activity
20242026
collaborators

10 papers

cs.CV2026

GraphPilot: Grounded Scene Graph Conditioning for Language-Based Autonomous Driving

Fabian Schmidt, Markus Enzweiler, Abhinav Valada

Vision-language models have recently emerged as promising planners for autonomous driving, where success hinges on topology-aware reasoning over spatial structure and dynamic inter…

cs.RO2026

Sensor Configuration Matters: A Systematic Evaluation of Multimodal SLAM on Quadruped Robots

Roberto Corlito, Fabian Schmidt, Nils Seibert +3

Autonomous navigation of quadrupedal robots in diverse environments fundamentally relies on resilient Simultaneous Localization and Mapping (SLAM). While visual-inertial SLAM has m…

cs.SE2025

A Systematic Literature Review on Detecting Software Vulnerabilities with Large Language Models

Sabrina Kaniewski, Fabian Schmidt, Markus Enzweiler +2

The increasing adoption of Large Language Models (LLMs) in software engineering has sparked interest in their use for software vulnerability detection. However, the rapid developme…

cs.CV2025

Enhancing LLM-based Autonomous Driving with Modular Traffic Light and Sign Recognition

Fabian Schmidt, Noushiq Mohammed Kayilan Abdul Nazar, Markus Enzweiler +1

Large Language Models (LLMs) are increasingly used for decision-making and planning in autonomous driving, showing promising reasoning capabilities and potential to generalize acro…

cs.RO2025

Integration of Visual SLAM into Consumer-Grade Automotive Localization

Luis Diener, Jens Kalkkuhl, Markus Enzweiler

Accurate ego-motion estimation in consumer-grade vehicles currently relies on proprioceptive sensors, i.e. wheel odometry and IMUs, whose performance is limited by systematic error…

cs.RO2025

Radar-Based Odometry for Low-Speed Driving

Luis Diener, Jens Kalkkuhl, Markus Enzweiler

We address automotive odometry for low-speed driving and parking, where centimeter-level accuracy is required due to tight spaces and nearby obstacles. Traditional methods using in…