RPO Navigation Engineer

Ömer Mersin

Visual Navigation & Sensor Fusion for Autonomous Systems

RPO Navigation Engineer at Dawn Aerospace in Delft, Netherlands. I develop navigation systems for rendezvous and proximity operations, building on my background in real-time localization, perception, and autonomous robotics.

Dawn Aerospace Delft, Netherlands In-Space Servicing
C++ Python ROS 2 Sensor Fusion Real-time Systems LiDAR-IMU Fusion
Current Focus: RPO Navigation
Visual Navigation Camera & Radar State Estimation

About Me

Ömer Mersin

2+ Years

Robotics Software Engineering

I design and ship navigation software for autonomous systems operating in demanding environments. My focus is visual navigation, sensor fusion, state estimation, SLAM, and perception pipelines that must run reliably in real time.

At Dawn Aerospace in Delft, I work as an RPO Navigation Engineer on navigation systems for rendezvous and proximity operations. My work spans vision-based navigation, sensor integration, and the architecture that connects navigation sensors to autonomous spacecraft operations. Previously, I developed autonomous drone navigation and operator systems at Dronetools. I also competed in TEKNOFEST Robotaxi for 3 consecutive years with Team Mekatek, helping the team reach 3rd place plus the Best Team Spirit Award.

Robotics Skill Matrix

Core Robotics Engineering

C++ Python ROS 2 Real-time Systems Multithreaded Pipelines Docker

Perception & SLAM

Visual Navigation Relative Pose Estimation LiDAR-Inertial Odometry FAST-LIO Sensor Fusion Camera & Radar Integration OpenCV YOLO-based Detection Video Stabilization & Tracking

Navigation, Control & Deployment

3D ESDF Planning Autonomous Decision-Making MAVLink (PX4/ArduPilot) GStreamer/RTSP CUDA + NVIDIA Jetson WPF/Qt Operator Tools

SLAM & Autonomy Portfolio

Four flagship and award-winning systems that demonstrate end-to-end robotics capability: perception, real-time mapping, planning, controls, and deployable software architecture.

Smart Gimbal Manager Interface
Flagship Project

Smart Gimbal Manager

Professional-grade UAV ground control station (GCS) for real-time gimbal, payload, telemetry, video, and mapping workflows across surveillance, inspection, and emergency operations.

Multi-protocol gimbal control (BaseCam, Viewlink, DJI) with clean abstraction layers
Dual map/video operations with camera footprint projection and terrain intersection tools
Low-latency telemetry + video pipeline with recording, replay, and geospatial export workflows

Platform

Windows WPF desktop app on .NET 6 (C#)

Architecture

MVVM + modular solution structure (40+ projects)

Ops Scope

Gimbal, mapping, video, cloud telemetry, and mission tooling

C# .NET 6 WPF MVVM GMap.NET ArcGIS/Cesium MQTT FFmpeg + OpenCV
Flagship Project

Video Stabilization Engine

Real-time, GPU-accelerated video stabilization and ultra-low-latency RTSP streaming library with seamless passthrough or processing modes, optimized for NVIDIA Jetson edge deployments.

Dual-mode RTSP: zero-processing passthrough or full processing with hot switching
GPU stabilization, roll correction (Canny + Hough), and configurable smoothing modes
DeepStream detection/tracking and Jetson hardware-encoder path for minimum latency

Latency

~10-20 ms passthrough, ~50-100 ms processing mode

Architecture

gstd + gst-interpipe with instant mode switching

Robotics Use

Stabilized FPV/perception streams for drones and robots

C++17 OpenCV CUDA GStreamer + gstd gst-interpipe DeepStream RTSP NVIDIA Jetson
TEKNOFEST Robotaxi Team Mekatek
Award-Winning Project

TEKNOFEST Robotaxi (Team Mekatek)

Autonomous vehicle competition project where our team achieved 3rd place and the Best Team Spirit Award. I contributed to real-time perception and sensor-fusion decision making under track constraints.

Drivable-area detection using image-processing pipelines
Label/sign detection with YOLO for real-time scene understanding
Sensor-fusion based autonomous driving and decision logic
Competed 3 years in a row and improved system robustness each season

Awards

3rd Place + Best Team Spirit Award

Perception

Drivable area + YOLO label detection

Autonomy

Multi-sensor fusion for driving decisions

Autonomous Driving Image Processing YOLO Sensor Fusion Real-time Decision Making

Additional robotics work and experiments are available on GitHub.

Stay Connected

Follow my work in spacecraft navigation, robotics perception, and autonomous systems.

Working on RPO navigation in Delft

I am currently an RPO Navigation Engineer at Dawn Aerospace, working on visual navigation and sensor integration for rendezvous and proximity operations. You can find my projects on GitHub or connect with me on LinkedIn.