CIS THESIS DEFENSE BY Phillip Igoe
When: Wednesday,
March 21, 2018
12:00 AM
-
Friday,
March 23, 2018 12:00 AM
Where: > See description for location
Description: College of Engineering
Computer and Information Science Department
Thesis defense by: Phillip Igoe
Date & Time: Friday, March 23, 2018, 3:00 PM
Location: Dion 115
Thesis Advisor: Dr. Ramprasad Balasubramanian
Thesis Committee: Dr. David Koop and Dr. Ming Shao
Title: An Expandable Decision Framework for Real Time Side-Scan Sonar Data Analysis and Action-selection with MOOS-IvP to support AUV Autonomy
Abstract: An important application for Autonomous Underwater Vehicles (AUVs) is to utilize them to survey large underwater areas to detect objects of interest. The capabilities of AUVs are augmented with the multi-objective autonomy platform called the Mission Oriented Operate Suite (MOOS) Interval Programming (IvP), which enables behavior-based autonomy for robotic platforms. An Expandable Decision Framework was created that supports real-time post-processing of side-scan sonar data, feature detection, and facilitates behavior-selection based on detected objects of interest. The framework has been implemented to utilize external modules for the post-processing of raw sonar data, and feature detection of the processed sonar data, such that different implementations can be used for different techniques. Modules for the specific use case of performing dynamically created re-acquire and identify (RID) search patterns on localized anomalies that are detected during a survey mission have been developed to show that the framework is extendable and is capable of real-time analysis to support autonomy. The framework has been tested in simulation with multiple previously collected sonar data on AUV missions.
For further information please contact Dr. Ram Balasubramanian at r.bala@umassd.edu.
Pastries and beverages will be served.
Computer and Information Science Department
Thesis defense by: Phillip Igoe
Date & Time: Friday, March 23, 2018, 3:00 PM
Location: Dion 115
Thesis Advisor: Dr. Ramprasad Balasubramanian
Thesis Committee: Dr. David Koop and Dr. Ming Shao
Title: An Expandable Decision Framework for Real Time Side-Scan Sonar Data Analysis and Action-selection with MOOS-IvP to support AUV Autonomy
Abstract: An important application for Autonomous Underwater Vehicles (AUVs) is to utilize them to survey large underwater areas to detect objects of interest. The capabilities of AUVs are augmented with the multi-objective autonomy platform called the Mission Oriented Operate Suite (MOOS) Interval Programming (IvP), which enables behavior-based autonomy for robotic platforms. An Expandable Decision Framework was created that supports real-time post-processing of side-scan sonar data, feature detection, and facilitates behavior-selection based on detected objects of interest. The framework has been implemented to utilize external modules for the post-processing of raw sonar data, and feature detection of the processed sonar data, such that different implementations can be used for different techniques. Modules for the specific use case of performing dynamically created re-acquire and identify (RID) search patterns on localized anomalies that are detected during a survey mission have been developed to show that the framework is extendable and is capable of real-time analysis to support autonomy. The framework has been tested in simulation with multiple previously collected sonar data on AUV missions.
For further information please contact Dr. Ram Balasubramanian at r.bala@umassd.edu.
Pastries and beverages will be served.
Contact: > See Description for contact information
Topical Areas: University Community, Computer and Information Science