Autonomous Systems (MSc)

R&D Project Defense

Hier finden Sie die erfolgreich abgeschlossenen R&D Projekte unserer Studierenden aus dem Studiengang Master Autonome Systeme. Die Liste wird fortlaufend erweitert. Ergänzungen insbesondere aus weiter zurückliegenden Jahrgängen nehmen wir gerne entgegen.

R&D Project Defense 2024

  • A Comparative Study of Visual Anomaly Detection Methods in Industrial Inspection
  • Cyber Threats and Risk Mitigation in Autonomous Vehicles
  • Object detection in adverse weather conditions using tightly-coupled data-driven multimodal sensor fusion
  • Learning-Based Individual Plant Detection for Vegetation Monitoring of Post-Harvest Forest Floor Using Aerial Imagery
  • Combining Multi-speaker Recognition and Diarization
  • A Study On Multi-Classification Problem Of fNIRS Data Using Right-Hand Fingers
  • Exploiting contact constraints in robotic manipulation tasks

R&D Project Defense 2023

  • Integrating Anomaly Detection with Fault Diagnosis for Long-Horizon Tasks
  • Automatic LiDAR - Camera Extrinsic Calibration Based on Natural Features in the Environment
  • From Motion Specifications to Robot Control Architectures: Design and Implementation of a DSL for Robot Manipulation
  • Semantic mapping for enhanced localization in indoor environments
  • 3D Object Detection for Autonomous Driving Using Stereo Vision
  • Difference Annotation for Car Crash Software Reports
  • Safe and Fault-aware Child-Robot Natural Language Interaction
  • Automated Grading System for Plot Grading
  • Similarity Calculation and Textual Entailment Identification for Short Answers
  • Interval-based anomaly isolation in friction stir welding using machine learning
  • Model-based time series synthesis for stress wave classification
  • Learning Efficient Knife Handling Skills in Semi-Structured Environments on a Dual-Arm Robot
  • Developing Framework to Compare 2D to 3D Few-shot Object Detection Algorithms
  • Evaluation of Visual SLAM Approaches for UAVs in Indoor Environments
  • Uncertainty Estimation for Quantized Deep Learning Models: Comparative Study
  • Language Modelling for Conversational Speech Recognition
  • Benchmarking Uncertainty Estimation of Deep Learning Models Using Synthetic Dataset
  • Development and implementation of a self-learning control approach for contact-rich object manipulation
  • Evaluation and Comparison of Real-Time Robot Perception Capabilities in a 24/7 Supermarket
  • Anomaly detection with acoustic data in friction stir welding
  • A Method for Creating a Forest Surface Temperature Model
  • Tree Stump Detection Using Learning-Based Methods with Data Fusion
  • Ontology for Integrating Failure Mode and Effect Analysis and Issue Reporting in Robotics
  • ROS based provenance for robotic applications
  • Uncertainty Estimation for Key-point Detection Task : Robustness Study
  • Similarity in Convolutional Neural Networks
  • Real-Time Body Movement Analysis Of Fitness Exercises For Paralyzed People Using Sensors

R&D Project Defense 2022

  • Evaluation of Visual Object Tracking Methods on Multimedia Datasets
  • Automatic Consistency Check Of Table & Text In Financial Documents
  • Semantic Video Keyframe Extraction
  • Automatic Consistency Check Of Table & Text In Financial Documents
  • 3D Molecular Representation Using Machine Learning Models
  • Traffic Sign Data Augmentation using Cycle-Consistent Generative Adversarial Networks (CycleGAN)
  • Investigating topic segmentation for online news classification
  • Tangible Programming in Open Roberta Lab
  • Analysis of Active Learning Mechanism Applied to Language Models for Computer Assisted Short Answer Grading
  • Learning human gestures by imitation for robots
  • Personalised Behaviour Models for Child-Robot Interaction
  • Hard/Soft logic inferencing using machine learning approaches in ODIN-II
  • Benchmarking object placement algorithms for mobile robotic manipulators
  • Uncertainty Estimation in Prediction of Time-series
  • An intelligent approach to detect valid Measurement Sequence for Driving Dynamics
  • Testbench for UAVs
  • Assurance Cases for Learning Enabled Components
  • Implementing an Enhanced Fruit Tracking System for Precision Agriculture
  • Design of Semantic Parsers for Knowledge Representation using existing Computer Vision outputs
  • Speech Emotion Recognition from German Oral History Interviews
  • Automatic Scenario Detection for ADAS using Dynamic Time Warping
  • Evolving Deep Neural Network Architectures for Time Series Classification
  • Interactive Learning Loop for Modelling Valid Measurement Data in Driving Dynamics Evaluation
  • Anomaly Detection in Time Series Data

R&D Project Defense 2021

  • Classification of the Degree of Destruction of Laminated Safety Glass by Texture Analysis
  • Design of Cost-Effective, Lightweight Robotic Running Coach
  • Deep Learning for Livestock Detection
  • UAV Path Planning In 3D Unstructured Environment
  • Development of an UAV 3D terrain mapping system for forestry application
  • Design and feasibilityy of a UAV based seeding mechanism
  • Comparative Evaluation of Adversarial Attacks and its Defense Mechanisms on Deep Neural Network
  • Comparative Analysis of Explanations for Multivariate Time Series Classification
  • Imbalance Problems in Vision-based Object Detection and Learning from Negative Examples
  • Generic Object Segmentation in Dense Volume Data
  • Comparative evaluation of unsupervised methods for video anomaly detection
  • Estimation of water content in agricultural land via UAV-based sensing
  • Model-driven engineering support for ROS 2 through meta-models and tooling
  • Benchmarking Uncertainty Estimation Methods in Deep Learning for Regression
  • Explaining Deep Learning Models for Detecting Anomalies in Time Series Data
  • Registering and visualizing point cloud data with existing 3D CityGML Models
  • Clustering Techniques in Computer-Assisted Short Answer Grading
  • Automated Test Generation for Robot Self-Examination
  • Survey on Video-based Anticipation for Anomaly Detection
  • Comparative Evaluation of Generative Models for Future Frame Prediction
  • Feature Extraction for Motion Data
  • Environmental Sound Classification Using Deep Learning
  • Acoustic Quality Checking of Gearboxes using Machine Learning
  • Comparison between Fixed-weight Neural Network and Bayesian Neural Network for 3D Object Detection in Autonomous Driving

R&D Project Defense 2020

  • NEPO Framework based on Blockly Library
  • Automatic Question Generation For Exams
  • Identification of Reliable Observations in Car-Crash Analysis
  • Localization of Objects Using Unsupervised Representation Learning and Object Proposal Techniques
  • Generative Models for the Analysis of Dynamical Systems with Applications
  • Evaluation of Change Point Detection Algorithms for Time-Zero Estimation in Vehicle Crash Tests
  • Intelligent Identification of Valid Measurement Data for Driving Dynamics Evaluation
  • Detection of Occluded Pedestrians Using Deep Learning Techniques
  • Comparative Study of 3D Object Detection Frameworks Based on LiDAR Data and Sensor Fusion Technologies
  • Implementation of weightless neural networks on GPU for background subtraction
  • Comparing Reinforcement Learning Generalization across Physics Engines
  • Simulation of realistic traffic flows with genetic algorithms
  • Dynamic Modelling and Identification of the Neobotix MPO-700 Mobile Robot
  • Whole Body Contact Sensing in Human Robot Interaction: A Comprehensive Literature Survey with Preliminary Implementations
  • Fusing 3D Range Measures with Video Data for Robust Obstacle Detection and Avoidance
  • Comparative evaluation of mobile LiDAR-based 3D mapping systems for robot navigation in large-scale environments
  • Comparative Evaluation of Transfer Learning Models in Semantic Text Similarity
  • Embedded Deep Learning for Image-Based Grasp Verification
  • A Comprehensive Classification and Evaluation of Deep Learning Techniques for Object Detection in Videos
  • Multimodal machine learning techniques for evaluating task performance in robots
  • A Comparative Study of Sparsity Methods in Deep Neural Network for Faster Inference
  • Interactive Learned Models to Aid Human-Decision Making
  • Retrieval-based Geo-Localization from Aerial Images Using CNN Features
  • Towards smart coupling in multiphysics simulation
  • Evaluation of Language Interoperability Issues in PySpark

R&D Project Defense 2019

  • Comparative Study of Uncertainty Estimation Methods in Deep Learning based Classification Models
  • SqueezeBox: Real Time CPU Face Detector
  • Incorporating Contextual Knowledge Into Human-Robot Collaborative Task Execution
  • Comparative analysis of experience-based path planning frameworks for multi-robot systems
  • Assessing Service Robots Experience Data with Conversational Interfaces
  • Neural Scrutiny: A comparative study of neural network architecture generation techniques
  • On Using Convolutional Neural Networks for Human Activity Recognition with Accelerometer Data
  • Singularity detection in the Vereshchagin hybrid dynamics solver
  • Extending the Vereshchagin hybrid dynamic solver to mobile robots
  • Safe Reinforcement Learning - Comparative Evaluation and Experimentation