activity
20202026
most citedRLtools: A Fast, Portable Deep Reinforcement Learning Library for Continuous Control

3 citations · 5 across the 5 of their papers we have counts for

collaborators

7 papers

cs.RO2026

HyperDrone: Simulation-to-Reality Transfer at Millions of Frames per Second

Jonas Eschmann, Giuseppe Loianno

We present HyperDrone, an extremely fast quadrotor simulator focused on high-performance batch rendering that is more than 20x faster than existing state-of-the-art batch quadrotor…

cs.RO2026★ 2 cited

HoLoArm: Deformable Arms for Collision-Tolerant Quadrotor Flight

Quang Ngoc Pham, Jonas Eschmann, Yang Zhou +3

The increasing use of drones in human-centric applications highlights the need for designs that can survive collisions and recover rapidly, minimizing risks to both humans and the…

cs.RO2025

RAPTOR: A Foundation Policy for Quadrotor Control

Jonas Eschmann, Dario Albani, Giuseppe Loianno

Humans are remarkably data-efficient when adapting to new unseen conditions, like driving a new car. In contrast, modern robotic control systems, like neural network policies train…

cs.RO2024

Data-Driven System Identification of Quadrotors Subject to Motor Delays

Jonas Eschmann, Dario Albani, Giuseppe Loianno

Recently non-linear control methods like Model Predictive Control (MPC) and Reinforcement Learning (RL) have attracted increased interest in the quadrotor control community. In con…

cs.RO2023

Learning to Fly in Seconds

Jonas Eschmann, Dario Albani, Giuseppe Loianno

Learning-based methods, particularly Reinforcement Learning (RL), hold great promise for streamlining deployment, enhancing performance, and achieving generalization in the control…

cs.LG2023★ 3 cited

RLtools: A Fast, Portable Deep Reinforcement Learning Library for Continuous Control

Jonas Eschmann, Dario Albani, Giuseppe Loianno

Deep Reinforcement Learning (RL) can yield capable agents and control policies in several domains but is commonly plagued by prohibitively long training times. Additionally, in the…

cs.RO2020

Underactuated Waypoint Trajectory Optimization for Light Painting Photography

Christian Eilers, Jonas Eschmann, Robin Menzenbach +3

Despite their abundance in robotics and nature, underactuated systems remain a challenge for control engineering. Trajectory optimization provides a generally applicable solution,…