Self-supervised Deep LiDAR Odometry for Robotic Applications
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Updated
Oct 8, 2022 - Python
Self-supervised Deep LiDAR Odometry for Robotic Applications
Official code release for Doppler ICP
CAE-LO: LiDAR Odometry Leveraging Fully Unsupervised Convolutional Auto-Encoder for Interest Point Detection and Feature Description
LiDAR Guide
We provide the code, pretrained models, and scripts to reproduce the experiments of the paper "Towards All-Weather Autonomous Driving". All code was implemented in Python using the deep learning framework PyTorch.
LoRCoN-LO: Long-term Recurrent Convolutional Network-based LiDAR Odometry
Official implementation of the ITSC 2023 paper "LiDAR View Synthesis for Robust Vehicle Navigation Without Expert Labels"
benchmark scripts for LiDAR or LiDAR-inertial odometry research
Lidar Ouster OS1-128
A viewer for visualizing, tracking and mapping data from CARLA simulator.
A 3D Mapping Algorithm that generates PointCloud2 Messages which can be used with OctoMap or Cartographer to visualise 3D Voxels on Rviz/Rviz2
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