223 citations · 388 across the 14 of their papers we have counts for
10 papers · 1 filter
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…
Demonstrating Agile Flight from Pixels without State Estimation
Ismail Geles, Leonard Bauersfeld, Angel Romero +2
Quadrotors are among the most agile flying robots. Despite recent advances in learning-based control and computer vision, autonomous drones still rely on explicit state estimation.…
AERIAL-CORE: AI-Powered Aerial Robots for Inspection and Maintenance of Electrical Power Infrastructures
Anibal Ollero, Alejandro Suarez, Christos Papaioannidis +27
Large-scale infrastructures are prone to deterioration due to age, environmental influences, and heavy usage. Ensuring their safety through regular inspections and maintenance is c…
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…