Skip to content

[Master thesis] FastSLAM 1.0 GPU implementation with Python bindings

Notifications You must be signed in to change notification settings

tomasr8/fastslam64

Repository files navigation

FastSLAM64 - FastSLAM 1.0 GPU implementation

This repository contains a real-time CUDA implementation of the FastSLAM 1.0 [1] algorithm. The implementation is described in my thesis Navigation System for Autonomous Student Formula (Czech Technical University in Prague, 2021).

Dependencies

The algorithm require a CUDA-capable GPU with CUDA installed on the host. Python3 is required to run the examples. The Python dependencies can be installed using:

$ python3 -m pip install -r requirements.txt

Running

There are three examples from different datasets -- simulation.py, fsonline.py, and utias.py, which can run by executing the corresponding file with Python.

Code structure

  • simulation.py
  • fsonline.py
  • utias.py
  • lib/
    • Python GPU instrumentation/visualization
  • cuda/
    • FastSLAM 1.0 implementation

References

[1] M. Montemerlo, S. Thrun, D. Koller, B. Wegbreit, et al. FastSLAM: Afactored solution to the simultaneous localization and mapping problem. Aaai/iaai, 593598, 2002

About

[Master thesis] FastSLAM 1.0 GPU implementation with Python bindings

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published