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dc.contributor.supervisor Baltes, Jacky (Computer Science) en_US
dc.contributor.author Bagot, Jonathan
dc.date.accessioned 2014-08-20T15:24:25Z
dc.date.available 2014-08-20T15:24:25Z
dc.date.issued 2014-08-20
dc.identifier.uri http://hdl.handle.net/1993/23829
dc.description.abstract Robots moving about in complex environments must be capable of determining and performing difficult motion sequences to accomplish tasks. As the tasks become more complicated, robots with greater dexterity are required. An increase in the number of degrees of freedom and a desire for autonomy in uncertain environments with real-time requirements leaves much room for improvement in the current popular robot motion planning algorithms. In this thesis, state of the art robot motion planning techniques are surveyed. A solution to the general movers problem in the context of motion planning for robots is presented. The proposed robot motion planner solves the general movers problem using a sample-based tree planner combined with an incremental simulator. The robot motion planner is demonstrated both in simulation and the real world. Experiments are conducted and the results analyzed. Based on the results, methods for tuning the robot motion planner to improve the performance are proposed. en_US
dc.subject Robot en_US
dc.subject Motion Planning en_US
dc.subject Rapidly Exploring Random Tree en_US
dc.subject Forward Kinematics en_US
dc.subject Inverse Kinematics en_US
dc.subject Jacobian en_US
dc.subject Probabilistic Road Map en_US
dc.subject Configuration Space en_US
dc.subject Humanoid en_US
dc.subject Denavit Hartenberg en_US
dc.subject Nearest Neighbor en_US
dc.subject Incremental Simulator en_US
dc.title Single-Query Robot Motion Planning using Rapidly Exploring Random Trees (RRTs) en_US
dc.degree.discipline Computer Science en_US
dc.contributor.examiningcommittee Anderson, John (Computer Science) McLeod, Robert (Electrical and Computer Engineering) en_US
dc.degree.level Master of Science (M.Sc.) en_US
dc.description.note October 2014 en_US


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