Anagenisis - Ana

ROS 2 C++ / Python Simulation URDF Modeling SLAM / Navigation Computer Vision

Bridging the gap between theory and deployment, this project leverages Gazebo and custom ROS 2 nodes to demonstrate core autonomy concepts. From multi-sensor fusion and SLAM to vision-guided control, the system is architected to translate abstract control theory into high-impact educational content and visual demonstrations.

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Phase I: I Exist

The URDF Foundation & Modular Identity. > Built Ana’s digital twin using a modular URDF architecture. This allows for "hot-swapping" sensor payloads—adding LiDARs, cameras, or IMUs—without breaking the core robot identity, establishing a stable internal structure for future evolution.

Phase II: I See & Feel

Synchronized Sensor Streams. > Integrated the first live vision and inertial pipelines. Ana now perceives her environment through a virtual camera and processes high-frequency IMU data. This stage focused on stable data transport and transforming raw sensor frames into actionable information.

Phase III: I Move

Virtual Mobility & Control Logic. > Launched Ana into a high-fidelity Gazebo environment. Implemented the first movement controllers, allowing Ana to transition from a static observer to an active participant in her world, navigating her first virtual map via manual and programmatic control.

Phase IV: I Recognize

Object Detection & Semantic Awareness. > Implemented OpenCV-based vision pipelines to unlock color and object recognition. Ana can now differentiate between environmental elements, setting the stage for autonomous decision-making and goal-oriented tasks in complex surroundings.

ZSL Autonomous Ships

Embedded Python Visualization ROS2

Design and development of four autonomous model ships used as educational platforms for mechatronics students.

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I. Design & Integration

Led the full hardware lifecycle: from component selection and procurement to assembly and rigorous system testing. Engineered the power distribution and waterproofing for a centralized Linux-based autonomy stack.

II. Industry Showcasing

Represented the project at major international stages, including boot Düsseldorf 2025 and XPONENTIAL Europe. Developed live sensor visualization tools to demonstrate real-time autonomous navigation to industry experts.

IIII. Mentorship & Coaching

Transformed the ships into a stable educational platform for the PuEmP course. Served as a technical coach, guiding students through the complexities of mechanical troubleshooting and ROS 2 software integration.

NOVA Research Vessel

Data Infrastructure Inland Shipping Real-time Monitoring

Built the data infrastructure and sensor suite for an autonomous inland shipping research vessel, focusing on real-time visualization.

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Sensor Suite

Contributed to the physical deployment of the vessel's perception layer, executing the precision installation and cabling of LiDAR, RADAR, and 360° situational awareness cameras. Configured the on-board Linux server and managed sensor-specific software environments to bridge the gap between raw hardware and system-wide compatibility.

Telemetry Dashboard

Engineered the software stack responsible for data acquisition and synchronization. Developed custom ROS 2 packages and launch files to fuse multi-modal data streams, enabling real-time display of vessel telemetry and environment perception on the command bridge.

Maritime Cobot Fusion

Master's Thesis Sensor Fusion Automation

Sensor integration system providing real-time ship pose data for automated liquid cargo handling (Cobotank).

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Pose Estimation

Developing algorithms to track 6-DOF ship movement during cargo transfer in dynamic harbor environments.

Sensor Fusion

Combining IMU data with optical sensors to provide a redundant and highly accurate positioning signal.

Empirical Validation

Developed a dedicated ROS 2 evaluation package to benchmark sensor accuracy against "ground truth" data generated by a Universal Robot (UR). Conducted rigorous performance analysis across diverse edge cases, including camera occlusion and sensor drift, to evaluate the system’s durability and precision in real-world harbor conditions.