78 citations · 133 across the 9 of their papers we have counts for
6 papers · 1 filter
Learning to Fly Omnidirectional Micro Aerial Vehicles with an End-To-End Control Network
Eugenio Cuniato, Olov Andersson, Helen Oleynikova +2
Overactuated tilt-rotor platforms offer many advantages over traditional fixed-arm drones, allowing the decoupling of the applied force from the attitude of the robot. This expands…
COIN-LIO: Complementary Intensity-Augmented LiDAR Inertial Odometry
Patrick Pfreundschuh, Helen Oleynikova, Cesar Cadena +2
We present COIN-LIO, a LiDAR Inertial Odometry pipeline that tightly couples information from LiDAR intensity with geometry-based point cloud registration. The focus of our work is…
Learning to Open Doors with an Aerial Manipulator
Eugenio Cuniato, Ismail Geles, Weixuan Zhang +3
The field of aerial manipulation has seen rapid advances, transitioning from push-and-slide tasks to interaction with articulated objects. So far, when more complex actions are per…
Dynablox: Real-time Detection of Diverse Dynamic Objects in Complex Environments
Lukas Schmid, Olov Andersson, Aurelio Sulser +2
Real-time detection of moving objects is an essential capability for robots acting autonomously in dynamic environments. We thus propose Dynablox, a novel online mapping-based appr…
Material-agnostic Shaping of Granular Materials with Optimal Transport
Nikhilesh Alatur, Olov Andersson, Roland Siegwart +1
From construction materials, such as sand or asphalt, to kitchen ingredients, like rice, sugar, or salt; the world is full of granular materials. Despite impressive progress in rob…
Obstacle avoidance using raycasting and Riemannian Motion Policies at kHz rates for MAVs
Michael Pantic, Isar Meijer, Rik Bähnemann +5
In this paper, we present a novel method for using Riemannian Motion Policies on volumetric maps, shown in the example of obstacle avoidance for Micro Aerial Vehicles (MAVs). While…