652 citations · 4.2k across the 67 of their papers we have counts for
77 papers
maplab 2.0 -- A Modular and Multi-Modal Mapping Framework
Andrei Cramariuc, Lukas Bernreiter, Florian Tschopp +5
Integration of multiple sensor modalities and deep learning into Simultaneous Localization And Mapping (SLAM) systems are areas of significant interest in current research. Multi-m…
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge
Marco Tranzatto, Frank Mascarich, Lukas Bernreiter +38
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems as underground settings present key challenges that can render robot autonomy h…
Superquadric Object Representation for Optimization-based Semantic SLAM
Florian Tschopp, Juan Nieto, Roland Siegwart +1
Introducing semantically meaningful objects to visual Simultaneous Localization And Mapping (SLAM) has the potential to improve both the accuracy and reliability of pose estimates,…
Panoptic Multi-TSDFs: a Flexible Representation for Online Multi-resolution Volumetric Mapping and Long-term Dynamic Scene Consistency
Lukas Schmid, Jeffrey Delmerico, Johannes Schönberger +4
For robotic interaction in environments shared with other agents, access to volumetric and semantic maps of the scene is crucial. However, such environments are inevitably subject…
SemSegMap- 3D Segment-Based Semantic Localization
Andrei Cramariuc, Florian Tschopp, Nikhilesh Alatur +6
Localization is an essential task for mobile autonomous robotic systems that want to use pre-existing maps or create new ones in the context of SLAM. Today, many robotic platforms…
TSDF++: A Multi-Object Formulation for Dynamic Object Tracking and Reconstruction
Margarita Grinvald, Federico Tombari, Roland Siegwart +1
The ability to simultaneously track and reconstruct multiple objects moving in the scene is of the utmost importance for robotic tasks such as autonomous navigation and interaction…
Crowd against the machine: A simulation-based benchmark tool to evaluate and compare robot capabilities to navigate a human crowd
Fabien Grzeskowiak, David Gonon, Daniel Dugas +7
The evaluation of robot capabilities to navigate human crowds is essential to conceive new robots intended to operate in public spaces. This paper initiates the development of a be…
Spherical Multi-Modal Place Recognition for Heterogeneous Sensor Systems
Lukas Bernreiter, Lionel Ott, Juan Nieto +2
In this paper, we propose a robust end-to-end multi-modal pipeline for place recognition where the sensor systems can differ from the map building to the query. Our approach operat…
Mesh Manifold based Riemannian Motion Planning for Omnidirectional Micro Aerial Vehicles
Michael Pantic, Lionel Ott, Cesar Cadena +2
This paper presents a novel on-line path planning method that enables aerial robots to interact with surfaces. We present a solution to the problem of finding trajectories that dri…
Hough2Map -- Iterative Event-based Hough Transform for High-Speed Railway Mapping
Florian Tschopp, Cornelius von Einem, Andrei Cramariuc +5
To cope with the growing demand for transportation on the railway system, accurate, robust, and high-frequency positioning is required to enable a safe and efficient utilization of…
PHASER: a Robust and Correspondence-free Global Pointcloud Registration
Lukas Bernreiter, Lionel Ott, Juan Nieto +2
We propose PHASER, a correspondence-free global registration of sensor-centric pointclouds that is robust to noise, sparsity, and partial overlaps. Our method can seamlessly handle…
Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Clutter
Michel Breyer, Jen Jen Chung, Lionel Ott +2
General robot grasping in clutter requires the ability to synthesize grasps that work for previously unseen objects and that are also robust to physical interactions, such as colli…
Active Model Learning using Informative Trajectories for Improved Closed-Loop Control on Real Robots
Weixuan Zhang, Marco Tognon, Lionel Ott +2
Model-based controllers on real robots require accurate knowledge of the system dynamics to perform optimally. For complex dynamics, first-principles modeling is not sufficiently p…
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…
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…
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…
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…
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…
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…