CS MSc Thesis Presentation 31 August 2026

Monday, 31 August there will be a master thesis presentation in Computer Science at Lund University, Faculty of Engineering.

The presentation will take place in E:4130 (Lucas).

Note to potential opponents: Register as an opponent to the presentation of your choice by sending an email to the examiner for that presentation (firstname [dot] lastname [at] cs [dot] lth [dot] se). Do not forget to specify the presentation you register for! Note that the number of opponents may be limited (often to two), so you might be forced to choose another presentation if you register too late. Registrations are individual, just as the oppositions are! More instructions for opponents are found here on the LTH thesis project page.

15:15-16:00 in E:4130 (Lucas)

• Presenter: Oscar Gren
• Title: Vision-Language Navigation Models for Mobile Robots
• Examiner: Davide Tateo
• Supervisors: Maj Stenmark (LTH), Hannes Bergkvist (Levtek)

Vision-Language Navigation (VLN) models are a class of machine learning models that interpret natural language instructions and vision data to produce navigation instructions for robotics. This thesis compares several different available VLN models and further fine-tunes a selected model, DualVLN, for an Ackermann-controlled industrial mobile robot. Two different real-world navigation tasks were used as target tasks. Results show that fine-tuning the model increased performance on the target tasks while it decreased performance on a non-target task.

Furthermore, this thesis identifies that navigation datasets R2R and RxR are fundamentally incompatible with the chosen robot. Analysis shows that only around 1 % of episodes in these datasets can be feasibly executed on the robot. To address this, this thesis introduces an Ackermann-adapted model, created by finetuning DualVLN on a subset of R2R and RxR adapted for the specific Ackermann embodiment. This adapted model outperformed the base model on two of three real-world tasks.