223 citations · 273 across the 42 of their papers we have counts for
13 papers · 1 filter
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…
Drift-free Visual SLAM using Digital Twins
Roxane Merat, Giovanni Cioffi, Leonard Bauersfeld +1
Globally-consistent localization in urban environments is crucial for autonomous systems such as self-driving vehicles and drones, as well as assistive technologies for visually im…
Student-Informed Teacher Training
Nico Messikommer, Jiaxu Xing, Elie Aljalbout +1
Imitation learning with a privileged teacher has proven effective for learning complex control behaviors from high-dimensional inputs, such as images. In this framework, a teacher…
Residual Policy Learning for Perceptive Quadruped Control Using Differentiable Simulation
Jing Yuan Luo, Yunlong Song, Victor Klemm +3
First-order Policy Gradient (FoPG) algorithms such as Backpropagation through Time and Analytical Policy Gradients leverage local simulation physics to accelerate policy search, si…
Environment as Policy: Learning to Race in Unseen Tracks
Hongze Wang, Jiaxu Xing, Nico Messikommer +1
Reinforcement learning (RL) has achieved outstanding success in complex robot control tasks, such as drone racing, where the RL agents have outperformed human champions in a known…
Learning Quadrotor Control From Visual Features Using Differentiable Simulation
Johannes Heeg, Yunlong Song, Davide Scaramuzza
The sample inefficiency of reinforcement learning (RL) remains a significant challenge in robotics. RL requires large-scale simulation and can still cause long training times, slow…
Structure-Invariant Range-Visual-Inertial Odometry
Ivan Alberico, Jeff Delaune, Giovanni Cioffi +1
The Mars Science Helicopter (MSH) mission aims to deploy the next generation of unmanned helicopters on Mars, targeting landing sites in highly irregular terrain such as Valles Mar…
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.…
MPCC++: Model Predictive Contouring Control for Time-Optimal Flight with Safety Constraints
Maria Krinner, Angel Romero, Leonard Bauersfeld +3
Quadrotor flight is an extremely challenging problem due to the limited control authority encountered at the limit of handling. Model Predictive Contouring Control (MPCC) has emerg…
Learning Quadruped Locomotion Using Differentiable Simulation
Yunlong Song, Sangbae Kim, Davide Scaramuzza
This work explores the potential of using differentiable simulation for learning quadruped locomotion. Differentiable simulation promises fast convergence and stable training by co…
Robotics meets Fluid Dynamics: A Characterization of the Induced Airflow below a Quadrotor as a Turbulent Jet
Leonard Bauersfeld, Koen Muller, Dominic Ziegler +2
The widespread adoption of quadrotors for diverse applications, from agriculture to public safety, necessitates an understanding of the aerodynamic disturbances they create. This p…
Bootstrapping Reinforcement Learning with Imitation for Vision-Based Agile Flight
Jiaxu Xing, Angel Romero, Leonard Bauersfeld +1
Learning visuomotor policies for agile quadrotor flight presents significant difficulties, primarily from inefficient policy exploration caused by high-dimensional visual inputs an…