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Airborne particle classification in LiDAR point clouds using deep learning
(2021)Springer Proceedings in Advanced Robotics ~ Field and Service RoboticsLiDAR sensors have been very popular in robotics due to their ability to provide accurate range measurements and their robustness to lighting conditions. However, their sensitivity to airborne particles such as dust or fog can lead to perception algorithm failures (e.g., the detection of false obstacles by field robots). In this work, we address this problem by proposing methods to classify airborne particles in LiDAR data. We propose and ...Conference Paper -
Learning Common and Transferable Feature Representations for Multi-Modal Data
(2020)2020 IEEE Intelligent Vehicles Symposium (IV)LiDAR sensors are crucial in automotive perception for accurate object detection. However, LiDAR data is hard to interpret for humans and consequently time-consuming to label. Whereas camera data is easy interpretable and thus, comparably simpler to label. Within this work we present a transductive transfer learning approach to transfer the knowledge for the object detection task from images to point cloud data. We propose a multi-modal ...Conference Paper -
VIZARD: Reliable Visual Localization for Autonomous Vehicles in Urban Outdoor Environments
(2019)2019 IEEE Intelligent Vehicles Symposium (IV)Conference Paper -
Empty Cities: Image Inpainting for a Dynamic-Object-Invariant Space
(2019)2019 International Conference on Robotics and Automation (ICRA)Conference Paper -
Object Classification Based on Unsupervised Learned Multi-Modal Features For Overcoming Sensor Failures
(2019)2019 International Conference on Robotics and Automation (ICRA)Conference Paper -
From coarse to fine: Robust hierarchical localization at large scale
(2019)Proceedings of the 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2019)Conference Paper -
An Approach for Semantic Segmentation of Tree-like Vegetation
(2019)2019 International Conference on Robotics and Automation (ICRA)Conference Paper -
C-blox: A Scalable and Consistent TSDF-based Dense Mapping Approach
(2018)2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)Conference Paper -
A Data-driven Model for Interaction-Aware Pedestrian Motion Prediction in Object Cluttered Environments
(2018)Proceedings of the 2018 IEEE International Conference on Robotics and Automation (ICRA)Conference Paper -
Aerial-Ground collaborative sensing: Third-Person view for teleoperation
(2018)Proceedings of the 2018 International Symposium on Safety, Security, and Rescue Robotics (SSRR)Conference Paper