513 citations · 2.4k across the 53 of their papers we have counts for
12 papers · 1 filter
Gaussian Radar Transformer for Semantic Segmentation in Noisy Radar Data
Matthias Zeller, Jens Behley, Michael Heidingsfeld +1
Scene understanding is crucial for autonomous robots in dynamic environments for making future state predictions, avoiding collisions, and path planning. Camera and LiDAR perceptio…
Wheel-SLAM: Simultaneous Localization and Terrain Mapping Using One Wheel-mounted IMU
Yibin Wu, Jian Kuang, Xiaoji Niu +3
A reliable pose estimator robust to environmental disturbances is desirable for mobile robots. To this end, inertial measurement units (IMUs) play an important role because they ca…
Fully On-board Low-Power Localization with Multizone Time-of-Flight Sensors on Nano-UAVs
Hanna Müller, Nicky Zimmerman, Tommaso Polonelli +4
Nano-size unmanned aerial vehicles (UAVs) hold enormous potential to perform autonomous operations in complex environments, such as inspection, monitoring or data collection. Moreo…
Long-Term Localization using Semantic Cues in Floor Plan Maps
Nicky Zimmerman, Tiziano Guadagnino, Xieyuanli Chen +2
Lifelong localization in a given map is an essential capability for autonomous service robots. In this paper, we consider the task of long-term localization in a changing indoor en…
Hierarchical Approach for Joint Semantic, Plant Instance, and Leaf Instance Segmentation in the Agricultural Domain
Gianmarco Roggiolani, Matteo Sodano, Tiziano Guadagnino +3
Plant phenotyping is a central task in agriculture, as it describes plants' growth stage, development, and other relevant quantities. Robots can help automate this process by accur…
IR-MCL: Implicit Representation-Based Online Global Localization
Haofei Kuang, Xieyuanli Chen, Tiziano Guadagnino +3
Determining the state of a mobile robot is an essential building block of robot navigation systems. In this paper, we address the problem of estimating the robots pose in an indoor…
Robust Double-Encoder Network for RGB-D Panoptic Segmentation
Matteo Sodano, Federico Magistri, Tiziano Guadagnino +2
Perception is crucial for robots that act in real-world environments, as autonomous systems need to see and understand the world around them to act properly. Panoptic segmentation…
SHINE-Mapping: Large-Scale 3D Mapping Using Sparse Hierarchical Implicit Neural Representations
Xingguang Zhong, Yue Pan, Jens Behley +1
Accurate mapping of large-scale environments is an essential building block of most outdoor autonomous systems. Challenges of traditional mapping methods include the balance betwee…
KISS-ICP: In Defense of Point-to-Point ICP -- Simple, Accurate, and Robust Registration If Done the Right Way
Ignacio Vizzo, Tiziano Guadagnino, Benedikt Mersch +3
Robust and accurate pose estimation of a robotic platform, so-called sensor-based odometry, is an essential part of many robotic applications. While many sensor odometry systems ma…
Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions
Benedikt Mersch, Xieyuanli Chen, Ignacio Vizzo +3
A key challenge for autonomous vehicles is to navigate in unseen dynamic environments. Separating moving objects from static ones is essential for navigation, pose estimation, and…
Robust Onboard Localization in Changing Environments Exploiting Text Spotting
Nicky Zimmerman, Louis Wiesmann, Tiziano Guadagnino +3
Robust localization in a given map is a crucial component of most autonomous robots. In this paper, we address the problem of localizing in an indoor environment that changes and w…
Automatic Labeling to Generate Training Data for Online LiDAR-based Moving Object Segmentation
Xieyuanli Chen, Benedikt Mersch, Lucas Nunes +4
Understanding the scene is key for autonomously navigating vehicles and the ability to segment the surroundings online into moving and non-moving objects is a central ingredient fo…