PRBonn/kiss-icp

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PRBonn/kiss-icp

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A LiDAR odometry pipeline that just works

KISS-ICP

Demo • Install • ROS 1 • ROS 2 • ROS Demo • Paper • Contact Us

KISS-ICP is a LiDAR Odometry pipeline that just works on most of the cases without tunning any parameter.

Install

pip install kiss-icp

Next, follow the instructions on how to run the system by typing:

kiss_icp_pipeline --help

This should print the following help message:

For advanced instructions on the Python pacakge plase see this README

ROS support

ROS 2

git clone https://github.com/PRBonn/kiss-icp && colcon build

ROS 1

cd ~/catkin_ws/ && git clone https://github.com/PRBonn/kiss-icp && catkin build

For more detailed instructions on the ROS wrappers, please visit this README

Citation

If you use this library for any academic work, please cite our original paper.

@article{vizzo2023ral,
  author    = {Vizzo, Ignacio and Guadagnino, Tiziano and Mersch, Benedikt and Wiesmann, Louis and Behley, Jens and Stachniss, Cyrill},
  title     = {{KISS-ICP: In Defense of Point-to-Point ICP -- Simple, Accurate, and Robust Registration If Done the Right Way}},
  journal   = {IEEE Robotics and Automation Letters (RA-L)},
  pages     = {1029--1036},
  doi       = {10.1109/LRA.2023.3236571},
  volume    = {8},
  number    = {2},
  year      = {2023},
  codeurl   = {https://github.com/PRBonn/kiss-icp},
}

Contributing

We envision KISS-ICP as a community-driven project, we love to see how the project is growing thanks to the contributions from the community. We would love to see your face in the list below, just open a Pull Request!

depth_clustering

🚕 Fast and robust clustering of point clouds generated with a Velodyne sensor.

lidar-bonnetal

Semantic and Instance Segmentation of LiDAR point clouds for autonomous driving

semantic_suma

SuMa++: Efficient LiDAR-based Semantic SLAM (Chen et al IROS 2019)

semantic-kitti-api

SemanticKITTI API for visualizing dataset, processing data, and evaluating results.

OverlapNet

OverlapNet - Loop Closing for 3D LiDAR-based SLAM (chen2020rss)

LiDAR-MOS

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

vdbfusion

C++/Python Sparse Volumetric TSDF Fusion

SHINE_mapping

🌟 SHINE-Mapping: Large-Scale 3D Mapping Using Sparse Hierarchical Implicit Neural Representations (ICRA 2023)

puma

Poisson Surface Reconstruction for LiDAR Odometry and Mapping

PIN_SLAM

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

bonnet

Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics.

range-mcl

Range Image-based LiDAR Localization for Autonomous Vehicles Using Mesh Maps (chen2021icra)

overlap_localization

chen2020iros: Learning an Overlap-based Observation Model for 3D LiDAR Localization.

rangenet_lib

Inference module for RangeNet++ (milioto2019iros, chen2019iros)

refusion

ReFusion: 3D Reconstruction in Dynamic Environments for RGB-D Cameras Exploiting Residuals

bonnetal

Bonnet and then some! Deep Learning Framework for various Image Recognition Tasks. Photogrammetry and Robotics Lab, University of Bonn

4DMOS

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

MapClosures

Effectively Detecting Loop Closures using Point Cloud Density Maps

LiDiff

[CVPR'24] Scaling Diffusion Models to Real-World 3D LiDAR Scene Completion

visual-crop-row-navigation

This is a visual-servoing based robot navigation framework tailored for navigating in row-crop fields. It uses the images from two on-board cameras and exploits the regular crop-row structure present in the fields for navigation, without performing explicit localization or mapping. It allows the robot to follow the crop-rows accurately and handles the switch to the next row seamlessly within the same framework.

pole-localization

Online Range Image-based Pole Extractor for Long-term LiDAR Localization in Urban Environments

online_place_recognition

Graph-based image sequences matching for the visual place recognition in changing environments.

agribot

The mission of the project is to build an agricultural robot (AgriBot) from scratch with the aim of serving as a data-recording platform in fields. For further information about the design and purpose of the robot, please follow the About the AgriBot Project page

LocNDF

LocNDF: Neural Distance Field Mapping for Robot Localization

4dNDF

3D LiDAR Mapping in Dynamic Environments using a 4D Implicit Neural Representation (CVPR 2024)

make_it_dense

Make it Dense: Self-Supervised Geometric Scan Completion of Sparse 3D LiDAR Scans in Large Outdoor Environments

point-cloud-prediction

Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks

ir-mcl

IR-MCL: Implicit Representation-Based Online Global Localization https://arxiv.org/abs/2210.03113

MutiverseOdometry

Code for Simple But Effective Redundant Odometry for Autonomous Vehicles

vpr_relocalization

The framework for visual place recognition in changing enviroments. Matches two sequence of images of arbitrary trajectory overlap.

TARL

[CVPR'23] TARL: Temporal Consistent 3D LiDAR Representation Learning for Semantic Perception in Autonomous Driving

lidar-visualizer

A LiDAR visualization tool for all your datasets

deep-point-map-compression

segcontrast

auto-mos

Automatic Labeling to Generate Training Data for Online LiDAR-based Moving Object Segmentation

3DUIS

lidar_transfer

Code for Langer et al. "Domain Transfer for Semantic Segmentation of LiDAR Data using Deep Neural Networks", IROS, 2020.

descriptor-dr

[ICRA 2023] Learning-Based Dimensionality Reduction for Computing Compact and Effective Local Feature Descriptors

hsmcl

SIMP

ContMAV

[CVPR2024] Open-world Semantic Segmentation Including Class Similarity

extrinsic_calibration

Motion Based Multi-Sensor Extrinsic Calibration

vdbfusion_ros

ROS1 Wrapper for VDBFusion https://github.com/PRBonn/vdbfusion

DCPCR

DCPCR: Deep Compressed Point Cloud Registration in Large-Scale Outdoor Environments

HortiMapping

🫑 Panoptic Mapping with Fruit Completion and Pose Estimation for Horticultural Robots (IROS' 23)

fast_change_detection

Fast Image-Based Geometric Change Detection Given a 3D Model

contrastive_association

Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans

retriever

Point Cloud-based Place Recognition in Compressed Map

4d_plant_registration

tmcl

Text Guided MCL

dynamic-point-removal

Static Map Generation from 3D LiDAR Point Clouds Exploiting Ground Segmentation

MaskPLS

Mask-Based Panoptic LiDAR Segmentation for Autonomous Driving, RA-L, 2023

manifold_python

Python bindings for https://github.com/hjwdzh/Manifold

PS-res-excite

kppr

KPPR: Exploiting Momentum Contrast for Point Cloud-Based Place Recognition

goPro-meta

App to sample images from goPro Hero 5 video and syncronize sensor frames to them. Output is yaml file and extracted images.

geometrical_stem_detection

Code for fast and accurate geometrical plant stem detection

PartiallyObservedInverseGames.jl

An inverse game solver for inferring objectives from noise-corrupted partial state observations of non-cooperative multi-agent interactions.

pybonirob

Set of tools to access bonirob datasets in Python

phenobench-baselines

Baselines of the PhenoBench Dataset

voxblox_pybind

Python bindings for the Voxblox library

catkin_tools_fetch

🐕 "fetch" and "update" dependencies of projects in your catkin workspace with a new verb "dependencies" for catkin_tools

nuscenes2kitti

StyleGenForLabels

StyleGAN-based generation of labels for crop-weed segmentation

plants_temporal_matcher

This system can perform 3D point-to-point associations between plants' point clouds acquired in different session even in presence of highly repetitive structures and drastic changes.

ipb_homework_checker

✔️ A generic homework checker that we use to automatically check students homework

leaf_mesher

Precise 3D Reconstruction of Plants from UAV Imagery Combining Bundle Adjustment and Template Matching

HAPT

sigf

Image Matching for Crop Fields Using Similarity Invariant Geometric Feature

DG-CWS

Towards Domain Generalization in Crop and Weed Segmentation for Precision Farming Robots

agri-pretraining

leaf-plant-instance-segmentation

In-Field Phenotyping Based on Crop Leaf and Plant Instance Segmentation

MinkowskiPanoptic

Panoptic segmentation baseline implemented based on the MinkowskiEngine library

Unsupervised-Pre-Training-for-3D-Leaf-Instance-Segmentation

Official repository of Unsupervised Pre-Training for 3D Leaf Instance Segmentation by Roggiolani et al.

vdb_to_numpy

Tool to convert VDB grids to numpy arrays.

Jupyter Notebook

g2o_catkin

:octocat: G2O meets catkin

ipb_workspace

An empty default workspace for development inside IPB lab

plant_pcd_segmenter

High Precision Leaf Instance Segmentation for Phenotyping in Point Clouds Obtained Under Real Field Conditions

cinderella-geometric-animations

Animations of geometric properties relevant to Photogrammetry, Computer Vision and Robotics created with Cinderella