test

.gitignore

@@ -0,0 +1,2 @@
+.DS_Store
+/public

config.toml

@@ -1,16 +1,14 @@
-base_url = "https://um-arm-lab.github.io/lucca"
+base_url = "https://um-arm-lab.github.io"
 compile_sass = true
 build_search_index = false
 generate_feeds = false
-minify_html = true
+minify_html = false
 
 [markdown]
 highlight_code = true
 highlight_theme = "css"
 smart_punctuation = true
 
 [extra]
-favicon = false
-large_card = true
 footer_text = "This website is built using [Zola](https://www.getzola.org) and the [Academic Paper](http://github.com/aterenin/academic-paper/) theme, which is [designed to last](https://jeffhuang.com/designed_to_last/)."
 server_side_katex = true

content/_index.md

@@ -39,7 +39,7 @@ $$
 &emsp; *Dynamics, (2)*: The real system evolves following the unknown stochastic dynamics `$f$`. We only have access to an approximation `$\tilde f$` and the inference transitions in `$D_{cal}$`.<br>
 &emsp; *Safety, (3)*: Our trajectory should remain probabilistically safe, which we define as requiring it to lie within a safe set `$\mathscr C$` with at least a user-specified probability. This is difficult to guarantee in general for any `$f$` and `$\tilde f$`, since our approximation can be arbitrarily wrong in deployment conditions. <br>
 &emsp;*State and Control Admissibility, (4)*: Both the control inputs and the states must belong to pre-defined sets. <br>
-&emsp;*Objective Function, (1)*: Additionally, we aim to achieve optimality relative to an objective that incorporates `$\mathcal G$` along with the state and control sequences, `$s := (s_{t+1},\ldots, s_{t+H})$` and `$u := (u_{t},\ldots,u_{t+H-1})$`. For example, $J$ might minimize the expectation of a distance metric to `$\mathcal G$`, control effort, or epistemic-uncertainty along the state-control sequences.
+&emsp;*Objective Function, (1)*: Additionally, we aim to achieve optimality relative to an objective that incorporates `$\mathcal G$` along with the state and control sequences, `$s := (s_{t+1},\ldots, s_{t+H})$` and `$u := (u_{t},\ldots,u_{t+H-1})$`. For example, `$J$` might minimize the expectation of a distance metric to `$\mathcal G$`, control effort, or epistemic-uncertainty along the state-control sequences.
 
 # LUCCA
 

readme.md

@@ -0,0 +1,3 @@
+# LUCCa
+
+Visit the website for more information about this project published in WAFR 2024: [https://um-arm-lab.github.io/lucca](https://um-arm-lab.github.io/lucca).