78 citations · 133 across the 9 of their papers we have counts for
12 papers
CompSLAM: Complementary Hierarchical Multi-Modal Localization and Mapping for Robot Autonomy in Underground Environments
Shehryar Khattak, Timon Homberger, Lukas Bernreiter +5
Robot autonomy in unknown, GPS-denied, and complex underground environments requires real-time, robust, and accurate onboard pose estimation and mapping for reliable operations. Th…
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…
Resilient Terrain Navigation with a 5 DOF Metal Detector Drone
Patrick Pfreundschuh, Rik Bähnemann, Tim Kazik +3
Micro aerial vehicles (MAVs) hold the potential for performing autonomous and contactless land surveys for the detection of landmines and explosive remnants of war (ERW). Metal det…
Team CERBERUS Wins the DARPA Subterranean Challenge: Technical Overview and Lessons Learned
Marco Tranzatto, Mihir Dharmadhikari, Lukas Bernreiter +33
This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with…
NavDreams: Towards Camera-Only RL Navigation Among Humans
Daniel Dugas, Olov Andersson, Roland Siegwart +1
Autonomously navigating a robot in everyday crowded spaces requires solving complex perception and planning challenges. When using only monocular image sensor data as input, classi…
Fast and Compute-efficient Sampling-based Local Exploration Planning via Distribution Learning
Lukas Schmid, Chao Ni, Yuliang Zhong +2
Exploration is a fundamental problem in robotics. While sampling-based planners have shown high performance, they are oftentimes compute intensive and can exhibit high variance. To…
Real-Time Robotic Search using Hierarchical Spatial Point Processes
Olov Andersson, Per Sidén, Johan Dahlin +2
Aerial robots hold great potential for aiding Search and Rescue (SAR) efforts over large areas. Traditional approaches typically searches an area exhaustively, thereby ignoring tha…