Author: Sidney Molnar
Title of dissertation: Metareasoning Strategies to Correct Navigation Failures of Autonomous Ground Robots
Date/time: April 8th, 2024 at 10:00am
Zoom: https://umd.zoom.us/j/9892794999?omn=94673990602
Location: 2164 DeWALT Conference Room, Glenn L. Martin Hall.
Committee members:
- Dr. Jeffrey Herrmann, Advisor and Chair
- Dr. Michael Otte
- Dr. Shapour Azarm
Abstract: Due to the complexity of autonomous systems, theoretically perfect path planning algorithms sometimes fail because of unexpected behaviors that occur when these systems interact with various sub-processes like perception, mapping, and goal planning. These failures can prevent the success of a mission, especially in complex and unexplored environments. Metareasoning, or “thinking about thinking,” is one approach to mitigate these planning failures. This project introduces a novel metareasoning approach that employs various methods of monitoring and control to identify and address path planning irregularities that lead to failures. All methods were integrated into the ARL ground autonomy stack, which utilizes both global and local path planning ROS nodes. The monitoring methods proposed include listening to messages from the planning algorithms, assessing the environmental context of the robot, expected progress methods that evaluate the robot’s progress based on its movement capabilities from a milestone checkpoint, and fixed radius methods that use parameters selected based on mission objectives to assess progress from a milestone checkpoint. The control policies introduced are metric-based sequential policies which select new planner combinations based on benchmark robot performance metrics, context-based pairs policies that assess the effects of switching between two planner combinations, and a restart policy that relaunches a new instance of the same planner combination. The study evaluated which combinations of monitoring and control policies improved or degraded navigation performance by assessing how close the robot could get to the final mission goal. Additionally, this thesis suggests areas for further research to determine the conditions under which metareasoning can improve navigation.