Projects I have worked on at various points in my life.

F1Tenth Racing Benchmarks

A project to benchmark common algorithms for F1Tenth autonomous racing. I implemented trajectory optimisation and tracking, model predictive control, and end-to-end reinforcement learning methods.

PPO in JAX

The proximal policy optimisation algorithm using the JAX framework. I developed this project to learn how the JAX ecosystem can be used for high-performance code.

Deep reinforcement learning algorithm implementations

Personal implementations of the DQN, PPO, DDPG, A2C, SAC and TD3 algorithms in PyTorch. The repo includes a document summarising the algorithms and code components.

Sensor fusion algorithms

Implemenations of the Linear Kalman Filter (LKF), Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF) and Particle Filter (PF)

Tutorial for end-to-end reinforcement learning for autonomous racing

A tutorial style example of how to use end-to-end reinforcement learning (TD3 and SAC algorithms) for F1Tenth autonomous racing.