This is a ROS package for lidar odometry implementation using rotation optimization method.

LIO_SAM for 6-axis IMU and GNSS.

Jobs_Applier_AI_Agent_AIHawk aims to easy job hunt process by automating the job application process. Utilizing artificial intelligence, it enables users to apply for multiple jobs in a tailored way.

Robot-centric elevation mapping for rough terrain navigation

[CoRL 2024] Tag Map: A Text-Based Map for Spatial Reasoning and Navigation with Large Language Models

Elevation Mapping on GPU.

Global and local path planner plugins for ROS move_base which move the robot in 2D (x,y,angle) but avoid collisions using full 3D data (robot meshes and environment octomap).

[ICRA19] Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning

ROS stack with footstep planning and localization for humanoid robots: http://wiki.ros.org/humanoid_navigation

[ICRA2023] Implementation of Visual Language Maps for Robot Navigation

IRON: A Fast Interest Point Descriptor for Robust NDT-Map Matching and Its Application to Robot Localization

Robust and efficient coverage paths for autonomous agricultural vehicles. A modular and extensible Coverage Path Planning library

NMPC, WBC, state estimation, and sim2real framework for legged robots based on OCS2 and ros-controls

OpenMMLab's next-generation platform for general 3D object detection.

Livox open source detection algorithm

GenZ-ICP: SOTA robust LiDAR odometry (IEEE RA-L 2024)

An MPC Motion Planner in ROS/C++

IMU Allan standard deviation charts for use with Kalibr and inertial kalman filters.

Efficient and parallel algorithms for point cloud registration [C++, Python]

A computationally efficient and robust LiDAR-inertial odometry (LIO) package

基于pangolin，提供常规的slam可视化api

Realtime Glass Detection with Laser Rangefinders for Robot Navigation and Mapping

A real-time multifunctional Lidar SLAM package.

[RA-L 2022] An efficient and probabilistic adaptive voxel mapping method for LiDAR odometry

MapEval: Towards Unified, Robust and Efficient SLAM Map Evaluation Framework.

A Modular Framework for LiDAR-based Lifelong Mapping

📍PIN-SLAM: LiDAR SLAM Using a Point-Based Implicit Neural Representation for Achieving Global Map Consistency [TRO' 24]