Sample-efficient reinforcement learning for quadcopter flight control

The combination of reinforcement learning and deep neural networks has the potential to train intelligent autonomous agents on high dimensional sensory inputs, with applications in flight control. However, the amount of samples needed by these methods is often too large to use real-world interaction. In this work, mirror-descent guided policy...

Low level quadcopter control using Reinforcement Learning: Developing a self-learning drone

Reinforcement Learning (RL) is a learning paradigm where an agent learns a task by trial and error. The agent needs to explore its environment and by simultaneously receiving rewards it learns what is appropriate behaviour.<br/>Even though it has roots in machine learning, RL is essentially different from other machine learning methods. In...

Obstacle avoidance for quadrotors using reinforcement learning and obstacle-airflow interactions

This research investigates and proposes a new method for obstacle detection and avoidance on quadrotors. One that does not require the addition of any sensors, but relies solely on measurements from the accelerometer and rotor controllers. The detection of obstacles is based on the principle that the airflow around a quadrotor changes when the...

Continuous state and action Q-learning framework applied to quadrotor UAV control

This paper describes an implementation of a reinforcement learning-based framework applied to the control of a multi-copter rotorcraft. The controller is based on continuous state and action Q-learning. The policy is stored using a radial basis function neural network. Distance-based neuron activation is used to optimize the generalization...

Intelligent Controller Selection for Aggressive Quadrotor Manoeuvring: A reinforcement learning approach

A novel intelligent controller selection method for quadrotor attitude and altitude control is presented that maintains performance in different regimes of the flight envelope. Conventional quadrotor controllers can behave insufficiently during aggressive manoeuvring, in extreme angles the quadrotor is unable to maintain height which may result...