Date of Award
Master of Science in Electrical Engineering
Department of Electrical and Computer Engineering
Jason M. Bindewald, PhD.
Autonomous systems are increasingly being used for complex tasks in dynamic environments. Robust automation needs to be able to establish its current goal and determine when the goal has changed. In human-machine teams autonomous goal detection is an important component of maintaining shared situational awareness between both parties. This research investigates how different categories of goals affect autonomous change detection in a dynamic environment. In order to accomplish this goal, a set of autonomous agents were developed to perform within an environment with multiple possible goals. The agents perform the environmental task while monitoring for goal changes. The experiment tests the agents over a range of goal changes to determine how detection performance is affected by the different categories of goals. Results show that detection is highly dependent on what goal is being switch to and from. The point similarity between goals is the most significant factor in evaluating the change detection time. An additional experiment improved upon the goal agent and demonstrated the importance of having the proper perception mechanics for feedback within the environment.
DTIC Accession Number
Ball, Nathan R., "Effects of Dynamic Goals on Agent Performance" (2018). Theses and Dissertations. 1829.