A modular software architecture for Automatic Plant Phenotyping
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Updated
Nov 21, 2019 - C++
A modular software architecture for Automatic Plant Phenotyping
LIDAR SLAM for Autonomous Vehicles Playground
The Light Imaging Detection and Ranging (LIDAR) is a method for measuring distances (ranging) by illuminating the target with laser light and measuring the reflection with a sensor. The LIDAR Sensor escalates the entire mechanism with great efficiency which is notified with process and main activation codes.
This dataset is captured using a Velodyne VLP-16, which is mounted on an UGV - Clearpath Jackal, on Stevens Institute of Technology campus
Easy description to run and evaluate Lego-LOAM with KITTI-data
Track Advancement of SLAM 跟踪SLAM前沿动态【2021 version】業務調整,暫停更新
Easy description to run and evaluate A-LOAM with KITTI-data
PyTorch reimplementation for "LO-Net: Deep Real-time Lidar Odometry" https://arxiv.org/abs/1904.08242
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.
Self-supervised Deep LiDAR Odometry for Robotic Applications
Official code release for Doppler ICP
A reinforced LiDAR inertial odometry system provides accurate and robust 6-DoF movement estimation under challenging perceptual conditions.
Lidar Ouster OS1-128
LVI-SAM: Tightly-coupled Lidar-Visual-Inertial Odometry via Smoothing and Mapping
CAE-LO: LiDAR Odometry Leveraging Fully Unsupervised Convolutional Auto-Encoder for Interest Point Detection and Feature Description
ICRA 2021 - Robust Place Recognition using an Imaging Lidar
A simple localization framework that can re-localize in built maps based on FAST-LIO.
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