Deep Drone Racing: Learning Agile Flight in Dynamic Environments Elia Kaufmann1∗, Antonio Loquercio1∗, Ren´e Ranftl2 , Alexey Dosovitskiy2 , Vladlen Koltun2 , Davide Scaramuzza1 1 Robotics and Perception Group Depts

First Page		Document Content
Date: 2018-10-09 07:32:05 Robotics Emerging technologies Technology Applied mathematics Computational neuroscience Artificial intelligence Cybernetics Trajectory optimization Unmanned aerial vehicle Quadcopter Artificial neural network Self-driving car		Deep Drone Racing: Learning Agile Flight in Dynamic Environments Elia Kaufmann1∗, Antonio Loquercio1∗, Ren´e Ranftl2 , Alexey Dosovitskiy2 , Vladlen Koltun2 , Davide Scaramuzza1 1 Robotics and Perception Group Depts Add to Reading List Source URL: rpg.ifi.uzh.ch Download Document from Source Website File Size: 2,71 MB Share Document on Facebook

	GODIRECT™ FLIGHT EFFICIENCY Honeywell’s Flight Data Analytics Platform and Trajectory Optimization Tools Honeywell’s GoDirect™ Flight Efficiency offering brings together our flight DocID: 1xW0o - View Document
	Monte Carlo Motion Planning for Robot Trajectory Optimization Under Uncertainty Lucas Janson† , Edward Schmerling† , and Marco Pavone Abstract This article presents a novel approach, named MCMP (Monte Carlo Motion Pl DocID: 1vjBF - View Document
	A tutorial on Newton methods for constrained trajectory optimization and relations to SLAM, Gaussian Process smoothing, optimal control, and probabilistic inference Marc Toussaint March 9, 2017 DocID: 1vh2p - View Document
	2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) Birmingham, UK, November 15-17, 2017 Safe trajectory optimization for whole-body motion of humanoids Valerio Modugno1,2 , Gabriele Nava3 , Dani DocID: 1v7Bj - View Document
	Receding Horizon Trajectory Optimization for Simultaneous Signal Landscape Mapping and Receiver Localization Zaher M. Kassas, Jahshan A. Bhatti, and Todd E. Humphreys The University of Texas at Austin BIOGRAPHIES DocID: 1v3bP - View Document