Title page for ETD etd-10282011-170419


Type of Document Dissertation
Author Goode, Brian Joseph
URN etd-10282011-170419
Title A State Space Partitioning Scheme for Vehicle Control in Pursuit-Evasion Scenarios
Degree PhD
Department Mechanical Engineering
Advisory Committee
Advisor Name Title
Roach, John W. Committee Chair
Kurdila, Andrew J. Committee Member
Leonessa, Alexander Committee Member
Papenfuss, Cory M. Committee Member
Stilwell, Daniel J. Committee Member
Keywords
  • Bellman optimality
  • differential games
  • pursuit-evasion
  • path planning
  • vehicle control
Date of Defense 2011-10-21
Availability restricted
Abstract
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.

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