Pursuit-evasion games are the subject of a variety of research initiatives seeking to provide some level of autonomy to mobile, robotic vehicles with on-board controllers. Applications of these controllers include defense topics such as unmanned aerial vehicle (UAV) and unmanned underwater vehicle (UUV) navigation for threat surveillance, assessment, or engagement. Controllers implementing pursuit-evasion algorithms are also used for improving everyday tasks such as driving in traffic when used for collision avoidance maneuvers.
Currently, pursuit-evasion tactics are incorporated into the control by solving the Hamilton-Jacobi-Isaacs (HJI) equation explicitly, simplifying the solution using approximate dynamic programming, or using a purely finite-horizon approach. Unfortunately, these methods are either subject to difficulties of long computational times or having no guarantees of succeeding in the pursuit-evasion game. This leads to more difficulties of implementing these tactics on-line in a real robotic scenario where the opposing agent may not be known before the maneuver is required.
This dissertation presents a novel method of solving the HJI equation by partitioning the state space into regions of local, finite horizon control laws. As a result, the HJI equation can be reduced to solving the Hamilton-Jacobi-Bellman equation recursively as information is received about an opposing agent. Adding complexity to the problem structure results in a decreased calculation time to allow pursuit-evasion tactics to be calculated on-board an agent during a scenario. The algorithms and implementation methods are given explicitly and illustrated with an example of two robotic vehicles in a collision avoidance maneuver. / Ph. D.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/40266 |
| Date | 01 November 2011 |
| Creators | Goode, Brian Joseph |
| Contributors | Mechanical Engineering, Roach, John W., Kurdila, Andrew J., Leonessa, Alexander, Papenfuss, Cory M., Stilwell, Daniel J. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
| Relation | Goode_BJ_D_2011.pdf, Goode_BJ_D_2011_Copyright.pdf |
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