PDF-An Application of Reinforcement Learning to Aerobatic Helicopter Flight Pieter Abbeel PDF document

Ng Computer Science Dept Stanford University Stanford CA 94305 Abstract Autonomous helicopter 64258ight is widely regarded to be a highl y challenging control problem

Upload by lindy-dunigan
Published on 2014-12-16

Presentation Embed Code

<iframe width="560" height="315" src="https://www.docslides.com/embed/24727" frameborder="0" allowfullscreen></iframe>

Download Presentation

Download Presentation The PPT/PDF document "An Application of Reinforcement Learning..." is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.

An Application of Reinforcement Learning to Aerobatic Helicopter Flight Pieter Abbeel: Transcript

PDF-An Application of Reinforcement Learning to Aerobatic Helicopter Flight Pieter Abbeel PDF document

Presentation Embed Code

Download Presentation

An Application of Reinforcement Learning to Aerobatic Helicopter Flight Pieter Abbeel: Transcript

Related Contents

Autonomous inverted helicopter ight via reinforcement learning Andrew Y

Machine Learning Techniques For Autonomous Aerobatic Helic

Learning for Control from Multiple Demonstrations Adam

Discriminati raining of Kalman Filters Pieter Abbeel Adam Coates Michael Montemerlo Andre

A Lowcost Compliant DOF Robotic Manipulator Morgan Quigley Alan Asbeck and Andrew Y

Apprenticeship Learning for Robotic Control, with Applicati

Text Detection and Character Recognition in Scene Images with Unsupervised Feature Learning

Enabling Blockchain Innovations with Pegged Sidechains Adam Back Matt Corallo Luke Dashjr

Reinforcement Learning Reinforcement Learning: An Introduction

FLIGHT TEST STANDARDS GUIDE AEROBATIC FLIGHT RATING AE

LQGMP Optimized Path Planning for Robots with Motion Uncertainty and Imperfect State Information

mponent of European Helicopter Safety Team Advantages of Simulators FSTDs inHelicopter

Deep Reinforcement Learning

Akroutsjekk