Serve the wiki from roboticsknowledgebase.github.io

_config.yml

@@ -12,7 +12,7 @@ title_separator          : "-"
 remote_theme             : "mmistakes/minimal-mistakes@4.19.1"
 name                     : #"Your Name"
 description              : "The Wiki for Robot Builders."
-url                      : https://roboticsknowledgebase.com # the base hostname & protocol for your site e.g. "https://mmistakes.github.io"
+url                      : https://roboticsknowledgebase.github.io # the base hostname & protocol for your site
 baseurl                  : # the subpath of your site, e.g. "/blog"
 repository               : "roboticsknowledgebase/roboticsknowledgebase.github.io" # GitHub username/repo-name e.g. "mmistakes/minimal-mistakes"
 teaser                   : # path of fallback teaser image, e.g. "/assets/images/500x300.png"

about.md

@@ -20,7 +20,7 @@ This wiki is meant for people in various stages of their career, including absol
 
 For simple edits, you can use the [editor on GitHub](https://github.com/RoboticsKnowledgebase/roboticsknowledgebase.github.io/blob/master/README.md) to maintain and preview the content for your website in Markdown files.
 
-Please see the [Contribute page](https://roboticsknowledgebase.com/docs) for more details.
+Please see the [Contribute page](/docs) for more details.
 
 Whenever you commit to this repository, GitHub Pages will run [Jekyll](https://jekyllrb.com/) to rebuild the pages in your site, from the content in your Markdown files.
 

index.md

@@ -8,7 +8,7 @@ header:
   overlay_filter: "0.5"
   overlay_image: /assets/images/ricardo-gomez-angel-162935.jpg
   cta_label: "Start Learning"
-  cta_url: "https://roboticsknowledgebase.com/wiki/"
+  cta_url: "/wiki/"
 excerpt: "The Robotics Knowledgebase exists to advance knowledge in the robotics discipline."
 ---
 {% include nav_list nav=page.sidebar.nav %}

wiki/actuation/selecting-the-right-motor.md

@@ -106,8 +106,8 @@ BLDC and servo motors often require active or passive cooling in high-performanc
 To summarize; selecting the right motor for a project involves balancing priorities and understanding the trade-offs between precision, control complexity, maintenance, torque, and cost. For applications requiring high precision, stepper or servo motors are ideal, whereas geared motors or high-torque BLDCs are suited for power-intensive tasks. Simple projects can use brushed motors for their ease of use, while advanced designs may justify the cost and control demands of brushless or servo motors. Brushless and AC motors are better for long-term use due to low maintenance, making them worthwhile investments. To amplify torque, gearboxes are effective, though they can reduce speed and introduce backlash. Finally, while cost-effective motors like brushed or stepper options work for non-critical components, critical applications demand higher-performing, costlier solutions.
 
 ## See Also:
-- [Motor Controller with Feedback](https://roboticsknowledgebase.com/wiki/actuation/motor-controller-feedback/)
-- [Linear Actuator Resources and Quick Reference](https://roboticsknowledgebase.com/wiki/actuation/linear-actuator-resources/)
+- [Motor Controller with Feedback](/wiki/actuation/motor-controller-feedback/)
+- [Linear Actuator Resources and Quick Reference](/wiki/actuation/linear-actuator-resources/)
 
 ## Further Reading
 - [Back-EMF in BLDC Motors : A Complete Guide](https://mechtex.com/blog/back-emf-in-bldc-motors-a-complete-guide#:~:text=Effects%20of%20Back%2DEMF%20on%20BLDC%20Motor%20Performance,and%20back%2DEMF%20which%20results%20in%20speed%20regulation)

wiki/common-platforms/dji-drone-breakdown-for-technical-projects.md

@@ -86,4 +86,4 @@ Here are some quadcopter safety precautions to keep in mind:
 If you are thinking of using DJI drones for your project, either be sure to stick with their GPS, implement your own EKF and Controller, or augment their drone with a PX4 controller to take advantage of the DJI hardware. Be sure to know the three flight control modes well, and follow general and safety tips for a successful project.
 
 ## See Also:
-- [DJI SDK Introduction](https://roboticsknowledgebase.com/wiki/common-platforms/dji-sdk/)
+- [DJI SDK Introduction](/wiki/common-platforms/dji-sdk/)

wiki/common-platforms/ros/ros-arduino-interface.md

@@ -204,4 +204,4 @@ sudo chmod a+rw /dev/ttyUSB0
 if the above command doesn’t work.
 
 ## See Also:
-- [ROS Introduction](https://roboticsknowledgebase.com/wiki/common-platforms/ros/ros-intro/)
+- [ROS Introduction](/wiki/common-platforms/ros/ros-intro/)

wiki/common-platforms/ros/ros-unsupported-os.md

@@ -32,7 +32,7 @@ Each ROS distribution supports only a select number of platforms, and for all su
 ### 1. Running ROS2 Humble via a docker container on Ubuntu 20.04
 
 #### Installing Docker
-Follow instructions given here to install docker - https://roboticsknowledgebase.com/wiki/tools/docker/
+Follow instructions given here to install docker - /wiki/tools/docker/
 #### Running ROS2 Humble docker container
 Running the command below will pull the latest ROS2 Humble Docker Image, start a container and attach a shell to it
 ```sh
@@ -179,7 +179,7 @@ ros2 run demo_nodes_py listener
 In this article, we discussed how to run a ROS distribution on an unsupported OS. Specifically we looked at the process of running ROS2 Humble on Ubuntu 20.04. However, the methods presented in the article can be easily adapted to accommodate other scenarios.
 
 ## Further Reading
-- [Introduction to Docker](https://roboticsknowledgebase.com/wiki/tools/docker/)
+- [Introduction to Docker](/wiki/tools/docker/)
 - [Docker Reference (docker run)](https://docs.docker.com/engine/reference/run/)
 
 ## References

wiki/common-platforms/ros2-navigation-for-clearpath-husky.md

@@ -10,7 +10,7 @@ For instance, in the [Husky](https://github.com/husky/husky/tree/humble-devel) r
 This tutorial aims to guide you through the process of setting up the ROS 1 navigation stack on the Clearpath Husky and seamlessly connecting it to ROS 2. It assumes a foundational understanding of both ROS 1 and ROS 2.
 
 ## ROS 1 - ROS 2 Bridge
-To configure the Clearpath Husky hardware, we will be using the [husky_robot](https://github.com/husky/husky_robot) repository. This repository contains the ROS 1 packages for the Husky, including the navigation stack. To connect the ROS 1 packages to ROS 2, we will be using the [ros1_bridge](https://github.com/ros2/ros1_bridge) package. Detailed instruction on how to setup this is provided in [this tutorial](https://roboticsknowledgebase.com/wiki/interfacing/ros1-ros2-bridge/) on the Robotics Knowledgebase. Once the bridge is established, we can proceed to configure the Husky using the following steps.
+To configure the Clearpath Husky hardware, we will be using the [husky_robot](https://github.com/husky/husky_robot) repository. This repository contains the ROS 1 packages for the Husky, including the navigation stack. To connect the ROS 1 packages to ROS 2, we will be using the [ros1_bridge](https://github.com/ros2/ros1_bridge) package. Detailed instruction on how to setup this is provided in [this tutorial](/wiki/interfacing/ros1-ros2-bridge/) on the Robotics Knowledgebase. Once the bridge is established, we can proceed to configure the Husky using the following steps.
 ```
 # Install Husky Packages
 apt-get update && apt install ros-noetic-husky* -y
@@ -393,7 +393,7 @@ This tutorial provides a step-by-step guide to configure the Clearpath Husky for
 It is recommended to read the [Nav2 documentation](https://navigation.ros.org/index.html) to understand the Nav2 stack in detail. The [Nav2 tutorials](https://navigation.ros.org/getting_started/index.html) are also a good place to start.
 
 ## See Also:
-- [ROS1 - ROS2 Bridge](https://roboticsknowledgebase.com/wiki/interfacing/ros1-ros2-bridge/)
+- [ROS1 - ROS2 Bridge](/wiki/interfacing/ros1-ros2-bridge/)
 
 ## Further Readings:
 - [Nav2 First Time Setup](https://navigation.ros.org/setup_guides/index.html)

wiki/computing/setup-gpus-for-computer-vision.md

@@ -6,19 +6,19 @@ title: Setup your GPU Enabled System for Computer Vision and Deep Learning
 This tutorial will help you setup your Ubuntu (16/17/18) system with a NVIDIA GPU including installing the Drivers, CUDA, cuDNN, and TensorRT libraries. Tutorial also covers on how to build OpenCV from source and installing Deep Learning Frameworks such as TensorFlow (Source Build), PyTorch, Darknet for YOLO, Theano, and Keras. The setup has been tested on Ubuntu x86 platform and should also hold good for other Debian based (x86/ARM64) platforms.
 
 ## Contents
-1. [Install Prerequisites](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#1-install-prerequisites)
-2. [Setup NVIDIA Driver for your GPU](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#2-install-nvidia-driver-for-your-gpu)
-3. [Install CUDA](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#3-install-cuda)
-4. [Install cuDNN](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#4-install-cudnn)
-5. [Install TensorRT](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#5-install-tensorrt)
-6. [Python and Other Dependencies](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#6-python-and-other-dependencies)
-7. [OpenCV and Contrib Modules](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#7-install-opencv-and-contrib-modules)
-8. [Deep Learning Frameworks](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#8-install-deep-learning-frameworks)
-    - [PyTorch](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#pytorch)
-    - [TensorFlow](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#tensorflow)
-    - [Keras](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#keras)
-    - [Theano](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#theano)
-    - [Darknet for YOLO](https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/#darknet-for-yolo)
+1. [Install Prerequisites](/wiki/computing/setup-gpus-for-computer-vision/#1-install-prerequisites)
+2. [Setup NVIDIA Driver for your GPU](/wiki/computing/setup-gpus-for-computer-vision/#2-install-nvidia-driver-for-your-gpu)
+3. [Install CUDA](/wiki/computing/setup-gpus-for-computer-vision/#3-install-cuda)
+4. [Install cuDNN](/wiki/computing/setup-gpus-for-computer-vision/#4-install-cudnn)
+5. [Install TensorRT](/wiki/computing/setup-gpus-for-computer-vision/#5-install-tensorrt)
+6. [Python and Other Dependencies](/wiki/computing/setup-gpus-for-computer-vision/#6-python-and-other-dependencies)
+7. [OpenCV and Contrib Modules](/wiki/computing/setup-gpus-for-computer-vision/#7-install-opencv-and-contrib-modules)
+8. [Deep Learning Frameworks](/wiki/computing/setup-gpus-for-computer-vision/#8-install-deep-learning-frameworks)
+    - [PyTorch](/wiki/computing/setup-gpus-for-computer-vision/#pytorch)
+    - [TensorFlow](/wiki/computing/setup-gpus-for-computer-vision/#tensorflow)
+    - [Keras](/wiki/computing/setup-gpus-for-computer-vision/#keras)
+    - [Theano](/wiki/computing/setup-gpus-for-computer-vision/#theano)
+    - [Darknet for YOLO](/wiki/computing/setup-gpus-for-computer-vision/#darknet-for-yolo)
 
 ## 1. Install Prerequisites
 Before installing anything, let us first update the information about the packages stored on the computer and upgrade the already installed packages to their latest versions.

wiki/computing/troubleshooting-ubuntu-dual-boot.md

@@ -57,8 +57,8 @@ In either case, however, usage will require essential packages like build-essent
 There are a few ways Ubuntu installation can go wrong or be delayed but this page hopefully will help a few people avoid major mistakes that held the writers of this page back a few weeks. After this guide the computer should be ready for installing browsers (such as Firefox), IDEs (such as VSCode or PyCharm), and libraries (such as mujoco or realsense-ros) as desired.
 
 ## See Also:
-- [Ubuntu 14.04 on Chromebook](https://roboticsknowledgebase.com/wiki/computing/ubuntu-chromebook)
-- [Upgrading Ubuntu Kernels](https://roboticsknowledgebase.com/wiki/computing/upgrading-ubuntu-kenel)
+- [Ubuntu 14.04 on Chromebook](/wiki/computing/ubuntu-chromebook)
+- [Upgrading Ubuntu Kernels](/wiki/computing/upgrading-ubuntu-kernel/)
 
 ## Further Reading
 - [Git repositories for drivers for different types of RealTek cards](https://www.github.com/lwfinger)

wiki/interfacing/microros-for-ros2-on-microcontrollers.md

@@ -476,6 +476,6 @@ void loop()
 
 
 ## See Also:
-- [Docker](https://roboticsknowledgebase.com/wiki/tools/docker/)
-- [ROS Arduino Interface](https://roboticsknowledgebase.com/wiki/common-platforms/ros/ros-arduino-interface/) (If using ROS1 as opposed to ROS2)
-- [udev Rules](https://roboticsknowledgebase.com/wiki/tools/udev-rules/)
+- [Docker](/wiki/tools/docker/)
+- [ROS Arduino Interface](/wiki/common-platforms/ros/ros-arduino-interface/) (If using ROS1 as opposed to ROS2)
+- [udev Rules](/wiki/tools/udev-rules/)

wiki/machine-learning/ros-yolo-gpu.md

@@ -196,8 +196,8 @@ In this tutorial, we went through the procedures for integrating YOLO with ROS b
 We also demonstrated how to setup CUDA and cuDNN to run YOLO in real-time. By following our step-by-step instructions, YOLO can run with realtime performance.
 
 ## See Also
-- [realsense_camera](https://roboticsknowledgebase.com/wiki/sensing/realsense/)
-- [ROS](https://roboticsknowledgebase.com/wiki/common-platforms/ros/ros-intro/)
+- [realsense_camera](/wiki/sensing/realsense/)
+- [ROS](/wiki/common-platforms/ros/ros-intro/)
 
 ## Further Reading
 - [CUDA_tutorial](https://medium.com/@exesse/cuda-10-1-installation-on-ubuntu-18-04-lts-d04f89287130)

wiki/planning/coverage-planning-implementation-guide.md

@@ -97,7 +97,7 @@ This wiki details how to implement a basic coverage planner, which can be used f
  Overall, coverage planning is useful for tasks that require scanning of an area by a robot. We have seen how we can generate such paths over complicated areas by first splitting the region into simpler trapezoidal cells, planning a traversal across those cells, and then using a simple back-and-forth lawnmower pattern to cover each trapezoid. With such an algorithm, we can have our robots plan paths to cover arbitrarily complex polygonal regions.
 
 ## See Also:
-- [Planning Overview](https://roboticsknowledgebase.com/wiki/planning/planning-overview/)
+- [Planning Overview](/wiki/planning/planning-overview/)
 
 ## Further Reading
 - [A Survey on Coverage Path Planning for Robotics](https://core.ac.uk/download/pdf/132555826.pdf)

wiki/project-management/jira.md

@@ -129,7 +129,7 @@ In summary, Jira is a powerful tool for agile development. There are numerous fe
 
 
 ## See Also:
-- To learn more about project management see [Product Development in Complex System Design](https://roboticsknowledgebase.com/wiki/project-management/product-development-complex-systems/)
+- To learn more about project management see [Product Development in Complex System Design](/wiki/project-management/product-development-complex-systems/)
 
 
 ## Further Reading

wiki/project-management/using-notion-for-project-management.md

@@ -188,8 +188,8 @@ In summary, Notion is a powerful tool for project management. Its intuitive feat
 
 
 ## See Also:
-- [Risk Management](https://roboticsknowledgebase.com/wiki/project-management/risk-management/)
-- [Using Jira for Project Management](https://roboticsknowledgebase.com/wiki/project-management/jira/)
+- [Risk Management](/wiki/project-management/risk-management/)
+- [Using Jira for Project Management](/wiki/project-management/jira/)
 
 
 ## Further Reading

wiki/sensing/thermal-perception.md

@@ -251,5 +251,5 @@ facing depth recovery in non-traditional modalities, foundation models are a com
 
 ## See Also
 
-- The [Thermal Cameras wiki page](https://roboticsknowledgebase.com/wiki/sensing/thermal-cameras/) goes into more depth
+- The [Thermal Cameras wiki page](/wiki/sensing/thermal-cameras/) goes into more depth
   about how thermal cameras function.

wiki/state-estimation/optitrack-mocap.md

@@ -80,7 +80,7 @@ Adhering to best practices, such as proper marker placement and frame alignment,
 
 ## See Also
 - [Setting up ROS Workspaces](https://wiki.ros.org/ROS/Tutorials)
-- [Motion Capture for Robotics](https://roboticsknowledgebase.com/mocap)
+- [Motion Capture for Robotics](/wiki/state-estimation/optitrack-motion-capture/)
 
 ## Further Reading
 - [OptiTrack Official Documentation](https://optitrack.com/documentation/)

wiki/tools/clion.md

@@ -103,7 +103,7 @@ One of the important part of transitioning to professional life is using tools t
 ## See Also:
 
 - [Pycharm IDE for Python](https://www.jetbrains.com/pycharm/)
-- [VIM](https://roboticsknowledgebase.com/wiki/tools/vim/)
+- [VIM](/wiki/tools/vim/)
 - [Sublime-Text](https://www.sublimetext.com/)
 - [Sublime-Merge](https://www.sublimemerge.com/)
 

wiki/tools/code-editors-introduction-to-vs-code-and-vim.md

@@ -176,7 +176,7 @@ Just to name a few. The list is still super long. Vim plugins are powerful. Howe
 There of course is not a single best code editor that one should use. People have different preferences and situations. In fact, the debate about which code editor is the best has been around for decades. People still strive to speak for their favorite editors while once a person is stuck with an editor, it is often really hard for them to make up their mind to change. However, VS Code and Vim are certainly two of the most used code editors nowadays. I hope the above context could help you decide the one you would like to try it out. Good luck coding!
 
 ## See Also:
-- Vim Text Editor: <https://roboticsknowledgebase.com/wiki/tools/vim/>
+- Vim Text Editor: </wiki/tools/vim/>
 
 ## Further Reading
 - [Transitioning from VS Code to Vim](https://medium.com/@kalebzeray/transitioning-from-vscode-to-vim-dc3b23e35c58)

wiki/tools/docker-for-pytorch.md

@@ -130,9 +130,9 @@ Breakdown of the command:
 With this we come to the end of our article. If you were able to successfully follow the above commands and were able to run the container, you now have a docker environment for training your PyTorch model. Hope this makes your life easier.
 
 ## See Also
-- Docker https://roboticsknowledgebase.com/wiki/tools/docker/
-- Setup GPU https://roboticsknowledgebase.com/wiki/computing/setup-gpus-for-computer-vision/
-- Python construct https://roboticsknowledgebase.com/wiki/programming/python-construct/
+- Docker /wiki/tools/docker/
+- Setup GPU /wiki/computing/setup-gpus-for-computer-vision/
+- Python construct /wiki/programming/python-construct/
 
 ## Further Reading
 - PyTorch https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch

wiki/tools/gazebo-simulation.md

@@ -130,7 +130,7 @@ To update the parameters such as topic to publish, rate, and depth limits, you c
 We have covered several aspects in Gazebo, including importing and customizing a model into a Gazebo world, and to implement plugins for the sensors as well as define the URDF files so that messages would be published accordingly. These two components are crucial when we want to start a ROS simulation using Gazebo.
 
 ## See Also:
-* [Visualization and Simulation](https://roboticsknowledgebase.com/wiki/tools/visualization-simulation/)
+* [Visualization and Simulation](/wiki/tools/visualization-simulation/)
 
 ## Further Reading
 * Gazebo ROS tutorial: <http://wiki.ros.org/simulator_gazebo/Tutorials>