Systems and robotics engineer focused on autonomous and safety-critical real-time software.
Experience with ROS 2–based robotic systems, multi-robot platforms, autonomous vehicles, and UAV simulation, as well as reinforcement learning and control algorithms. Background in safety-critical and deterministic systems (RTOS kernel development, and DO-178C–aligned practices), along with low-level C/C++ development and FPGA design using Verilog.
Frontier-based exploration for multiple autonomous robots in ROS 2. Implemented collaborative goal allocation with integrated path planning and trajectory tracking.
Real-World Validation & Mentions:
- US R&D Implementation: Evaluated and integrated by the US Engineering Research and Development Center (ERDC) in their official technical report (ERDC TR-25-10). The package was selected for its efficient Depth-First Search (DFS) algorithm to govern autonomous decision-making, successfully guiding a physical robot to autonomously map indoor environments and generate 3D point clouds.
- Academic Research: Featured as a core implementation in a Master's thesis at Politecnico di Torino (Italy), focusing on collaborative autonomous exploration methodologies (Read Thesis).
End-to-end navigation for 12-DoF quadruped robots using deep reinforcement learning. Trained with SAC in a physics-based Unity simulation, including reward, action, and observation space design for stable and energy-efficient locomotion.
Perception, planning, and control algorithms for autonomous driving and robotics. Includes vision-based recognition, Pure Pursuit tracking, and a modified A* path planning approach.
Project demos and technical details:
| Domain | Technologies |
|---|---|
| Real-Time & Safety-Critical Systems | RTOS kernel development, partitioned systems, deterministic scheduling, real-time constraints, DO-178C–aligned development practices |
| Low-Level & Embedded | C / C++ (system-level and embedded), kernel and RTOS-oriented development, FPGA design with Verilog |
| Robotics & Autonomous Systems | ROS 2, multi-robot systems, autonomous navigation, UAV and ground vehicle simulation (Unity, Gazebo, Webots), path planning, mapping, control, decision-making |
| AI & Learning | Deep Reinforcement Learning (SAC), neural network–based control and perception |
| Systems & Tooling | Linux, Git, Docker |
