Reinforcement Learning for Orientation Estimation Using Inertial Sensors with Performance Guarantee

This paper presents a deep reinforcement learning (DRL) algorithm for orientation estimation using inertial sensors combined with a magnetometer. Lyapunov’s method in control theory is employed to prove the convergence of orientation estimation errors. The estimator gains and a Lyapunov function are parametrised by deep neural networks and...

Hopcount in the NICE Application Layer Multicast Protocol