It sounds like science fiction, but also strangely familiar: drones buzzing around, inspecting tomatoes in greenhouses, delivering your package or inspecting an industrial site. With …
Category: Code
Our work on estimating attitude and angular rate with vision alone has been accepted for publication in Nature Portfolio Journals Robotics! It is part of …
🧠 Bridging the Gap Between Simulation and Reality Training drones to navigate complex environments autonomously is one of the central challenges in robotics. While simulators …
Our work on online, on-board learning of depth from events has been accepted at CVPR 2025. Event cameras provide low-latency perception for only milliwatts of …
We introduce a novel obstacle avoidance pipeline named Memory-Augmented Varying-speed Reinforcement Learning (MAVRL). MAVRL utilizes depth maps, along with the drone and target’s states as …
Our work on fully neuromorphic vision and control for autonomous drone flight has been published in the Science Robotics May 2024 issue. In this work, …
Abstract Insects have long been recognized for their ability to navigate and return home using visual cues from their nest’s environment. However, the precise mechanism …
Federico Paredes-Vallés, Kirk W. Y. Scheper, Christophe De Wagter, Guido C. H. E. de Croon Event cameras have recently gained significant traction …
At ICRA (IEEE International Conference on Robotics and Automation) 2023, MAVLab presented AvoidBench, a high-fidelity vision-based obstacle avoidance benchmarking suite for multi-rotors. Motivation Vision-based obstacle …
Jesse J. Hagenaars*, Federico Paredes-Vallés*, Guido C.H.E. de Croon The field of neuromorphic computing promises extremely low-power and low-latency sensing and processing. …