513 citations · 2.8k across the 104 of their papers we have counts for
116 papers
Compact Feed-Forward 3D Gaussians via Saliency-Guided Primitive Merging
Tim-Felix Faasch, Tim-Felix Fassch, Jochen Kall +1
3D scene reconstruction, modeling, and rendering are highly relevant for numerous tasks, and 3D Gaussian splatting has become a standard choice in this context. Its feed-forward va…
Robust 6-DoF Object Pose Tracking with Built-In Recovery under Occlusions and Rapid Object Motions
Balázs Opra, Léo Ghafari, Thomas Stewart +1
Real-time 6-DoF object pose tracking is essential for many robotics applications, and several approaches exist. Yet even today's approaches remain unreliable under temporary full o…
Still image and spatial-temporal tomato data enabling detection, segmentation, tracking, and video-instance segmentation using strong and weak labels
Michael Halstead, Esra Guclu, Mohamed Farag +7
In this manuscript we release two datasets for visual sensing of tomato plants grown in commercial-like settings and acquired using a robot. The first is BUTom21 which consists of…
Improving Map Consistency in Graph-Based LiDAR SLAM Through Information-Aware Odometry and Retroactive Loop Closure
Saurabh Gupta, Niklas Trekel, Louis Wiesmann +1
High-quality maps are fundamental for robotics tasks such as navigation and planning. Although modern graph-based LiDAR SLAM systems achieve good trajectory accuracies, a low traje…
TASE: Truncation-Aware Semantic Embeddings for 3D Scene Understanding and Editing
Tim-Felix Faasch, Jochen Kall, Lucas Nunes +2
High-fidelity semantic 3D scene representations are crucial for numerous applications, including robotics, autonomous driving, and simulation. Beyond this, the ability to edit such…
LiPS: Lightweight Panoptic Segmentation for Resource-Constrained Robotics
Calvin Galagain, Martyna Poreba, François Goulette +1
Panoptic segmentation is a key enabler for robotic perception, as it unifies semantic understanding with object-level reasoning. However, the increasing complexity of state-of-the-…
DigiForest: Digital Analytics and Robotics for Sustainable Forestry
Marco Camurri, Enrico Tomelleri, Matías Mattamala +18
Covering one third of Earth's land surface, forests are vital to global biodiversity, climate regulation, and human well-being. In Europe, forests and woodlands reach approximately…
Loop Closure via Maximal Cliques in 3D LiDAR-Based SLAM
Javier Laserna, Saurabh Gupta, Oscar Martinez Mozos +2
Reliable loop closure detection remains a critical challenge in 3D LiDAR-based SLAM, especially under sensor noise, environmental ambiguity, and viewpoint variation conditions. RAN…
SAHA: Supervised Autonomous HArvester for selective forest thinning
Fang Nan, Meher Malladi, Qingqing Li +7
Forestry plays a vital role in our society, creating significant ecological, economic, and recreational value. Efficient forest management involves labor-intensive and complex oper…
Dynamic Visual SLAM using a General 3D Prior
Xingguang Zhong, Liren Jin, Marija Popović +2
Reliable incremental estimation of camera poses and 3D reconstruction is key to enable various applications including robotics, interactive visualization, and augmented reality. Ho…
Register Any Point: Scaling 3D Point Cloud Registration by Flow Matching
Yue Pan, Tao Sun, Liyuan Zhu +4
Point cloud registration aligns multiple unposed point clouds into a common reference frame and is a core step for 3D reconstruction and robot localization without initial guess. I…
Self-Supervised Moving Object Segmentation of Sparse and Noisy Radar Point Clouds
Leon Schwarzer, Matthias Zeller, Daniel Casado Herraez +3
Moving object segmentation is a crucial task for safe and reliable autonomous mobile systems like self-driving cars, improving the reliability and robustness of subsequent tasks li…
A Robust Approach for LiDAR-Inertial Odometry Without Sensor-Specific Modeling
Meher V. R. Malladi, Tiziano Guadagnino, Luca Lobefaro +1
Accurate odometry is a critical component in a robotic navigation stack, and subsequent modules such as planning and control often rely on an estimate of the robot's motion. Sensor…
Coherent Online Road Topology Estimation and Reasoning with Standard-Definition Maps
Khanh Son Pham, Christian Witte, Jens Behley +2
Most autonomous cars rely on the availability of high-definition (HD) maps. Current research aims to address this constraint by directly predicting HD map elements from onboard sen…
Uncertainty-Informed Active Perception for Open Vocabulary Object Goal Navigation
Utkarsh Bajpai, Julius Rückin, Cyrill Stachniss +1
Mobile robots exploring indoor environments increasingly rely on vision-language models to perceive high-level semantic cues in camera images, such as object categories. Such model…
SemRaFiner: Panoptic Segmentation in Sparse and Noisy Radar Point Clouds
Matthias Zeller, Daniel Casado Herraez, Bengisu Ayan +3
Semantic scene understanding, including the perception and classification of moving agents, is essential to enabling safe and robust driving behaviours of autonomous vehicles. Came…
Radar Velocity Transformer: Single-scan Moving Object Segmentation in Noisy Radar Point Clouds
Matthias Zeller, Vardeep S. Sandhu, Benedikt Mersch +3
The awareness about moving objects in the surroundings of a self-driving vehicle is essential for safe and reliable autonomous navigation. The interpretation of LiDAR and camera da…
Radar Tracker: Moving Instance Tracking in Sparse and Noisy Radar Point Clouds
Matthias Zeller, Daniel Casado Herraez, Jens Behley +2
Robots and autonomous vehicles should be aware of what happens in their surroundings. The segmentation and tracking of moving objects are essential for reliable path planning, incl…
Globally Consistent RGB-D SLAM with 2D Gaussian Splatting
Xingguang Zhong, Yue Pan, Liren Jin +3
Recently, 3D Gaussian splatting-based RGB-D SLAM displays remarkable performance of high-fidelity 3D reconstruction. However, the lack of depth rendering consistency and efficient…
DM-OSVP++: One-Shot View Planning Using 3D Diffusion Models for Active RGB-Based Object Reconstruction
Sicong Pan, Liren Jin, Xuying Huang +3
Active object reconstruction is crucial for many robotic applications. A key aspect in these scenarios is generating object-specific view configurations to obtain informative measu…
Doppler-SLAM: Doppler-Aided Radar-Inertial and LiDAR-Inertial Simultaneous Localization and Mapping
Dong Wang, Hannes Haag, Daniel Casado Herraez +3
Simultaneous localization and mapping (SLAM) is a critical capability for autonomous systems. Traditional SLAM approaches, which often rely on visual or LiDAR sensors, face signifi…
Improving Indoor Localization Accuracy by Using an Efficient Implicit Neural Map Representation
Haofei Kuang, Yue Pan, Xingguang Zhong +3
Globally localizing a mobile robot in a known map is often a foundation for enabling robots to navigate and operate autonomously. In indoor environments, traditional Monte Carlo lo…
KISS-SLAM: A Simple, Robust, and Accurate 3D LiDAR SLAM System With Enhanced Generalization Capabilities
Tiziano Guadagnino, Benedikt Mersch, Saurabh Gupta +3
Robust and accurate localization and mapping of an environment using laser scanners, so-called LiDAR SLAM, is essential to many robotic applications. Early 3D LiDAR SLAM methods of…
Keypoint Semantic Integration for Improved Feature Matching in Outdoor Agricultural Environments
Rajitha de Silva, Jonathan Cox, Marija Popovic +3
Robust robot navigation in outdoor environments requires accurate perception systems capable of handling visual challenges such as repetitive structures and changing appearances. V…