shubhamomprakashpatil / simulataeous_localisation_and_mapping_using_gtsam

This repository lays out a detailed example code to use the GTSAM Library, used for Factor Graph Optimization of 2-Dimensional and 3-Dimensional trajectory sensor data.

Simulataeous_Localisation_and_Mapping_using_GTSAM

This repository lays out a detailed example code to use the GTSAM Library, used for Factor Graph Optimization of 2-Dimensional and 3-Dimensional trajectory sensor data.

1. It consists of 6 python files (in two sub-folders), each corresponding to 2D / 3D Batch and Incremental Optimisation for SLAM using GTSAM Library.

2. The repository uses the input_INTEL_g20.g2o (for 2D) and parking-garage.g2o (for 3D) dataset, publicly available at https://lucacarlone.mit.edu/datasets/

3. Ideally, no addition dependicies should be required to run these files, other than gtsam and matplotlib.

The author adheres to the Honour Code and have commented all the steps in the code for the reader's understanding of algorithm and the code. Furthermore, detailed explanation of the code and the algorithm is provided in .docx format for reference.

Thank-you.

Pre-requisites

1. Install GTSAM in Python using pip install gtsam
2. For plotting install Matplotlib using pip install matplotlib