GPisMap_v2

This repository contains source codes and demo files for our paper Online Continuous Mapping using Gaussian Process Implicit Surfaces (GPIS), which is presented at IEEE ICRA 2019.

The previous repo [GPisMAP(https://github.com/leebhoram/GPisMap.git) is not maintained but kept as legacy. This repo contains some updates including slightly enhanced speed and simple python interfaces.

License

Licensed under GNU General Public License version 3.

Requirements: Software

1. Eigen

2. (Option 1) Build the source via MATLAB mex and run demo & visualization scripts on MATLAB Recommended for best visualization.

3. (Option 2) Alternatively, build the source via cmake and run demo & visualization scripts in Python (tested with version 3.7 - 3.9 and CMake 3.20+). Visualization is limited, but useful in case you have no Matlab license.

Compiling and Running

1. Clone this repository

git clone https://github.com/leebhoram/GPisMap2.git
cd GPisMap2

MATLAB Option

2. cd to the mex directive in MATLAB

cd <GPisMap2>/matlab/mex

3. Compile the mex functions by executing the make script.

   • Setup mex

   mex -setup
   

   • Run the make scripts

   make_GPisMap
   make_GPisMap3
   

4. Run the demo scripts

First,

cd <GPisMap2>/matlab

Then,

• For 2D

run('demo_gpisMap.m')

• For 3D

run('demo_gpisMap3.m')

5. Trouble shooting
   • If mex complains about not finding eigen, configure the eigen path appropriately in both make_GPisMap.m and make_GPisMap3.m

Python Option

2. Build the source

mkdir build && cd build
cmake ..
make -j $(nproc)

3. Run the demo scripts

cd <GPisMap2>/python

• For 2D

python test.py

• For 3D

python test3d.py 

4. Python required packages (To-do)

Author

Bhoram Lee E-mail: <first_name>.<last_name>@gmail.com

Misc.

Code has been developed and tested on Ubuntu 22.04

Citation

If you find GPisMap/GPisMap_v2 useful in your research, please consider citing:

  @article{<blee-icra19>,
      Author = {Bhoram Lee, Clark Zhang, Zonghao Huang, and Daniel D. Lee},
      Title = {Online Continuous Mapping using Gaussian Process Implicit Surfaces},
      Journal = {IEEE ICRA},
      Year = {2019}
   }