4 citations · 10 across the 5 of their papers we have counts for
10 papers · 1 filter
Local Path Planning and Obstacle Avoidance for an Omnicopter Platform
Mikolaj Helinski, Spilios Theodoulis, Mahmoud Hamandi +3
Autonomous unmanned aerial vehicles (UAVs) increasingly operate in cluttered environments where global planners such as RRT* are not directly deployable at control rates. This pape…
Aerial Manipulation Using Hybrid Force and Position NMPC Applied to Aerial Writing
Dimos Tzoumanikas, Felix Graule, Qingyue Yan +3
Aerial manipulation aims at combining the manoeuvrability of aerial vehicles with the manipulation capabilities of robotic arms. This, however, comes at the cost of the additional…
Active Learning for UAV-based Semantic Mapping
Hermann Blum, Silvan Rohrbach, Marija Popovic +2
Unmanned aerial vehicles combined with computer vision systems, such as convolutional neural networks, offer a flexible and affordable solution for terrain monitoring, mapping, and…
Obstacle-aware Adaptive Informative Path Planning for UAV-based Target Search
Ajith Anil Meera, Marija Popovic, Alexander Millane +1
Target search with unmanned aerial vehicles (UAVs) is relevant problem to many scenarios, e.g., search and rescue (SaR). However, a key challenge is planning paths for maximal sear…
Informative Path Planning for Active Field Mapping under Localization Uncertainty
Marija Popovic, Teresa Vidal-Calleja, Jen Jen Chung +2
Information gathering algorithms play a key role in unlocking the potential of robots for efficient data collection in a wide range of applications. However, most existing strategi…
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…