A Modular Optimization framework for Localization and mApping (MOLA)
- slam
- lidar
- lidar-point-cloud
- localization
47,133 repositories indexed
25–48 of 61 · Most stars
A Modular Optimization framework for Localization and mApping (MOLA)
Interactive Map Correction for 3D Graph SLAM
C++ implementation to Detect, track and classify multiple objects using LIDAR scans or point cloud
Point cloud registration pipeline for robot localization and 3D perception
Multi-threaded and SSE friendly NDT algorithm
A C++, header-only library for constructing JSON and JSON-like data formats, with JSON Pointer, JSON Patch, JSON Schema, JSONPath, JMESPath, CSV, MessagePack, CBOR, BSON, UBJSON, toon-format
Polygonal Surface Reconstruction from Point Clouds (C++ & Python)
Ground Segmentation from Lidar Point Clouds
Detect 6-DOF grasp poses in point clouds
My awesome point cloud labeling tool
A Compositional Numeric Library for C++
C++ header-only JSON library
LiDAR point cloud ground filtering / segmentation (bare earth extraction) method based on cloth simulation
The Point Processing Toolkit (pptk) is a Python package for visualizing and processing 2-d/3-d point clouds.
Converts a 3D Point Cloud into a 2D laser scan.
A ROS node to perform a probabilistic 3-D/6-DOF localization system for mobile robots with 3-D LIDAR(s). It implements pointcloud based Monte Carlo localization that uses a reference pointcloud as a map.
Entwine - point cloud organization for massive datasets
An unordered C++ data container providing fast iteration/insertion/erasure while maintaining pointer/iterator validity to non-erased elements regardless of insertions/erasures. Provides higher-performance than std:: library containers for high-modification scenarios with unordered data.
Implementation of the Go-ICP algorithm for globally optimal 3D pointset registration
Large collection of number systems providing custom arithmetic for mixed-precision algorithm development and optimization for AI, Machine Learning, Computer Vision, Signal Processing, CAE, EDA, control, optimization, estimation, and approximation.
The fastest automatic differentiation library for C++, with Python bindings. Forward, adjoint and higher-order derivatives, checkpointing, Eigen support and JIT. Reproducible benchmarks against CppAD, Adept and autodiff.
This repository contains a subset of pointers to solutions with editorials and notes to my trainees (ACM ICPC, OJs, IOI, POI, CEOI, JOI, etc). For IOI/OI, I organized what I found on the web from official solutions and materials.
Real-time LIDAR-based Urban Road and Sidewalk detection for Autonomous Vehicles 🚗
Use LiDAR to map the static world