Use public workflow badge in README and documentation

.vscode/settings.json

@@ -37,6 +37,7 @@
         "fargs",
         "fiducials",
         "fignums",
+        "flamegraph",
         "FLANN",
         "Fullscreen",
         "GFTT",
@@ -54,6 +55,7 @@
         "Jacobians",
         "jhartzer",
         "Kabsch",
+        "Kalman",
         "keypoint",
         "mainpage",
         "mathcal",
@@ -79,6 +81,7 @@
         "Treeware",
         "tsukuba",
         "undistort",
+        "unmannedlab",
         "whitegrid",
         "xdata",
         "ydata",

README.md

@@ -1,13 +1,13 @@
 # ekf_cal
-[![All Tests](https://github.com/JHartzer/ekf_cal/actions/workflows/all-tests.yaml/badge.svg)](https://github.com/JHartzer/ekf_cal/actions/workflows/all-tests.yaml)
+[![All Tests](https://github.com/UnmannedLab/ekf_cal/actions/workflows/all-tests.yaml/badge.svg)](https://github.com/UnmannedLab/ekf_cal/actions/workflows/all-tests.yaml)
 
 Extended Kalman Filter Calibration and Localization: ekf_cal is a package focused on the simulation and development of a multi-sensor online calibration kalman filter. It combines the architecture of a Multi-State Constraint Kalman Filter (MSCKF) with a multi-sensor calibration filter to provide intrinsic and extrinsic estimates for the following sensors:
 - [IMU](https://unmannedlab.org/ekf_cal/imu.html)
 - [GPS](https://unmannedlab.org/ekf_cal/gps.html)
 - [Cameras](https://unmannedlab.org/ekf_cal/camera.html)
 - [Fiducials](https://unmannedlab.org/ekf_cal/fiducial.html)
 
-The full project documentation can be found here: [https://www.unmannedlab.org/ekf_cal/](https://www.unmannedlab.org/ekf_cal/)
+The full [project documentation](https://www.unmannedlab.org/ekf_cal/) is available online.
 
 <img src="docs/doxygen/html/images/setup.svg" alt="setup" width="80%"/>
 

docs/main.md

@@ -1,12 +1,21 @@
 # ekf_cal
-[![Documentation](https://github.com/unmannedlab/ekf_cal/actions/workflows/documentation.yaml/badge.svg)](https://github.com/unmannedlab/ekf_cal/actions/workflows/documentation.yaml)
+
+\htmlonly
+<a href="https://github.com/UnmannedLab/ekf_cal/actions/workflows/all-tests.yaml">
+  <svg width="120" height="20" viewBox="0 0 120 20">
+    <image width="120" height="20" xlink:href="https://github.com/UnmannedLab/ekf_cal/actions/workflows/all-tests.yaml/badge.svg"/>
+  </svg>
+</a>
+\endhtmlonly
 
 Extended Kalman Filter Calibration and Localization: ekf_cal is a package focused on the simulation and development of a multi-sensor online calibration kalman filter. It combines the architecture of a Multi-State Constraint Kalman Filter (MSCKF) with a multi-sensor calibration filter to provide intrinsic and extrinsic estimates for the following sensors:
 - [IMU](docs/filters/imu.md)
 - [GPS](docs/filters/gps.md)
 - [Cameras](docs/filters/camera.md)
 - [Fiducials](docs/filters/fiducial.md)
 
+The full [project documentation](https://www.unmannedlab.org/ekf_cal/) is available online.
+
 <img src="images/setup.svg" alt="setup" width="80%"/>
 
 ## Quick Start
@@ -30,7 +39,6 @@ The ekf_cal package has the following hard dependencies that are required for al
 The following dependencies are for building the ROS node and simulation, respectively
 - [ROS2](https://docs.ros.org/en/rolling/index.html)
 - [yaml-cpp](https://github.com/jbeder/yaml-cpp)
-
 The following soft dependencies useful for development and documentation
 - [Doxygen](https://www.doxygen.nl/index.html)
 - [Google Test](https://google.github.io/googletest/)