Machine Learning for Flapping Wing Flight Control

Flight control of Flapping Wing Micro Air Vehicles is challenging, because of their complex dynamics and variability due to manufacturing inconsistencies. Machine Learning algorithms can be used to tackle these challenges. A Policy Gradient algorithm is used to tune the gains of a Proportional-Integral controller using Reinforcement Learning. A...

Flexible Heuristic Dynamic Programming for Reinforcement Learning in Quadrotors

Reinforcement learning is a paradigm for learning decision-making tasks from interaction with the environment. Function approximators solve a part of the curse of dimensionality when learning in high-dimensional state and/or action spaces. It can be a time-consuming process to learn a good policy in a high dimensional state space directly. A...

System Identification using the Multivariate Simplotope B-Spline

In recent research efforts the multivariate simplex spline has shown great promise in system identification applications. It has high approximation power, while its linearity in the parameters allows for computationally efficient estimation of the coefficients. In this paper the multivariate simplotope spline is derived from this spline, and...

Three-dimensional velocity obstacle method for UAV uncoordinated avoidance maneuver

A novel approach with safety metrics for real-time exploration of uncertain environments

Graph based dynamic policy for UAV navigation

Efficient methods for flight envelope estimation through reachability analysis