139 citations · 305 across the 20 of their papers we have counts for
21 papers
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…
Adaptive Informative Path Planning Using Deep Reinforcement Learning for UAV-based Active Sensing
Julius Rückin, Liren Jin, Marija Popović
Aerial robots are increasingly being utilized for environmental monitoring and exploration. However, a key challenge is efficiently planning paths to maximize the information value…
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…
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…
Building an Aerial-Ground Robotics System for Precision Farming: An Adaptable Solution
Alberto Pretto, Stéphanie Aravecchia, Wolfram Burgard +25
The application of autonomous robots in agriculture is gaining increasing popularity thanks to the high impact it may have on food security, sustainability, resource use efficiency…
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…
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…
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…
Multi-agent Time-based Decision-making for the Search and Action Problem
Takahiro Miki, Marija Popovic, Abel Gawel +2
Many robotic applications, such as search-and-rescue, require multiple agents to search for and perform actions on targets. However, such missions present several challenges, inclu…
The ETH-MAV Team in the MBZ International Robotics Challenge
Rik Bähnemann, Michael Pantic, Marija Popović +7
This article describes the hardware and software systems of the Micro Aerial Vehicle (MAV) platforms used by the ETH Zurich team in the 2017 Mohamed Bin Zayed International Robotic…
weedNet: Dense Semantic Weed Classification Using Multispectral Images and MAV for Smart Farming
Inkyu Sa, Zetao Chen, Marija Popovic +4
Selective weed treatment is a critical step in autonomous crop management as related to crop health and yield. However, a key challenge is reliable, and accurate weed detection to…
Build Your Own Visual-Inertial Drone: A Cost-Effective and Open-Source Autonomous Drone
Inkyu Sa, Mina Kamel, Michael Burri +5
This paper describes an approach to building a cost-effective and research grade visual-inertial odometry aided vertical taking-off and landing (VTOL) platform. We utilize an off-t…
Multiresolution Mapping and Informative Path Planning for UAV-based Terrain Monitoring
Marija Popovic, Teresa Vidal-Calleja, Gregory Hitz +3
Unmanned aerial vehicles (UAVs) can offer timely and cost-effective delivery of high-quality sensing data. How- ever, deciding when and where to take measurements in complex enviro…
Dynamic System Identification, and Control for a cost effective open-source VTOL MAV
Inkyu Sa, Mina Kamel, Raghav Khanna +3
This paper describes dynamic system identification, and full control of a cost-effective vertical take-off and landing (VTOL) multi-rotor micro-aerial vehicle (MAV) --- DJI Matrice…
Online Informative Path Planning for Active Classification Using UAVs
Marija Popovic, Gregory Hitz, Juan Nieto +3
In this paper, we introduce an informative path planning (IPP) framework for active classification using unmanned aerial vehicles (UAVs). Our algorithm uses a combination of global…
Online Informative Path Planning for Active Classification on UAVs
Marija Popovic, Gregory Hitz, Juan Nieto +2
We propose an informative path planning (IPP) algorithm for active classification using an unmanned aerial vehicle (UAV), focusing on weed detection in precision agriculture. We mo…