learning and feeling SLAM together with hands-on-experiments

Last update: Dec 22, 2022

Related tags

Overview

modern-slam-tutorial-python

Learning and feeling SLAM together with hands-on-experiments 😀 😃 😆

Dependencies

Most of the examples are based on GTSAM. use $ pip install gtsam and I prefer using conda environment.
- Also, I'll (want to) also use Pytorch to study recent differentiable factor-graph optimization works.

robust_pgo: a robust pose-graph optimization
- Tutorial video
- Dependencies: numpy, GTSAM (python)
- The datasets are available from https://lucacarlone.mit.edu/datasets/

To be continued ...

Contact

[email protected]

Plan

Other geometric optimization for SLAM
- Non-rigid ICP
- Rotation initialization
- ...
Trying GTSAM integration with Open3D, scipy, Pytorch, etc ...

Owner

Giseop Kim

Research Engineer at NAVER LABS

GitHub Repository

Demystifying How Self-Supervised Features Improve Training from Noisy Labels

Demystifying How Self-Supervised Features Improve Training from Noisy Labels This code is a PyTorch implementation of the paper "[Demystifying How Sel

[email protected]"> 4 Oct 14, 2022

Implementation of PyTorch-based multi-task pre-trained models

mtdp Library containing implementation related to the research paper "Multi-task pre-training of deep neural networks for digital pathology" (Mormont

27 Oct 14, 2022

Luminous is a framework for testing the performance of Embodied AI (EAI) models in indoor tasks.

Luminous is a framework for testing the performance of Embodied AI (EAI) models in indoor tasks. Generally, we intergrete different kind of functional

28 Jan 08, 2023

TransReID: Transformer-based Object Re-Identification

TransReID: Transformer-based Object Re-Identification [arxiv] The official repository for TransReID: Transformer-based Object Re-Identification achiev

569 Dec 30, 2022

Gym Threat Defense

Gym Threat Defense The Threat Defense environment is an OpenAI Gym implementation of the environment defined as the toy example in Optimal Defense Pol

5 Dec 08, 2022

Code for "Learning Canonical Representations for Scene Graph to Image Generation", Herzig & Bar et al., ECCV2020

Learning Canonical Representations for Scene Graph to Image Generation (ECCV 2020) Roei Herzig*, Amir Bar*, Huijuan Xu, Gal Chechik, Trevor Darrell, A

24 Jul 07, 2022

VolumeGAN - 3D-aware Image Synthesis via Learning Structural and Textural Representations

VolumeGAN - 3D-aware Image Synthesis via Learning Structural and Textural Representations 3D-aware Image Synthesis via Learning Structural and Textura

116 Dec 26, 2022

This is the pytorch re-implementation of the IterNorm

IterNorm-pytorch Pytorch reimplementation of the IterNorm methods, which is described in the following paper: Iterative Normalization: Beyond Standard

32 Dec 27, 2022

Open source hardware and software platform to build a small scale self driving car.

Donkeycar is minimalist and modular self driving library for Python. It is developed for hobbyists and students with a focus on allowing fast experimentation and easy community contributions.

2.4k Jan 04, 2023

HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electronic Health Records

HiPAL Code for KDD'22 Applied Data Science Track submission -- HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electro

4 Aug 08, 2022

A Kitti Road Segmentation model implemented in tensorflow.

KittiSeg KittiSeg performs segmentation of roads by utilizing an FCN based model. The model achieved first place on the Kitti Road Detection Benchmark

890 Jan 04, 2023

The pyrelational package offers a flexible workflow to enable active learning with as little change to the models and datasets as possible

pyrelational is a python active learning library developed by Relation Therapeutics for rapidly implementing active learning pipelines from data management, model development (and Bayesian approximat

95 Dec 27, 2022