513 citations · 2.8k across the 104 of their papers we have counts for
13 papers · 1 filter
Data-Centric Digital Agriculture: A Perspective
Ribana Roscher, Lukas Roth, Cyrill Stachniss +1
In response to the increasing global demand for food, feed, fiber, and fuel, digital agriculture is rapidly evolving to meet these demands while reducing environmental impact. This…
BonnBeetClouds3D: A Dataset Towards Point Cloud-based Organ-level Phenotyping of Sugar Beet Plants under Field Conditions
Elias Marks, Jonas Bömer, Federico Magistri +3
Agricultural production is facing severe challenges in the next decades induced by climate change and the need for sustainability, reducing its impact on the environment. Advanceme…
LIO-EKF: High Frequency LiDAR-Inertial Odometry using Extended Kalman Filters
Yibin Wu, Tiziano Guadagnino, Louis Wiesmann +3
Odometry estimation is crucial for every autonomous system requiring navigation in an unknown environment. In modern mobile robots, 3D LiDAR-inertial systems are often used for thi…
Radar Instance Transformer: Reliable Moving Instance Segmentation in Sparse Radar Point Clouds
Matthias Zeller, Vardeep S. Sandhu, Benedikt Mersch +3
The perception of moving objects is crucial for autonomous robots performing collision avoidance in dynamic environments. LiDARs and cameras tremendously enhance scene interpretati…
PAg-NeRF: Towards fast and efficient end-to-end panoptic 3D representations for agricultural robotics
Claus Smitt, Michael Halstead, Patrick Zimmer +4
Precise scene understanding is key for most robot monitoring and intervention tasks in agriculture. In this work we present PAg-NeRF which is a novel NeRF-based system that enables…
Building Volumetric Beliefs for Dynamic Environments Exploiting Map-Based Moving Object Segmentation
Benedikt Mersch, Tiziano Guadagnino, Xieyuanli Chen +3
Mobile robots that navigate in unknown environments need to be constantly aware of the dynamic objects in their surroundings for mapping, localization, and planning. It is key to r…
PhenoBench -- A Large Dataset and Benchmarks for Semantic Image Interpretation in the Agricultural Domain
Jan Weyler, Federico Magistri, Elias Marks +6
The production of food, feed, fiber, and fuel is a key task of agriculture, which has to cope with many challenges in the upcoming decades, e.g., a higher demand, climate change, l…
On Domain-Specific Pre-Training for Effective Semantic Perception in Agricultural Robotics
Gianmarco Roggiolani, Federico Magistri, Tiziano Guadagnino +4
Agricultural robots have the prospect to enable more efficient and sustainable agricultural production of food, feed, and fiber. Perception of crops and weeds is a central componen…
Constructing Metric-Semantic Maps using Floor Plan Priors for Long-Term Indoor Localization
Nicky Zimmerman, Matteo Sodano, Elias Marks +2
Object-based maps are relevant for scene understanding since they integrate geometric and semantic information of the environment, allowing autonomous robots to robustly localize a…
Panoptic Mapping with Fruit Completion and Pose Estimation for Horticultural Robots
Yue Pan, Federico Magistri, Thomas Läbe +5
Monitoring plants and fruits at high resolution play a key role in the future of agriculture. Accurate 3D information can pave the way to a diverse number of robotic applications i…
A Survey on Global LiDAR Localization: Challenges, Advances and Open Problems
Huan Yin, Xuecheng Xu, Sha Lu +5
Knowledge about the own pose is key for all mobile robot applications. Thus pose estimation is part of the core functionalities of mobile robots. Over the last two decades, LiDAR s…
An Informative Path Planning Framework for Active Learning in UAV-based Semantic Mapping
Julius Rückin, Federico Magistri, Cyrill Stachniss +1
Unmanned aerial vehicles (UAVs) are frequently used for aerial mapping and general monitoring tasks. Recent progress in deep learning enabled automated semantic segmentation of ima…
Online and Offline Learning of Player Objectives from Partial Observations in Dynamic Games
Lasse Peters, Vicenç Rubies-Royo, Claire J. Tomlin +4
Robots deployed to the real world must be able to interact with other agents in their environment. Dynamic game theory provides a powerful mathematical framework for modeling scena…