Matthew Wallace MS Thesis Defense

Announcing:
MS Thesis Defense

Name:
Matthew Wallace

Title:
Model Predictive Planning

Date:
3/29/2024

Time:
10:00:00 AM

Location:
Room: HS 204.  Link: Teams

Committee Members:
Prof. Laurent Lessard (Advisor)
Prof. Michael Everett
Prof. Derya Aksaray

Abstract:
This thesis presents Model Predictive Planning (MPP), a trajectory planner for low-agility vehicles such as a fixed-wing aircraft to navigate obstacle-laden environments.  MPP consists of (1) a multi-path planning procedure that identifies candidate paths, (2) a raytracing procedure that generates linear constraints around these paths that enforce obstacle avoidance, and (3) a convex quadratic program that finds a feasible trajectory within these constraint if one exists. Low-agility aircraft cannot track arbitrary paths, so refining a given path into a trajectory that respects the vehicle’s limited maneuverability and avoids obstacles often leads to an infeasible optimization problem. The critical feature of MPP is that it efficiently considers multiple candidate paths during the refinement process, thereby greatly increasing the chance of finding a feasible and trackable trajectory. I begin by presenting a background on path planning, trajectory optimization, and Model Predictive Control.  This is followed by a presentation of the MPP algorithm.  Finally, I demonstrate the effectiveness of MPP on both a longitudinal and 3D aircraft model.