<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>data on Matthew Shields</title>
    <link>https://mshields.name/tags/data/</link>
    <description>Recent content in data on Matthew Shields</description>
    <generator>Hugo -- gohugo.io</generator>
    <copyright>© 2022 - 2026 Matthew Shields</copyright>
    <lastBuildDate>Fri, 19 Jan 2024 00:00:00 +0000</lastBuildDate><atom:link href="https://mshields.name/tags/data/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>Setting Up CUDA 11.8 and Pytorch on Ubuntu 20.04 with Secure Boot Enabled</title>
      <link>https://mshields.name/blog/2024-01-20-setting-up-cuda-11-8-and-pytorch-on-ubuntu-20-04-with-secure-boot-enabled/</link>
      <pubDate>Fri, 19 Jan 2024 00:00:00 +0000</pubDate>
      
      <guid>https://mshields.name/blog/2024-01-20-setting-up-cuda-11-8-and-pytorch-on-ubuntu-20-04-with-secure-boot-enabled/</guid>
      <description>Preamble I recently got a fresh daily drive laptop which happens to have secure boot enabled. Typically this has added yet more complication to getting setup with CUDA and PyTorch. Hopefully the following reference can help someone else out or even just me if I need it again in the future.
How To 1. Purge system of NVIDIA CUDA in case of a previous failed install sudo rm -r /var/lib/dkms/nvidia sudo rm /etc/apt/sources.</description>
    </item>
    
    <item>
      <title>UK Climate Change</title>
      <link>https://mshields.name/blog/2022-06-10-uk-climate-change/</link>
      <pubDate>Fri, 10 Jun 2022 00:00:00 +0000</pubDate>
      
      <guid>https://mshields.name/blog/2022-06-10-uk-climate-change/</guid>
      <description>Preamble I found this on NASA’s climate site and my curiosity was piqued.
Temperature anomaly, how did they get to that?
Anomaly versus what?
Surely, it’s against where the temperature should be, but how do you know where the temperature should be?
What effects do you account for and what do you leave out?
I thought I’d have a stab at how they came up with these numbers, but I wanted to do it for UK data, specifically.</description>
    </item>
    
    <item>
      <title>Setting Up A Georeferenced RTK Base Station</title>
      <link>https://mshields.name/blog/2022-05-01-setting-up-a-georeferenced-rtk-base-station/</link>
      <pubDate>Sun, 01 May 2022 00:00:00 +0000</pubDate>
      
      <guid>https://mshields.name/blog/2022-05-01-setting-up-a-georeferenced-rtk-base-station/</guid>
      <description>Preamble In my previous post I detailed how to use RINEX data to create a sub-decimeter level position solution. Using RINEX data in this way from government sources ties you to an agreed upon reference datum. With your own base station this can be problematic as the accuracy of the established position of the station will likely not be geographically accurate. This then leads to repeatable rover solutions but they will have some offset versus many other georeferrenced data sets, eg.</description>
    </item>
    
    <item>
      <title>Registration Methods Comparison</title>
      <link>https://mshields.name/blog/2022-03-10-registration-methods-comparison/</link>
      <pubDate>Thu, 24 Mar 2022 00:00:00 +0000</pubDate>
      
      <guid>https://mshields.name/blog/2022-03-10-registration-methods-comparison/</guid>
      <description>Preamble Registration is the technique of aligning two data sets by finding either a rigid or affine transformation, depending on the problem. In robotics this is often between two pointclouds but the technique can be useful for aligning any data sets especially those that contain spatial data, MRI scan images for example. The Wikipedia page for this topic is quite concise and well written.
Background Typically we represent transformations in 3D space as a matrix and translation vector that we apply to an input vector of coordinates to produce a transformed output vector of shifted coordinates.</description>
    </item>
    
    <item>
      <title>Connecting to a ROS Master Over a VPN</title>
      <link>https://mshields.name/blog/2022-03-12-connecting-ros-master-over-vpn/</link>
      <pubDate>Sat, 12 Mar 2022 00:00:00 +0000</pubDate>
      
      <guid>https://mshields.name/blog/2022-03-12-connecting-ros-master-over-vpn/</guid>
      <description>Preamble This is a nice build on from my previous post on creating a VPN server. If you are using ROS and a VPN server it is possible to remotely connect to the ROS master on one of your robots from either another robot or other device. Basically the only requirement is that both systems are clients on the VPN and can run ROS. It also helps if you have provisioned each system with a static IP address, again details are in my previous post on creating a VPN server.</description>
    </item>
    
    <item>
      <title>Remotely Connecting to a U-Blox GNSS Receiver</title>
      <link>https://mshields.name/blog/2022-02-26-remotely-connecting-to-a-ublox-gnss-receiver/</link>
      <pubDate>Mon, 07 Mar 2022 00:00:00 +0000</pubDate>
      
      <guid>https://mshields.name/blog/2022-02-26-remotely-connecting-to-a-ublox-gnss-receiver/</guid>
      <description>Preamble Being able to deploy over the air updates to your robot’s peripherals is a powerful thing. In the early stages it may also be useful for engineers to be able to connect directly to these devices as if they were connected to their personal computers. Here I’m going to detail one approach for this using ser2net. I’ll use connecting to a U-Blox Z-F9P GNSS receiver as a demonstration use case.</description>
    </item>
    
    <item>
      <title>Extracting Road Markings from Pointcloud Data</title>
      <link>https://mshields.name/blog/2022-02-23-extracting-road-markings-from-pointcloud-data/</link>
      <pubDate>Sat, 26 Feb 2022 00:00:00 +0000</pubDate>
      
      <guid>https://mshields.name/blog/2022-02-23-extracting-road-markings-from-pointcloud-data/</guid>
      <description>Preamble This is the first post in a series looking back at past projects I have done but not shared publicly or documented in any way.
This was a piece of work from 2019 with the goal of extracting road markings from geo-referenced pointclouds. For those that don’t know, a geo-referenced pointcloud is created by taking a LiDAR and putting it on some kind of a rover vehicle, then taking all the observations of the LiDAR that were taken in the moving vehicle reference frame and converting them into the global “static” reference frame.</description>
    </item>
    
  </channel>
</rss>
