work, an algorithm for determining the shortest distance, collision-free path of a robot with unicycle kinematics is developed. In addition, the research defines a technique to discretize nonholonomic vehicle kinematics into a set of mixed integer linear constraints. Results obtained using the Tomlab/CPLEX mixed integer quadratic programming software exhibit that the method developed provides a powerful initial step in reconciling geometric path planning methods with optimal control techniques.</p> en_US
dc.subject Robotics en_US
dc.subject Artificial intelligence en_US
dc.subject Cell Decomposition en_US
dc.subject Mixed Integer Programming en_US
dc.subject Motion Planning en_US
dc.subject Unicycle Model en_US
dc.title A Cell Decomposition Approach to Robotic Trajectory Planning via Disjunctive Programming en_US
dc.type Thesis en_US
dc.department Mechanical Engineering and Materials Science en_US

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