Fachbereich Informatik

MAS Hall of Fame

Das sind sie - unsere erfolgreichen Absolventinnen und Absolventen des Master of Autonomous Systems. Die Liste wird fortlaufend erweitert. Ergänzungen insbesondere aus weiter zurückliegenden Jahrgängen nehmen wir gern entgegen.

Master Thesis Defense 2024

  • Development of an AI-based method for the pre-evaluation of electrical distribution grids for state-estimation based congestion handling
  • CAPerMoMa: Coupled Active Perception for Mobile Manipulation in Unknown Environments
  • Graph Optimization for View Motion Planner
  • Physically Informed 6D Object Pose Estimation
  • Harnessing Large Language Models for Clinical Entity Extraction and Medical Coding in German Clinical Text
  • Enhancing Synthetic Images for 3D Object Detection in Autonomous Vehicles
  • Joint Speaker Diarization and Recognition through Iterative Refinement
  • Multimodal Deep Anomaly Detection for Robot Pouring Task
  • Exploiting Contacts for Workspace Alignment with a Dual-Arm Mobile Robot
  • Graph CNN-Based Warpage Forecasting for Improved Quality in Electric Battery Case Manufacturing
  • Uncertainty Estimation for Keypoint Detection and its Application in Robot Grasping
  • Knowledge-based Adaptation of Robotic Control and Estimation Architectures in the Presence of Uncertainty
  • Sensor Fusion based SLAM leveraging Hierarchical Representation
  • Online Terrain Traversability Estimation for Wheel-Legged Rover Exploration
  • Towards Enhancing Industrial Process Fault Diagnosis: A Fusion of Logic Rules and Neural Networks
  • Outdoor Navigation in Uneven Terrain using Learning Methods
  • Investigating Surrogate Modeling Techniques for Quality Diversity Optimization of High-Dimensional Discrete Problems  
  • A Model-Based Approach for Fault Detection and Diagnosis in Robotics using Inductive Logic Programming
  • Natural Language Processing and Topic Modeling for Exploring Trends in Human-Robot Interaction
  • Multimodal Emotion-Aware Conversational Agent
  • Context-Aware Product Recommendation Engine for Automated Tender Processing
  • Differentiable Physics For Few-shot Contact Dynamics Learning
  • Deep Learning Based Super Resolution of Urban Digital Surface Models
  • Experience-Based Path Planning Framework for Real-Time Learning from Demonstration
  • Robustness and Fairness Evaluation for the German Question Answering Task
  • Quantitative Comparison of Deep Learning Classifiers and Human Attention in Assessing Rare Disorders
  • Increasing Efficiency of Monte-Carlo Tree Search via Bayesian Optimization

Master Thesis Defense 2023

  • Towards Building a Tomato Crop Localization Map using GPS, IMU, and Visual Odometry
  • 3-D Molecular Conformation Generation Using Machine Learning
  • An Investigation into the Impact of Multimodality on Named Entity Recognition
  • Multimodal Deep Learning-Based Adaptation of Robot Behaviour for Assistive Robotics
  • Applying the Principles of YOLO Object Detector to Timeseries Subsequence Search
  • Pedestrian Activity Monitoring using DeepSORT under Partial Occlusions
  • Multi-modal Emotion Categorization in Oral History Interviews
  • Timetable Optimization With the Help of Reinforcement Learning
  • Time series forecasting models for a simulation-accelerating surrogate model
  • Vehicular In-Cabin Depth Estimation Using Sparse Training Data
  • Deepfakes in Style: Improving Face-swapping Autoencoder with StyleGAN Components
  • Continual Learning in Object Detection
  • Benchmark for Few-Shot 6D Pose Estimation Methods
  • On the Explainability of Neural Network Models to Classify Rare Genetic Syndromes from Frontal Facial Images
  • Vision-Based Automation System to Prepare Harvested Lettuces for Packaging
  • Comparative Evaluation of Feature Extraction Methods for Time Series Classification
  • Property-Based Testing: Formalized Robotic Testing for Standard Compliance
  • Multi-View Temporal Fusion in Semantic Segmentation
  • Computer Assisted Short Answer Grading with Rubrics using Active Learning
  • Comparative analysis of the use of different granularity levels on word embeddings for literature-based knowledge discovery
  • End-to-End Prediction of Driving Commands Using 3D Lane Detection as an Auxiliary Task
  • Continuous Control of Under-Actuated Autonomous Vehicles using Reinforcement Learning Methods
  • Navigation of Bulky Robots in Confined Indoor Spaces

Master Thesis Defense 2022

  • Lifelong Action Learning for Socially Assistive Robots
  • Multi-Person Tracking using Generative Models
  • A Neuromorphic Approach to Obstacle Avoidance in Robot Manipulation
  • Composing Software Architectures for Smart Manipulation Tasks based on the Popov-Vereshchagin Hybrid Dynamics Solver
  • Specifying and Generating Simulated Environments for Verifying Autonomous Mobile Robot Scenarios
  • Uncertainty in Explanation methods for Neural Networks
  • COINS Map: Composable ontology-based indoor semantic map
  • Out-of-Distribution Detection in 3D Semantic Segmentation
  • Empirical evaluation of multi-modal communication between a visually impaired person and an autonomous navigation aid
  • Continual Learning in Semantic Segmentation
  • Learning simulation for plastic sheet extrusion in blow molding machine
  • Novelty Detection in Semantic Segmentation
  • Benchmarking Out Of Distribution Detection Methods in 2D Object Detection
  • DExT: Detector Explanation Toolkit for Explaining Multiple Detections Using Saliency Methods
  • Primitive detection on RGB-D data for a compact hybrid scene representation
  • Multisensor data fusion techniques for mass imbalance detection in wind turbine blades
  • Image Based Quality Control in Thermoplastic Composite Production using Deep Transfer Learning
  • Improving Hazardous Scenarios Traceability for Multi-Robot Systems using Knowledge Graph
  • LiDAR-based indoor localization with optimal particle filters using surface normal constraints
  • Auto-Encoding of Semantic Models of Mobile Robot Environment Based on Ontology for Localization and Navigation
  • Self-supervised Learning for Sonar Images: Enhancing Multimodal Perception for Underwater Applications
  • Evaluation of Drift Detection Techniques for Automated Machine Learning Pipelines
  • Object Detection in Dense Volume Data

Master Thesis Defense 2021 

  • Context-based navigation using composed behaviours
  • Humanoid Robot Grasp Suggestion
  • Visuomotor Policy Learning for Predictive Manipulation
  • Resilience of Edge-optimized CNNs to Adversarial Attacks
  • A Benchmark for Out-of-Distribution Detection in Deep Reinforcement Learning
  • Effective Neighborhood Feature Exploitation in Graph CNNs for Point Cloud Object-Part Segmentation
  • CoLe-VIO: Supervised Complementary Learning of Keyframe Detection and Visual-Inertial Odometry
  • Improving PySpark Performance with Cross-Language Optimization
  • Design and Realisation of Smart Non-prehensile Manipulation Strategies for Robots
  • Automatic Formative Assessment for Students’ Short Text Answers through Feature Extraction
  • Intelligent Neural Network Design for Robotic Embedded Vision
  • Automatic Question and Answer Generation from Domain-Specific Text for Exams
  • Improving Accessibility and Transparency of Large-Scale Robot Experience Data using a Natural Language Interface
  • Visuomotor Policy Learning using Dense Descriptors for Robot Manipulation
  • Enhancing Model Predictive Control to Improve the Navigation of a Quasi Omni-Directional Mobile Robot
  • Vision-based safe robot motion for human-robot collaboration
  • Image-based object detection for autonomous parking using convolutional neural networks
  • Identifying object grasps for manipulation
  • Deep Reinforcement Learning for Continuous Control Docking of Autonomous Underwater Vehicles: A Benchmarking Study
  • Efficient architectures for object pose estimation
  • Improving Uncertainty Estimates in Deep Learning Models using Knowledge Distillation

Master Thesis Defense 2020 

  • PillarFPN: A Feature Pyramid Extension to PointPillars for 3D Object Detection.
  • Knowledge-Enabled Specification of Composable Robot Motion Control Architectures
  • Efficient and Context-aware Pedestrian Trajectory Prediction
  • An investigation of regression as an avenue to find precision-runtime trade-off for object segmentation.
  • Evaluating Uncertainty Estimation Methods on 3D Semantic Segmentation of Point Clouds
  • Development of a New Quality Prediction Approach and Aggregation of a Quality Prediction Pipeline
  • Multi-Robot Task Allocation with Temporal Constraints and Uncertain Durations
  • Feature Extraction for Time Series Classification
  • Generative machine learning model obfuscation
  • Compositional Machine Learning Models for Robotic Manipulation Behaviors
  • Estimating Confidence in Spatio-Temporal Models
  • Explainable Assistive Short Answer Grading
  • A Comprehensive Evaluation of Uncertainty Quantification Methods in Deep Learning
  • Black-Box Optimization of Object Detector Hyper-Parameters.
  • Compliant Manipulation with Reinforcement Learning Guided by Task Specification
  • Skeleton Based Action Recognition: Enhancing Co-occurrence Explorer with View Adaptive Network
  • Lazy Robot Control by Relaxation of Motion and Force Constraints
  • Immersive Telepresence Through 360° Video Streaming: Potentials and Limitations Today
  • Evaluation of Deep Learning Technique for Impulse Sound Classification in 2D Representation
  • Comparative Evaluation of Image Data Selection Methods for Human Pose Estimation

Master Thesis Defense 2019 

  • Vision Based Human Fall Detection
  • Automated gait and pose analysis for lameness detection in cows
  • Realtime Deep Learning for Multispectral Human Detection
  • Multiagent System for Warehouse Material Flow Control
  • Poin cloud classification of real objects using CNNs
  • Semantic localization and navigation for indoor robots using OpenStreetMap
  • A mediator system for querying heterogeneous data in robotic applications​
  • An Evaluation of Deep Learning Object Detection Pipelines for Maritime Application Purposes

Links

Weiterführende Links

R&D Project Defense