1 code implementation • 25 Mar 2024 • Sicong Pan, Liren Jin, Xuying Huang, Cyrill Stachniss, Marija Popović, Maren Bennewitz
Object reconstruction is relevant for many autonomous robotic tasks that require interaction with the environment.
no code implementations • 17 Mar 2024 • Liren Jin, Haofei Kuang, Yue Pan, Cyrill Stachniss, Marija Popović
The key components of our framework are a semantic implicit neural representation and a compatible planning utility function based on semantic rendering and uncertainty estimation, enabling adaptive view planning to target objects of interest.
1 code implementation • 7 Feb 2024 • Apoorva Vashisth, Julius Rückin, Federico Magistri, Cyrill Stachniss, Marija Popović
To address these issues, we propose a novel deep reinforcement learning approach for adaptively replanning robot paths to map targets of interest in unknown 3D environments.
1 code implementation • 7 Dec 2023 • Julius Rückin, Federico Magistri, Cyrill Stachniss, Marija Popović
We propose a planning method for semi-supervised active learning of semantic segmentation that substantially reduces human labelling requirements compared to fully supervised approaches.
1 code implementation • 7 Feb 2023 • Julius Rückin, Federico Magistri, Cyrill Stachniss, Marija Popović
Our framework combines the mapped acquisition function information into the UAV's planning objectives.
no code implementations • 3 Mar 2022 • Felix Stache, Jonas Westheider, Federico Magistri, Cyrill Stachniss, Marija Popović
Efficient data collection methods play a major role in helping us better understand the Earth and its ecosystems.
no code implementations • 28 Sep 2021 • Julius Rückin, Liren Jin, Marija Popović
Aerial robots are increasingly being utilized for environmental monitoring and exploration.
no code implementations • 4 Aug 2021 • Felix Stache, Jonas Westheider, Federico Magistri, Marija Popović, Cyrill Stachniss
In this paper, we address the problem of adaptive path planning for accurate semantic segmentation of terrain using unmanned aerial vehicles (UAVs).