A State Space Partitioning Scheme for Vehicle Control in Pursuit-Evasion Scenarios

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.

Name thesis:degree_name

Ph. D.

Level thesis:degree_level

doctoral

Discipline thesis:degree_discipline

Mechanical Engineering

Department dc:contributor.department

Mechanical Engineering

Grantor dc:publisher

Virginia Tech

Year dc:date.issued

2011

Author dc:creator

• Goode, Brian Joseph

Chair dc:contributor.committeechair

• Roach, John W.

Committee members dc:contributor.committeemember

• Kurdila, Andrew J.
• Leonessa, Alexander
• Papenfuss, Cory M.
• Stilwell, Daniel J.

• Bellman optimality
• differential games
• pursuit-evasion
• path planning
• vehicle control

Statement dc:rights

• In Copyright

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Dc Identifier Other

etd-10282011-170419

OAI identifier oai:identifier

oai:vtechworks.lib.vt.edu:10919/40266