Projects

Self-driving algorithm with TD3 for TurtleBot3

Master’s thesis · Universidad de los Andes · 2022 — 2025

Designed and trained a reinforcement-learning policy that drives a TurtleBot3 mobile robot autonomously in the Gazebo simulation environment.

Highlights

  • TD3 (Twin Delayed Deep Deterministic Policy Gradient) for continuous control of the robot’s linear and angular velocities.

  • Integrated ROS2 topics for sensor input (LiDAR, odometry) and actuation.

  • Iterated on reward shaping and observation design to handle obstacle avoidance and goal-reaching in cluttered environments.

  • End-to-end pipeline: simulation setup, training loop, model evaluation, and policy deployment back into Gazebo.

Coming soon

I plan to write up additional projects here — including some of the open work and side experiments around web tooling and AI-assisted development.