From a5707f61d425a5cc5159b7eeeaf35a942c1b7a41 Mon Sep 17 00:00:00 2001 From: "Mohammed A. Shalaby" Date: Sun, 10 Nov 2024 19:25:53 -0500 Subject: [PATCH] Add titles to all EKF pages --- docs/examples/ekf/index.md | 2 +- docs/examples/ekf/se23_one_robot.md | 2 ++ docs/examples/ekf/se23_three_robot.md | 2 ++ 3 files changed, 5 insertions(+), 1 deletion(-) diff --git a/docs/examples/ekf/index.md b/docs/examples/ekf/index.md index e58aeff..1e7f4d8 100644 --- a/docs/examples/ekf/index.md +++ b/docs/examples/ekf/index.md @@ -4,7 +4,7 @@ parent: Examples nav_order: 4 --- -# Extended Kalman Filter (EKF) Examples - Overview +# Extended Kalman Filter (EKF) Examples The following examples demonstrate the usage of the MILUV dataset with the Extended Kalman Filter (EKF) for state estimation. We show EKF examples that use IMU for state propagation and UWB for state correction in single- and multi-robot scenarios. We also show EKF examples that use Visual-Inertial Navigation System (VINS) output for state propagation in a loosely-coupled manner, alongside UWB for state correction in single- and multi-robot scenarios. diff --git a/docs/examples/ekf/se23_one_robot.md b/docs/examples/ekf/se23_one_robot.md index 610f029..b9c6b25 100644 --- a/docs/examples/ekf/se23_one_robot.md +++ b/docs/examples/ekf/se23_one_robot.md @@ -5,6 +5,8 @@ usemathjax: true nav_order: 3 --- +# $SE_2(3)$ EKF with IMU - One Robot + ![The setup for the one-robot IMU EKF](https://decargroup.github.io/miluv/assets/one_robot.png) This example shows how we can use MILUV to test out an Extended Kalman Filter (EKF) for a single robot using an Inertial Measurement Unit (IMU). The derivations here are a little bit more involved than the [VINS EKF example](https://decargroup.github.io/miluv/examples/ekf/se3_one_robot.html), but we'll show that the EKF implementation is still straightforward using the MILUV devkit. Nonetheless, we suggest looking at the VINS example first before proceeding with this one. In this example, we will use the following data: diff --git a/docs/examples/ekf/se23_three_robot.md b/docs/examples/ekf/se23_three_robot.md index 2b4b730..11656b6 100644 --- a/docs/examples/ekf/se23_three_robot.md +++ b/docs/examples/ekf/se23_three_robot.md @@ -5,6 +5,8 @@ usemathjax: true nav_order: 4 --- +# $SE_2(3)$ EKF with IMU - Three Robots + ![The setup for the three-robot IMU EKF](https://decargroup.github.io/miluv/assets/three_robots.png) This example shows how we can use MILUV to test out an Extended Kalman Filter (EKF) for three robots using Inertial Measurement Units (IMUs). This extends the [one-robot IMU example](https://decargroup.github.io/miluv/examples/ekf/se23_one_robot.html) to three robots, in the same manner we extended the [one-robot VINS example](https://decargroup.github.io/miluv/examples/ekf/se3_one_robot.html) to [three robots](https://decargroup.github.io/miluv/examples/ekf/se3_three_robot.html). We will keep this example brief as it is not much different than what we have seen before. The data we use is the same as the one-robot example, but now we also use the inter-robot UWB range data to estimate the poses and IMU biases of all the robots.