Self-tuning gains of a quadrotor using a simple model for policy gradient reinforcement learning

Adaptive Path Planning for a Vision-Based quadrotor in an Obstacle Field: Beijing, China

This paper demonstrates a real life approach for quadrotor obstacle avoidance in indoor flight. A color-based vision approach for obstacle detection is used to good effect conjointly with an adaptive path planning algorithm. The presented task is to move about a set indoor space while avoiding randomly located obstacles and adapting a path to...

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

Autonomous Navigation in Partially Observable Environments Using Hierarchical Q-Learning

Flapping-wing MAVs represent an attractive alternative to conventional designs with rotary wings, since they promise a much higher efficiency in forward flight. However, further insight into the flapping-wing aerodynamics is still needed to get closer to the flight performance observed in natural fliers. Here we present the first step necessary...

A Hierarchical Maze Navigation Algorithm with Reinforcement Learning and Mapping

Goal-finding in an unknown maze is a challenging problem for a Reinforcement Learning agent, because the corresponding state space can be large if not intractable, and the agent does not usually have a model of the environment. Hierarchical Reinforcement Learning has been shown in the past to improve tractability and learning time of complex...

Reinforcement Learning based Algorithm with Safety Handling and Risk Perception

Navigation in an unknown or uncertain environment is a challenging task for an autonomous agent. The agent is expected to behave independently and to learn the suitable action to take for a given situation. Reinforcement Learning could be used to help the agent adapt to an unknown environment and learn the right actions to take. This paper...

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

Nonlinear adaptive flight control using incremental approximate dynamic programming and output feedback

Efficient methods for flight envelope estimation through reachability analysis

Graph based dynamic policy for UAV navigation

Safety assessment of unmanned aerial vehicle operations in an integrated airspace

Conflict detection and resolution system architecture for unmanned aerial vehicles in civil airspace

A novel architecture for a general Unmanned Aerial Vehicle (UAV) Conflict Detection and Resolution (CD&R) system, in the context of their integration into the civilian airspace, is proposed in this paper. The architecture consists of layers of safety approaches ,each representing a combination of different methods for surveillance, coordination,...