Hierarchical Trajectory Generation for a Class of Nonlinear Systems
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General Robotics, Automation, Sensing and Perception Laboratory
General Robotics, Automation, Sensing and Perception Laboratory
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GRASP
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Tabuada, Paulo
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Trajectory generation and motion planning for nonlinear control systems is an important and difficult problem. In this paper, we provide a constructive method for hierarchical trajectory generation and hierarchical motion planning. The approach is based on the recent notion of φ-related control systems. Given a control affine system satisfying certain assumptions, we project the trajectory planning problem onto a φ-related control system of smaller dimension. Trajectories designed for the smaller, abstracted system are guaranteed, by construction, to be feasible for the original system. Constructive procedures are provided for refining trajectories of the coarser system to the more detailed system.
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2003-12-09
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2023-05-16T22:29:09.000
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Copyright 2003 IEEE. Reprinted from Proceedings of the 42nd IEEE Conference on Decision and Control 2003, Volume 6, pages 6090-6095. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Copyright 2003 IEEE. Reprinted from Proceedings of the 42nd IEEE Conference on Decision and Control 2003, Volume 6, pages 6090-6095. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
Copyright 2003 IEEE. Reprinted from Proceedings of the 42nd IEEE Conference on Decision and Control 2003, Volume 6, pages 6090-6095. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.