Deep Reinforcement Learning for Goal-directed Visual Navigation

Safe navigation in a cluttered environment is a key capability for the autonomous operation of Micro Aerial Vehicles (MAVs). This work explores a (deep) Reinforcement Learning (RL) based approach for monocular vision based obstacle avoidance and goal directed navigation for MAVs in cluttered environments. We investigated this problem in the...

Strategic Conformal Automation for Air Traffic Control: A Machine Learning Approach

Acceptance of automation has been a bottleneck for successful introduction of automation in Air Traffic Control. Strategic conformal automation has been proven to increase automation acceptance, by creating a better match between automation and operator decision-making. In this paper strategic conformal automation for Air Traffic Control is...

Tabular Reinforcement Learning Aided by Generalisation Methods

Reinforcement learning is a machine learning paradigm that deals with optimisation and learns by interacting with its environment. Tabular reinforcement learning methods are popular because of their relative simplicity combined with good guarantees of finding an optimal solution. The downside is that they suffer from an exponentially growing...