Code for a real-time distributed cooperative slam(RDC-SLAM) system for ROS compatible platforms.

Related tags

Deep LearningRDC_SLAM
Overview

RDC-SLAM

This repository contains code for a real-time distributed cooperative slam(RDC-SLAM) system for ROS compatible platforms. The system takes in point cloud from 3d Lidar as inputs. A demonstration of the system can be found here -> https://www.youtube.com/watch?v=FvHQ3VcNWTI demo

The system

RDC-SLAM is an online cooperative SLAM system, which consists of three steps to establish a global map by distributively leveraging existing SLAM techniques. First, similar places are recognized as bridges between each robot. Next, the relative pose estimation is computed through the recognized relative places. Finally, a distributed graph optimization approach is used to merge the local maps generated by all robots. framework

Dependency

  • ROS(tested with kinetic and melodic)
  • gtsam(Georgia Tech Smoothing and Mapping library, 4.0.0-alpha2)
wget -O ~/Downloads/gtsam.zip https://github.com/borglab/gtsam/archive/4.0.0-alpha2.zip
cd ~/Downloads/ && unzip gtsam.zip -d ~/Downloads/
cd ~/Downloads/gtsam-4.0.0-alpha2/
mkdir build && cd build
cmake ..
sudo make install
  • libnabo
git clone git://github.com/ethz-asl/libnabo.git
mkdir build && cd build
cmake ..
sudo make install

Compile

catkin_make -j8

Run the package

  • setup the local network

  • run the launch file on each device

The datasets

Sync2Gen Code for ICCV 2021 paper: Scene Synthesis via Uncertainty-Driven Attribute Synchronization

Sync2Gen Code for ICCV 2021 paper: Scene Synthesis via Uncertainty-Driven Attribute Synchronization 0. Environment Environment: python 3.6 and cuda 10

Haitao Yang 62 Dec 30, 2022
CLIP (Contrastive Language–Image Pre-training) trained on Indonesian data

CLIP-Indonesian CLIP (Radford et al., 2021) is a multimodal model that can connect images and text by training a vision encoder and a text encoder joi

Galuh 17 Mar 10, 2022
Implements the training, testing and editing tools for "Pluralistic Image Completion"

Pluralistic Image Completion ArXiv | Project Page | Online Demo | Video(demo) This repository implements the training, testing and editing tools for "

Chuanxia Zheng 615 Dec 08, 2022
FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks

FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks

HKBU High Performance Machine Learning Lab 6 Nov 18, 2022
Code repository for the paper "Tracking People with 3D Representations"

Tracking People with 3D Representations Code repository for the paper "Tracking People with 3D Representations" (paper link) (project site). Jathushan

Jathushan Rajasegaran 77 Dec 03, 2022
Vision Transformer and MLP-Mixer Architectures

Vision Transformer and MLP-Mixer Architectures Update (2.7.2021): Added the "When Vision Transformers Outperform ResNets..." paper, and SAM (Sharpness

Google Research 6.4k Jan 04, 2023
Official code for "EagerMOT: 3D Multi-Object Tracking via Sensor Fusion" [ICRA 2021]

EagerMOT: 3D Multi-Object Tracking via Sensor Fusion Read our ICRA 2021 paper here. Check out the 3 minute video for the quick intro or the full prese

Aleksandr Kim 276 Dec 30, 2022
Flybirds - BDD-driven natural language automated testing framework, present by Trip Flight

Flybird | English Version 行为驱动开发(Behavior-driven development,缩写BDD),是一种软件过程的思想或者

Ctrip, Inc. 706 Dec 30, 2022
The GitHub repository for the paper: “Time Series is a Special Sequence: Forecasting with Sample Convolution and Interaction“.

SCINet This is the original PyTorch implementation of the following work: Time Series is a Special Sequence: Forecasting with Sample Convolution and I

386 Jan 01, 2023
Algo-burn - Script to configure an Algorand address as a "burn" address for one or more ASA tokens

Algorand Burn Address This is a simple script to illustrate how a "burn address"

GSD 5 May 10, 2022
Example of a Quantum LSTM

Example of a Quantum LSTM

Riccardo Di Sipio 36 Oct 31, 2022
Toward Multimodal Image-to-Image Translation

BicycleGAN Project Page | Paper | Video Pytorch implementation for multimodal image-to-image translation. For example, given the same night image, our

Jun-Yan Zhu 1.4k Dec 22, 2022
Code samples for my book "Neural Networks and Deep Learning"

Code samples for "Neural Networks and Deep Learning" This repository contains code samples for my book on "Neural Networks and Deep Learning". The cod

Michael Nielsen 13.9k Dec 26, 2022
Official implementation of the paper 'Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution' in CVPR 2022

LDL Paper | Supplementary Material Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution Jie Liang*, Hu

150 Dec 26, 2022
Intrinsic Image Harmonization

Intrinsic Image Harmonization [Paper] Zonghui Guo, Haiyong Zheng, Yufeng Jiang, Zhaorui Gu, Bing Zheng Here we provide PyTorch implementation and the

VISION @ OUC 44 Dec 21, 2022
Codes for NeurIPS 2021 paper "On the Equivalence between Neural Network and Support Vector Machine".

On the Equivalence between Neural Network and Support Vector Machine Codes for NeurIPS 2021 paper "On the Equivalence between Neural Network and Suppo

Leslie 8 Oct 25, 2022
A PyTorch implementation of the architecture of Mask RCNN

EDIT (AS OF 4th NOVEMBER 2019): This implementation has multiple errors and as of the date 4th, November 2019 is insufficient to be utilized as a reso

Sai Himal Allu 975 Dec 30, 2022
This repository provides a PyTorch implementation and model weights for HCSC (Hierarchical Contrastive Selective Coding)

HCSC: Hierarchical Contrastive Selective Coding This repository provides a PyTorch implementation and model weights for HCSC (Hierarchical Contrastive

YUANFAN GUO 111 Dec 20, 2022
Lava-DL, but with PyTorch-Lightning flavour

Deep learning project seed Use this seed to start new deep learning / ML projects. Built in setup.py Built in requirements Examples with MNIST Badges

Sami BARCHID 4 Oct 31, 2022
Implementation of the paper "Language-agnostic representation learning of source code from structure and context".

Code Transformer This is an official PyTorch implementation of the CodeTransformer model proposed in: D. Zügner, T. Kirschstein, M. Catasta, J. Leskov

Daniel Zügner 131 Dec 13, 2022