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GXU-doudou's starred repositories

Awesome_Dynamic_SLAM

Dynamic SLAM, Life-long SLAM Research(Lidar, Visual, Sensor Fusion etc.)

MIT50100

LiDAR-MOS

(LMNet) Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data (RAL/IROS 2021)

Language:PythonMIT55700

4DMOS

Receding Moving Object Segmentation in 3D LiDAR Data Using Sparse 4D Convolutions (RAL 2022)

Language:PythonMIT25600

robot_localization

robot_localization is a package of nonlinear state estimation nodes. The package was developed by Charles River Analytics, Inc. Please ask questions on answers.ros.org.

Language:C++NOASSERTION130200

removert

Remove then revert (IROS 2020)

Language:C++51500

SWE-agent

SWE-agent takes a GitHub issue and tries to automatically fix it, using GPT-4, or your LM of choice. It solves 12.47% of bugs in the SWE-bench evaluation set and takes just 1 minute to run.

Language:PythonMIT1183500

OpenDevin

🐚 OpenDevin: Code Less, Make More

Language:PythonMIT2813600

ros1_bridge

ROS 2 package that provides bidirectional communication between ROS 1 and ROS 2

Language:C++Apache-2.041900

SensorsCalibration

OpenCalib: A Multi-sensor Calibration Toolbox for Autonomous Driving

Language:C++Apache-2.0217700

LIDAR-based-odometry-using-EKF-and-NDT-matching-algorithm-running-on-GPU

This repository is work at the Embedded Computing Lab at Worcester Polytechnic Institute. A map around WPI is used for localization. NDT algorithm is used for scan matching and finding the pose of the vehicle in the map.

Language:C++1600

AVP-SLAM-PLUS

An implementation of AVP-SLAM and some new contributions

Language:C++AGPL-3.059200

SuperFusion

[ICRA 2024] SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation

Language:PythonGPL-3.028800

bevfusion

[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

Language:PythonApache-2.0211700

MapTR

[ICLR'23 Spotlight] MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction

Language:PythonMIT97400

DBScan-PCL-Optimized

DBScan algorithm using Octrees to cluster 3D points in a space with PCL Library

Language:C++17200

Lane-Marking-Detection

This is the final project for the Geospatial Vision and Visualization class at Northwestern University. The goal of the project is detecting the lane marking for a small LIDAR point cloud. Therefore, we cannot use a Deep Learning algorithm that learns to identify the lane markings by looking at a vast amount of data. Instead we will need to build a system that is able to identify the marking just by looking at the intensity value within the point cloud.

Language:Jupyter Notebook10600