Marius Fehr
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Versatile Airborne Ultrasonic NDT Technologies via Active Omni-Sliding with Over-Actuated Aerial Vehicles Open
This paper presents the utilization of advanced methodologies in aerial manipulation to address meaningful industrial applications and develop versatile ultrasonic Non-Destructive Testing (NDT) technologies with aerial robots. The primary …
Modelify: An approach to incrementally build 3D object models for map completion Open
The capabilities of discovering new knowledge and updating the previously acquired one are crucial for deploying autonomous robots in unknown and changing environments. Spatial and objectness concepts are at the basis of several robotic fu…
View article: maplab 2.0 -- A Modular and Multi-Modal Mapping Framework
maplab 2.0 -- A Modular and Multi-Modal Mapping Framework Open
Integration of multiple sensor modalities and deep learning into Simultaneous Localization And Mapping (SLAM) systems are areas of significant interest in current research. Multi-modality is a stepping stone towards achieving robustness in…
View article: CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge Open
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems, as underground settings present key challenges that can render robot autonomy hard to achieve. This problem has motivated the DARPA Subte…
View article: CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge Open
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems, as underground settings present key challenges that can render robot autonomy hard to achieve. This problem has motivated the DARPA Subte…
View article: CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge Open
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems as underground settings present key challenges that can render robot autonomy hard to achieve. This has motivated the DARPA Subterranean C…
View article: 3D3L: Deep Learned 3D Keypoint Detection and Description for LiDARs
3D3L: Deep Learned 3D Keypoint Detection and Description for LiDARs Open
With the advent of powerful, light-weight 3D LiDARs, they have become the hearth of many navigation and SLAM algorithms on various autonomous systems. Pointcloud registration methods working with unstructured pointclouds such as ICP are of…
View article: VersaVIS—an open versatile multi-camera visual-inertial sensor suite
VersaVIS—an open versatile multi-camera visual-inertial sensor suite Open
Robust and accurate pose estimation is crucial for many applications in mobile robotics. Extending visual Simultaneous Localization and Mapping (SLAM) with other modalities such as an inertial measurement unit (IMU) can boost robustness an…
Predicting Unobserved Space for Planning via Depth Map Augmentation Open
Safe and efficient path planning is crucial for autonomous mobile robots. A prerequisite for path planning is to have a comprehensive understanding of the 3D structure of the robot's environment. On MAVs this is commonly achieved using low…
History-Aware Autonomous Exploration in Confined Environments Using MAVs Open
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 missions. To solve this high-dimensional path planning problem…
ACCURATE VISUAL LOCALIZATION IN OUTDOOR AND INDOOR ENVIRONMENTS EXPLOITING 3D IMAGE SPACES AS SPATIAL REFERENCE Open
In this paper, we present a method for visual localization and pose estimation based on 3D image spaces. The method works in indoor and outdoor environments and does not require the presence of control points or markers. The method is eval…
Incremental Object Database: Building 3D Models from Multiple Partial Observations Open
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 surfaces of an object or one needs to rotate it to completely o…
Long-term Large-scale Mapping and Localization Using maplab Open
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 the system that enable building a consistent map from mult…
Visual-Inertial Teach and Repeat for Aerial Inspection Open
Industrial facilities often require periodic visual inspections of key installations. Examining these points of interest is time consuming, potentially hazardous or require special equipment to reach. MAVs are ideal platforms to automate t…
Topomap: Topological Mapping and Navigation Based on Visual SLAM Maps Open
Visual robot navigation within large-scale, semi-structured environments deals with various challenges such as computation intensive path planning algorithms or insufficient knowledge about traversable spaces. Moreover, many state-of-the-a…
Visual-Inertial Teach and Repeat for Aerial Inspection Open
Industrial facilities often require periodic visual inspections of key installations. Examining these points of interest is time consuming, potentially hazardous or require special equipment to reach. MAVs are ideal platforms to automate t…
Maplab: An Open Framework for Research in Visual-Inertial Mapping and Localization Open
Robust and accurate visual-inertial estimation is crucial to many of today's challenges in robotics. Being able to localize against a prior map and obtain accurate and driftfree pose estimates can push the applicability of such systems eve…
Incremental Object Database: Building 3D Models from Multiple Partial Observations Open
Collecting 3D object data sets 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 surfaces of an object or one needs to rotate it to completely …
TSDF-based change detection for consistent long-term dense reconstruction and dynamic object discovery Open
Robots that are operating for extended periods of time need to be able to deal with changes in their environment and represent them adequately in their maps. In this paper, we present a novel 3D reconstruction algorithm based on an extende…
Voxblox: Building 3D Signed Distance Fields for Planning Open
Truncated Signed Distance Fields (TSDFs) have become a popular tool in 3D reconstruction, as they allow building very high-resolution models of the environment in real-time on GPU. However, they have rarely been used for planning on roboti…