https://github.com/juliarobotics/motioncapturejointcalibration.jl

Kinematic calibration for robots using motion capture data
https://github.com/juliarobotics/motioncapturejointcalibration.jl

Last synced: 4 months ago
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Kinematic calibration for robots using motion capture data

• Host: GitHub
• URL: https://github.com/juliarobotics/motioncapturejointcalibration.jl
• Owner: JuliaRobotics
• License: other
• Created: 2017-07-28T01:22:11.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2020-02-17T00:05:18.000Z (over 6 years ago)
• Last Synced: 2025-06-15T11:41:28.445Z (about 1 year ago)
• Language: Julia
• Size: 106 KB
• Stars: 19
• Watchers: 2
• Forks: 4
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

          
# MotionCaptureJointCalibration

[![Build Status](https://travis-ci.org/JuliaRobotics/MotionCaptureJointCalibration.jl.svg?branch=master)](https://travis-ci.org/JuliaRobotics/MotionCaptureJointCalibration.jl) [![codecov.io](http://codecov.io/github/JuliaRobotics/MotionCaptureJointCalibration.jl/coverage.svg?branch=master)](http://codecov.io/github/JuliaRobotics/MotionCaptureJointCalibration.jl?branch=master)

MotionCaptureJointCalibration provides functionality for kinematic calibration of robots, given measurements of the positions of motion capture markers attached to the robot's links and positions of the robot's joints in a number of poses. It does so by solving a nonlinear program (NLP) with (weighted) square error between measured and predicted marker locations as the objective to minimize.

MotionCaptureJointCalibration is a small Julia library built on top of [JuMP](https://github.com/JuliaOpt/JuMP.jl) and [RigidBodyDynamics.jl](https://github.com/JuliaRobotics/RigidBodyDynamics.jl). JuMP makes it possible to choose between various NLP solvers. [Ipopt](https://github.com/JuliaOpt/Ipopt.jl) appears to perform fairly well for the problems formulated by this package.

## News

* October 18, 2017: [tagged version 0.0.1](https://github.com/JuliaRobotics/MotionCaptureJointCalibration.jl/releases/tag/v0.0.1).

* August 4, 2017: the package is under initial construction.

## Features

Features include:

* handling of occlusions

* handling of measurements of the body-fixed locations of only a subset of the markers attached to the robot (the unknown marker positions will be solved for, given rough bounds)

* handling of measurements of only a subset of a robot's joint positions (the unknown joint positions will be solved for, given rough bounds)

* proper handling of quaternion-parameterized floating joints (unit norm constraints for quaternions)

* visualization of calibration results using [RigidBodyTreeInspector](https://github.com/rdeits/RigidBodyTreeInspector.jl)

Currently, MotionCaptureJointCalibration can only estimate constant offsets between measured and actual joint positions.

## Installation

To install, simply run

```julia

Pkg.add("MotionCaptureJointCalibration")

```

This will install MotionCaptureJointCalibration and its required dependencies. RigidBodyTreeInspector.jl is an optional dependency and can be used to visualize the calibration results (`Pkg.add("RigidBodyTreeInspector")`). You'll also need an NLP solver that interfaces with JuMP, e.g. Ipopt (`Pkg.add("Ipopt")`).

## Usage

See [the demo notebook](https://github.com/JuliaRobotics/MotionCaptureJointCalibration.jl/blob/master/notebooks/Demo.ipynb) for usage.

## Acknowledgements

A variant of the NLP formulation used in this package is due to Michael Posa.