223 citations · 366 across the 7 of their papers we have counts for
7 papers
Multi-Task Reinforcement Learning for Quadrotors
Jiaxu Xing, Ismail Geles, Yunlong Song +2
Reinforcement learning (RL) has shown great effectiveness in quadrotor control, enabling specialized policies to develop even human-champion-level performance in single-task scenar…
Agile Robotics: Optimal Control, Reinforcement Learning, and Differentiable Simulation
Yunlong Song, Davide Scaramuzza
Control systems are at the core of every real-world robot. They are deployed in an ever-increasing number of applications, ranging from autonomous racing and search-and-rescue miss…
Flymation: Interactive Animation for Flying Robots
Yunlong Song, Davide Scaramuzza
Trajectory visualization and animation play critical roles in robotics research. However, existing data visualization and animation tools often lack flexibility, scalability, and v…
Reaching the Limit in Autonomous Racing: Optimal Control versus Reinforcement Learning
Yunlong Song, Angel Romero, Matthias Mueller +2
A central question in robotics is how to design a control system for an agile mobile robot. This paper studies this question systematically, focusing on a challenging setting: auto…
Agilicious: Open-Source and Open-Hardware Agile Quadrotor for Vision-Based Flight
Philipp Foehn, Elia Kaufmann, Angel Romero +8
Autonomous, agile quadrotor flight raises fundamental challenges for robotics research in terms of perception, planning, learning, and control. A versatile and standardized platfor…
Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The BARN Challenge at ICRA 2022
Xuesu Xiao, Zifan Xu, Zizhao Wang +14
The BARN (Benchmark Autonomous Robot Navigation) Challenge took place at the 2022 IEEE International Conference on Robotics and Automation (ICRA 2022) in Philadelphia, PA. The aim…