activity
20182022
most citedSuMa++: Efficient LiDAR-based Semantic SLAM

501 citations · 932 across the 9 of their papers we have counts for

collaborators

17 papers

cs.CV202239 cited

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…

cs.RO2022

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…

eess.SP20222 cited

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…

cs.RO2022

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…

cs.RO2022104 cited

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…

cs.CV202113 cited

Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks

Benedikt Mersch, Xieyuanli Chen, Jens Behley +1

Exploiting past 3D LiDAR scans to predict future point clouds is a promising method for autonomous mobile systems to realize foresighted state estimation, collision avoidance, and…