Leonard Bauersfeld | DeepAI

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∙ 09/18/2023

Contrastive Learning for Enhancing Robust Scene Transfer in Vision-based Agile Flight

Scene transfer for vision-based mobile robotics applications is a highly...

0 Jiaxu Xing, et al. ∙

∙ 07/12/2023

Agilicious: Open-Source and Open-Hardware Agile Quadrotor for Vision-Based Flight

Autonomous, agile quadrotor flight raises fundamental challenges for rob...

0 Philipp Foehn, et al. ∙

∙ 06/20/2023

HDVIO: Improving Localization and Disturbance Estimation with Hybrid Dynamics VIO

Visual-inertial odometry (VIO) is the most common approach for estimatin...

0 Giovanni Cioffi, et al. ∙

∙ 01/17/2023

Event-based Shape from Polarization

State-of-the-art solutions for Shape-from-Polarization (SfP) suffer from...

0 Manasi Muglikar, et al. ∙

∙ 01/04/2023

Autonomous Drone Racing: A Survey

Over the last decade, the use of autonomous drone systems for surveying,...

0 Drew Hanover, et al. ∙

∙ 11/22/2022

User-Conditioned Neural Control Policies for Mobile Robotics

Recently, learning-based controllers have been shown to push mobile robo...

0 Leonard Bauersfeld, et al. ∙

∙ 11/14/2022

Cracking Double-Blind Review: Authorship Attribution with Deep Learning

Double-blind peer review is considered a pillar of academic research bec...

0 Leonard Bauersfeld, et al. ∙

∙ 10/27/2022

Learned Inertial Odometry for Autonomous Drone Racing

Inertial odometry is an attractive solution to the problem of state esti...

0 Giovanni Cioffi, et al. ∙

∙ 02/22/2022

A Benchmark Comparison of Learned Control Policies for Agile Quadrotor Flight

Quadrotors are highly nonlinear dynamical systems that require carefully...

0 Elia Kaufmann, et al. ∙

∙ 09/10/2021

Range, Endurance, and Optimal Speed Estimates for Multicopters

Multicopters are among the most versatile mobile robots. Their applicati...

0 Leonard Bauersfeld, et al. ∙

∙ 06/15/2021

NeuroBEM: Hybrid Aerodynamic Quadrotor Model

Quadrotors are extremely agile, so much in fact, that classic first-prin...

0 Leonard Bauersfeld, et al. ∙

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