https://github.com/baggepinnen/pfseamtracking.jl

https://github.com/baggepinnen/pfseamtracking.jl

particle-filter seam-tracking state-estimation

Last synced: 7 months ago
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• Host: GitHub
• URL: https://github.com/baggepinnen/pfseamtracking.jl
• Owner: baggepinnen
• License: other
• Created: 2016-07-29T12:32:22.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2020-12-13T07:44:13.000Z (almost 5 years ago)
• Last Synced: 2025-01-22T04:13:28.437Z (9 months ago)
• Topics: particle-filter, seam-tracking, state-estimation
• Language: Julia
• Size: 28.3 KB
• Stars: 1
• Watchers: 3
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

          
# PFSeamTracking

[![Build Status](https://travis-ci.org/baggepinnen/PFSeamTracking.jl.svg?branch=master)](https://travis-ci.org/baggepinnen/PFSeamTracking.jl)

Repository implementing the framework detailed in  

  **Particle Filter Framework for 6D Seam Tracking Under Large External Forces Using 2D Laser Sensors**  

  F Bagge Carlson, M Karlsson, A Robertsson, R Johansson  

  *2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)*

Available online: http://portal.research.lu.se/portal/files/12204979/seamTrackingPaper.pdf

```bibtex

@inproceedings{baggecarlson2016particle,

  title={Particle Filter Framework for 6D Seam Tracking Under Large External Forces Using 2D Laser Sensors},

  author={Bagge Carlson, Fredrik and Karlsson, Martin and Robertsson, Anders and Johansson, Rolf},

  booktitle={2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},

  year={2016},

  organization={IEEE--Institute of Electrical and Electronics Engineers Inc.}

}

```

# Installation

This package is not registered in `METADATA` and must thus be installed with the command  

`Pkg.clone("git@github.com:baggepinnen/PFSeamTracking.jl.git")`  

To test the functionality of the package, execute  

`Pkg.test("PFSeamTracking")`  

To plot results etc., install the package `Plots.jl` and a compatible backend. To perform the statistical analysis, install `ExperimentalAnalysis.jl`

# Usage

The file `simulate_tracking.jl` contains an example that executes a numer of simulations in parallel (start julia with `julia -p x` where `x` is your desired number of workers). The script then performs statistical analysis of the results using linear modeling with parameters as factors, as described in the paper.