652 citations · 7k across the 163 of their papers we have counts for
30 papers · 1 filter
Multiple Hypothesis Semantic Mapping for Robust Data Association
Lukas Bernreiter, Abel Gawel, Hannes Sommer +3
In this paper, we present a semantic mapping approach with multiple hypothesis tracking for data association. As semantic information has the potential to overcome ambiguity in mea…
NavRep: Unsupervised Representations for Reinforcement Learning of Robot Navigation in Dynamic Human Environments
Daniel Dugas, Juan Nieto, Roland Siegwart +1
Robot navigation is a task where reinforcement learning approaches are still unable to compete with traditional path planning. State-of-the-art methods differ in small ways, and do…
The Hidden Uncertainty in a Neural Networks Activations
Janis Postels, Hermann Blum, Yannick Strümpler +4
The distribution of a neural network's latent representations has been successfully used to detect out-of-distribution (OOD) data. This work investigates whether this distribution…
Model Predictive Control for Micro Aerial Vehicles: A Survey
Huan Nguyen, Mina Kamel, Kostas Alexis +1
This paper presents a review of the design and application of model predictive control strategies for Micro Aerial Vehicles and specifically multirotor configurations such as quadr…
Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning
Le Chen, Yunke Ao, Florian Tschopp +5
Visual-inertial systems rely on precise calibrations of both camera intrinsics and inter-sensor extrinsics, which typically require manually performing complex motions in front of…
3DSNet: Unsupervised Shape-to-Shape 3D Style Transfer
Mattia Segu, Margarita Grinvald, Roland Siegwart +1
Transferring the style from one image onto another is a popular and widely studied task in computer vision. Yet, style transfer in the 3D setting remains a largely unexplored probl…
Out-of-Distribution Detection for Automotive Perception
Julia Nitsch, Masha Itkina, Ransalu Senanayake +5
Neural networks (NNs) are widely used for object classification in autonomous driving. However, NNs can fail on input data not well represented by the training dataset, known as ou…
LCD -- Line Clustering and Description for Place Recognition
Felix Taubner, Florian Tschopp, Tonci Novkovic +2
Current research on visual place recognition mostly focuses on aggregating local visual features of an image into a single vector representation. Therefore, high-level information…
Freetures: Localization in Signed Distance Function Maps
Alexander Millane, Helen Oleynikova, Christian Lanegger +5
Localization of a robotic system within a previously mapped environment is important for reducing estimation drift and for reusing previously built maps. Existing techniques for ge…
Automatic Extension of a Symbolic Mobile Manipulation Skill Set
Julian Förster, Lionel Ott, Juan Nieto +2
Symbolic planning can provide an intuitive interface for non-expert users to operate autonomous robots by abstracting away much of the low-level programming. However, symbolic plan…
A Unified Approach for Autonomous Volumetric Exploration of Large Scale Environments under Severe Odometry Drift
Lukas Schmid, Victor Reijgwart, Lionel Ott +3
Exploration is a fundamental problem in robot autonomy. A major limitation, however, is that during exploration robots oftentimes have to rely on on-board systems alone for state e…
IDOL: A Framework for IMU-DVS Odometry using Lines
Cedric Le Gentil, Florian Tschopp, Ignacio Alzugaray +3
In this paper, we introduce IDOL, an optimization-based framework for IMU-DVS Odometry using Lines. Event cameras, also called Dynamic Vision Sensors (DVSs), generate highly asynch…
Deep UAV Localization with Reference View Rendering
Timo Hinzmann, Roland Siegwart
This paper presents a framework for the localization of Unmanned Aerial Vehicles (UAVs) in unstructured environments with the help of deep learning. A real-time rendering engine is…
Deep Learning-based Human Detection for UAVs with Optical and Infrared Cameras: System and Experiments
Timo Hinzmann, Tobias Stegemann, Cesar Cadena +1
In this paper, we present our deep learning-based human detection system that uses optical (RGB) and long-wave infrared (LWIR) cameras to detect, track, localize, and re-identify h…
Leveraging Stereo-Camera Data for Real-Time Dynamic Obstacle Detection and Tracking
Thomas Eppenberger, Gianluca Cesari, Marcin Dymczyk +2
Dynamic obstacle avoidance is one crucial component for compliant navigation in crowded environments. In this paper we present a system for accurate and reliable detection and trac…
Learning dynamics for improving control of overactuated flying systems
Weixuan Zhang, Maximilian Brunner, Lionel Ott +3
Overactuated omnidirectional flying vehicles are capable of generating force and torque in any direction, which is important for applications such as contact-based industrial inspe…
Precise Robot Localization in Architectural 3D Plans
Hermann Blum, Julian Stiefel, Cesar Cadena +2
This paper presents a localization system for mobile robots enabling precise localization in inaccurate building models. The approach leverages local referencing to counteract inhe…
Learning Camera Miscalibration Detection
Andrei Cramariuc, Aleksandar Petrov, Rohit Suri +3
Self-diagnosis and self-repair are some of the key challenges in deploying robotic platforms for long-term real-world applications. One of the issues that can occur to a robot is m…
Ascento: A Two-Wheeled Jumping Robot
Victor Klemm, Alessandro Morra, Ciro Salzmann +10
Applications of mobile ground robots demand high speed and agility while navigating in complex indoor environments. These present an ongoing challenge in mobile robotics. A system…
LQR-Assisted Whole-Body Control of a Wheeled Bipedal Robot with Kinematic Loops
Victor Klemm, Alessandro Morra, Lionel Gulich +5
We present a hierarchical whole-body controller leveraging the full rigid body dynamics of the wheeled bipedal robot Ascento. We derive closed-form expressions for the dynamics of…
Voxgraph: Globally Consistent, Volumetric Mapping using Signed Distance Function Submaps
Victor Reijgwart, Alexander Millane, Helen Oleynikova +3
Globally consistent dense maps are a key requirement for long-term robot navigation in complex environments. While previous works have addressed the challenges of dense mapping and…
Go Fetch: Mobile Manipulation in Unstructured Environments
Kenneth Blomqvist, Michel Breyer, Andrei Cramariuc +7
With humankind facing new and increasingly large-scale challenges in the medical and domestic spheres, automation of the service sector carries a tremendous potential for improved…
OneShot Global Localization: Instant LiDAR-Visual Pose Estimation
Sebastian Ratz, Marcin Dymczyk, Roland Siegwart +1
Globally localizing in a given map is a crucial ability for robots to perform a wide range of autonomous navigation tasks. This paper presents OneShot - a global localization algor…
Design and optimal control of a tiltrotor micro aerial vehicle for efficient omnidirectional flight
Mike Allenspach, Karen Bodie, Maximilian Brunner +5
Omnidirectional micro aerial vehicles are a growing field of research, with demonstrated advantages for aerial interaction and uninhibited observation. While systems with complete…