138 citations · 367 across the 16 of their papers we have counts for
9 papers · 1 filter
FindAnything: Open-Vocabulary and Object-Centric Mapping for Robot Exploration in Any Environment
Sebastián Barbas Laina, Simon Boche, Sotiris Papatheodorou +4
Geometrically accurate and semantically expressive map representations have proven invaluable for robot deployment and task planning in unknown environments. Nevertheless, real-tim…
Efficient Submap-based Autonomous MAV Exploration using Visual-Inertial SLAM Configurable for LiDARs or Depth Cameras
Sotiris Papatheodorou, Simon Boche, Sebastián Barbas Laina +1
Autonomous exploration of unknown space is an essential component for the deployment of mobile robots in the real world. Safe navigation is crucial for all robotics applications an…
Control-Barrier-Aided Teleoperation with Visual-Inertial SLAM for Safe MAV Navigation in Complex Environments
Siqi Zhou, Sotiris Papatheodorou, Stefan Leutenegger +1
In this paper, we consider a Micro Aerial Vehicle (MAV) system teleoperated by a non-expert and introduce a perceptive safety filter that leverages Control Barrier Functions (CBFs)…
Scalable Outdoors Autonomous Drone Flight with Visual-Inertial SLAM and Dense Submaps Built without LiDAR
Sebastián Barbas Laina, Simon Boche, Sotiris Papatheodorou +4
Autonomous navigation is needed for several robotics applications. In this paper we present an autonomous Micro Aerial Vehicle (MAV) system which purely relies on cost-effective an…
Finding Things in the Unknown: Semantic Object-Centric Exploration with an MAV
Sotiris Papatheodorou, Nils Funk, Dimos Tzoumanikas +3
Exploration of unknown space with an autonomous mobile robot is a well-studied problem. In this work we broaden the scope of exploration, moving beyond the pure geometric goal of u…
Volumetric Occupancy Mapping With Probabilistic Depth Completion for Robotic Navigation
Marija Popovic, Florian Thomas, Sotiris Papatheodorou +3
In robotic applications, a key requirement for safe and efficient motion planning is the ability to map obstacle-free space in unknown, cluttered 3D environments. However, commodit…
Elastic and Efficient LiDAR Reconstruction for Large-Scale Exploration Tasks
Yiduo Wang, Nils Funk, Milad Ramezani +5
We present an efficient, elastic 3D LiDAR reconstruction framework which can reconstruct up to maximum LiDAR ranges (60 m) at multiple frames per second, thus enabling robot explor…
Multi-Resolution 3D Mapping with Explicit Free Space Representation for Fast and Accurate Mobile Robot Motion Planning
Nils Funk, Juan Tarrio, Sotiris Papatheodorou +3
With the aim of bridging the gap between high quality reconstruction and mobile robot motion planning, we propose an efficient system that leverages the concept of adaptive-resolut…
Fast Frontier-based Information-driven Autonomous Exploration with an MAV
Anna Dai, Sotiris Papatheodorou, Nils Funk +2
Exploration and collision-free navigation through an unknown environment is a fundamental task for autonomous robots. In this paper, a novel exploration strategy for Micro Aerial V…