A master thesis from Aalborg University
From Heightmaps to Cameras: Teacher-Student Reinforcement Learning for Rover Navigation: Master’s thesis
[From Heightmaps to Cameras: Teacher-Student Reinforcement Learning for Rover Navigation]
Author(s)
Term
4. semester
Education
Publication year
2025
Submitted on
2025-06-04
Pages
69 pages
Abstract
This thesis investigates a DAgger-based teacher-student framework for transferring navigation behavior from a policy trained on privileged heightmap input to one using noisy RGB-D observations. The goal is to support learning under realistic sensor condi- tions, where reinforcement learning on RGB- D data remains challenging due to its partial and high-dimensional nature. A simulation pipeline was extended to enable separate sen- sor inputs for teacher and student using the RobuROC4 platform. While the student in- creasingly aligned with the teacher’s actions, it failed to generalize or perform the task effectively. This is attributed to memory- bound dataset handling and limited rollout diversity. The findings suggest that teacher- student imitation learning holds promise for sensor modality transfer, but depends on scalable infrastructure capable of supporting large and diverse training datasets.
Keywords
Reinforcement learning ; Imitation learning ; teacher-student ; DAgger ; Isaac Sim ; Isaac Lab ; RLRoverLab ; RobuROC4 ; RB Summit ; Leo Rover ; Simulation ; Camera ; RGB-D ; Heightmap
Documents
Colophon: This page is part of the AAU Student Projects portal, which is run by Aalborg University. Here, you can find and download publicly available bachelor's theses and master's projects from across the university dating from 2008 onwards. Student projects from before 2008 are available in printed form at Aalborg University Library.
If you have any questions about AAU Student Projects or the research registration, dissemination and analysis at Aalborg University, please feel free to contact the VBN team. You can also find more information in the AAU Student Projects FAQs.