652 citations · 7k across the 163 of their papers we have counts for
32 papers · 1 filter
An Open-Source System for Vision-Based Micro-Aerial Vehicle Mapping, Planning, and Flight in Cluttered Environments
Helen Oleynikova, Christian Lanegger, Zachary Taylor +4
We present an open-source system for Micro-Aerial Vehicle autonomous navigation from vision-based sensing. Our system focuses on dense mapping, safe local planning, and global traj…
From Coarse to Fine: Robust Hierarchical Localization at Large Scale
Paul-Edouard Sarlin, Cesar Cadena, Roland Siegwart +1
Robust and accurate visual localization is a fundamental capability for numerous applications, such as autonomous driving, mobile robotics, or augmented reality. It remains, howeve…
Towards Efficient Full Pose Omnidirectionality with Overactuated MAVs
Karen Bodie, Zachary Taylor, Mina Kamel +1
Omnidirectional MAVs are a growing field, with demonstrated advantages for aerial interaction and uninhibited observation. While systems with complete pose omnidirectionality and h…
AgriColMap: Aerial-Ground Collaborative 3D Mapping for Precision Farming
Ciro Potena, Raghav Khanna, Juan Nieto +3
The combination of aerial survey capabilities of Unmanned Aerial Vehicles with targeted intervention abilities of agricultural Unmanned Ground Vehicles can significantly improve th…
Redundant Perception and State Estimation for Reliable Autonomous Racing
Nikhil Bharadwaj Gosala, Andreas Bühler, Manish Prajapat +9
In autonomous racing, vehicles operate close to the limits of handling and a sensor failure can have critical consequences. To limit the impact of such failures, this paper present…
Leveraging Deep Visual Descriptors for Hierarchical Efficient Localization
Paul-Edouard Sarlin, Frédéric Debraine, Marcin Dymczyk +2
Many robotics applications require precise pose estimates despite operating in large and changing environments. This can be addressed by visual localization, using a pre-computed 3…
WeedMap: A large-scale semantic weed mapping framework using aerial multispectral imaging and deep neural network for precision farming
Inkyu Sa, Marija Popovic, Raghav Khanna +7
We present a novel weed segmentation and mapping framework that processes multispectral images obtained from an unmanned aerial vehicle (UAV) using a deep neural network (DNN). Mos…
Empty Cities: Image Inpainting for a Dynamic-Object-Invariant Space
Berta Bescos, José Neira, Roland Siegwart +1
In this paper we present an end-to-end deep learning framework to turn images that show dynamic content, such as vehicles or pedestrians, into realistic static frames. This objecti…
An informative path planning framework for UAV-based terrain monitoring
Marija Popovic, Teresa Vidal-Calleja, Gregory Hitz +4
Unmanned Aerial Vehicles (UAVs) represent a new frontier in a wide range of monitoring and research applications. To fully leverage their potential, a key challenge is planning mis…
Map Management for Efficient Long-Term Visual Localization in Outdoor Environments
Mathias Bürki, Marcin Dymczyk, Igor Gilitschenski +3
We present a complete map management process for a visual localization system designed for multi-vehicle long- term operations in resource constrained outdoor environments. Outdoor…
Appearance-Based Landmark Selection for Efficient Long-Term Visual Localization
Mathias Bürki, Igor Gilitschenski, Elena Stumm +2
We present an online landmark selection method for distributed long-term visual localization systems in bandwidth-constrained environments. Sharing a common map for online localiza…
Incremental Object Database: Building 3D Models from Multiple Partial Observations
Fadri Furrer, Tonci Novkovic, Marius Fehr +5
Collecting 3D object datasets involves a large amount of manual work and is time consuming. Getting complete models of objects either requires a 3D scanner that covers all the surf…
Modular Sensor Fusion for Semantic Segmentation
Hermann Blum, Abel Gawel, Roland Siegwart +1
Sensor fusion is a fundamental process in robotic systems as it extends the perceptual range and increases robustness in real-world operations. Current multi-sensor deep learning b…
LandmarkBoost: Efficient Visual Context Classifiers for Robust Localization
Marcin Dymczyk, Igor Gilitschenski, Juan Nieto +3
The growing popularity of autonomous systems creates a need for reliable and efficient metric pose retrieval algorithms. Currently used approaches tend to rely on nearest neighbor…
Aerial-Ground collaborative sensing: Third-Person view for teleoperation
Abel Gawel, Yukai Lin, Théodore Koutros +2
Rapid deployment and operation are key requirements in time critical application, such as Search and Rescue (SaR). Efficiently teleoperated ground robots can support first-responde…
Dynamic Objects Segmentation for Visual Localization in Urban Environments
Guoxiang Zhou, Berta Bescos, Marcin Dymczyk +3
Visual localization and mapping is a crucial capability to address many challenges in mobile robotics. It constitutes a robust, accurate and cost-effective approach for local and g…
An Overview of Perception Methods for Horticultural Robots: From Pollination to Harvest
Ho Seok Ahn, Feras Dayoub, Marija Popovic +3
Horticultural enterprises are becoming more sophisticated as the range of the crops they target expands. Requirements for enhanced efficiency and productivity have driven the deman…
Long-term Large-scale Mapping and Localization Using maplab
Marcin Dymczyk, Marius Fehr, Thomas Schneider +1
This paper discusses a large-scale and long-term mapping and localization scenario using the maplab open-source framework. We present a brief overview of the specific algorithms in…
Reinforced Imitation: Sample Efficient Deep Reinforcement Learning for Map-less Navigation by Leveraging Prior Demonstrations
Mark Pfeiffer, Samarth Shukla, Matteo Turchetta +4
This work presents a case study of a learning-based approach for target driven map-less navigation. The underlying navigation model is an end-to-end neural network which is trained…
Learning 3D Segment Descriptors for Place Recognition
Andrei Cramariuc, Renaud Dubé, Hannes Sommer +2
In the absence of global positioning information, place recognition is a key capability for enabling localization, mapping and navigation in any environment. Most place recognition…
Design of an Autonomous Racecar: Perception, State Estimation and System Integration
Miguel de la Iglesia Valls, Hubertus Franciscus Cornelis Hendrikx, Victor Reijgwart +6
This paper introduces flüela driverless: the first autonomous racecar to win a Formula Student Driverless competition. In this competition, among other challenges, an autonomous ra…
SegMap: 3D Segment Mapping using Data-Driven Descriptors
Renaud Dubé, Andrei Cramariuc, Daniel Dugas +3
When performing localization and mapping, working at the level of structure can be advantageous in terms of robustness to environmental changes and differences in illumination. Thi…
History-aware Autonomous Exploration in Confined Environments using MAVs
Christian Witting, Marius Fehr, Rik Bähnemann +2
Many scenarios require a robot to be able to explore its 3D environment online without human supervision. This is especially relevant for inspection tasks and search and rescue mis…
Visual-Inertial Teach and Repeat for Aerial Inspection
Marius Fehr, Thomas Schneider, Marcin Dymczyk +2
Industrial facilities often require periodic visual inspections of key installations. Examining these points of interest is time consuming, potentially hazardous or require special…