Academic CV · PhD Applications
Panagiota Grosdouli
Robotics · Robust Autonomy · Uncertainty-Aware AI
Profile
Electrical and Computer Engineering student building a PhD-oriented research portfolio in robust autonomy, visual-inertial localization, adaptive SLAM, uncertainty-aware sensor fusion, risk-aware navigation, and intelligent mobility safety.
Research Direction
My central research interest is how autonomous systems can remain reliable when perception, localization, mapping, and planning become uncertain.
I am particularly interested in graduate research groups working on SLAM, field robotics, UAV autonomy, safe robot navigation, uncertainty-aware perception, and intelligent transportation systems.
Education
MEng Electrical & Computer Engineering
2020–2026Democritus University of Thrace, Xanthi, Greece
Thesis direction: Trajectory Prediction of Vulnerable Road Users at Smart Intersections
Research Interests
- -Robust Autonomy: autonomous systems that remain reliable under perception, localization, and map uncertainty
- -Visual-Inertial Odometry & SLAM: degradation monitoring, adaptive sensor fusion, and self-healing localization
- -Risk-Aware Navigation: planning and replanning under uncertainty, collision risk, and safety constraints
- -Intelligent Mobility: trajectory prediction and vulnerable road-user safety at smart intersections
- -Computer Vision for Robotics: scene understanding, semantic perception, and failure-case analysis
Research Projects
SHIELD-VIO: Self-Healing Visual-Inertial Odometry
Flagship Robotics Research
Study whether visual-inertial odometry systems can detect degradation, diagnose likely failure causes, and select recovery actions before localization failure.
AEGIS-VIO: Uncertainty-Gated Visual-Inertial Estimation
VIO Safety Extension
Explore uncertainty-gated measurement selection for visual-inertial estimation under blur, lighting change, and dynamic-scene contamination.
Adaptive Multi-Modal SLAM with Uncertainty-Aware Sensor Fusion
Robust SLAM Research
Investigate adaptive fusion of visual, inertial, and event-based sensing under perceptual degradation such as blur, low light, texture scarcity, and rapid motion.
DynNav: Uncertainty-Aware Risk-Sensitive Navigation
Risk-Aware Navigation
Develop and evaluate navigation methods that reason about map uncertainty, collision risk, returnability, and safe replanning in unknown environments.
SafeCrossAI: Intelligent Intersection Safety
Intelligent Mobility Research
Develop a research platform for vulnerable road-user trajectory prediction, interaction modelling, risk assessment, and intelligent intersection safety.
OpenUWOC-AI: AI for Underwater Optical Wireless Communication
Communication-Constrained Autonomy
Explore how AI methods can support underwater optical communication reliability, channel adaptation, and communication-aware autonomy.
Urban Segmentation for Delivery Robots
Urban Robot Perception
Build a semantic-perception project for sidewalk and urban delivery robots, focused on navigability, obstacles, crossings, and scene reliability.
Risk-Aware UAV Return-to-Home
UAV Autonomy
Design a return-to-home planning prototype for UAVs that considers localization confidence, battery constraints, wind risk, and safe landing feasibility.
Real-Time Driving Scene Segmentation
Autonomous Driving Perception
Create a real-time semantic segmentation baseline for driving scenes with explicit reporting of latency, class-wise errors, and safety-relevant failure cases.
Neuromorphic Robot SNN
Neuromorphic Robotics
Prototype a small neuromorphic robotics experiment using spiking neural networks for event-driven perception or reactive control.
Formula 1 Race Simulation
Simulation and Reproducibility
Use race simulation as a clean, explainable environment for modelling strategy, uncertainty, event timing, and reproducible experiments.
Uncertainty-Aware Navigation
Focused Planning Benchmark
Create a focused benchmark for comparing classical shortest-path planning with uncertainty-weighted navigation in controlled map scenarios.
Technical Toolkit
Robotics & Autonomy
- Visual-Inertial Odometry
- SLAM
- Sensor Fusion
- Motion Planning
- ROS 2
- Navigation
AI & Vision
- Python
- PyTorch
- Computer Vision
- Trajectory Prediction
- Uncertainty-Aware Evaluation
- Data Analysis
Research Engineering
- NumPy
- Pandas
- OpenCV
- Matplotlib
- Git
- Linux
- Docker
- Reproducible Experiments
Open Research Repositories
- SHIELD-VIO: Self-Healing Visual-Inertial Odometry- Flagship Robotics Research
- Adaptive Multi-Modal SLAM with Uncertainty-Aware Sensor Fusion- Robust SLAM Research
- DynNav: Uncertainty-Aware Risk-Sensitive Navigation- Risk-Aware Navigation
- SafeCrossAI: Intelligent Intersection Safety- Intelligent Mobility Research
- OpenUWOC-AI: AI for Underwater Optical Wireless Communication- Communication-Constrained Autonomy
- Uncertainty-Aware Navigation- Focused Planning Benchmark
PhD Fit
Interested in PhD opportunities and research collaborations related to robust robotic perception, visual-inertial localization, adaptive SLAM, risk-aware navigation, uncertainty-aware autonomy, UAV systems, and intelligent mobility safety.
Contact