Merge pull request #106 from KIT-MRT/add_comparison_to_behavior_trees

Add comparison to behavior trees

README.md

@@ -14,21 +14,46 @@
   Behavior components address *How to do it?* and *Can we do it?*, while Arbitrators decide *What to do?*
  - 🧠 **Meta-framework**  
   Integrate diverse methods in one decision-making framework. Why not combine optimization-based planning, probabilistic approaches (POMDPs), and machine learning (RL)? Use any approach where it performs best!
-- 📈 **Scalability**  
-  Stack behavior components in arbitrators to create hierarchical behavior models.
 - 🛠️ **Maintainability**  
   Add new behaviors without having to touch existing ones – did we mention strict modularity and functional decomposition?
-- 💡 **Transparency**  
-  Easily follow and understand the decision-making process.
 - 🛡️ **Behavior Verification**  
   Use tightly integrated verifiers to ensure that only safe and valid behavior commands are executed.
 - 🪂 **Graceful Degradation**  
   Your behavior is unreliable or unsafe? Arbitrators will gracefully fall back to the next-best option.
+
+
+<details>
+<summary>😋 Click for more reasons!</summary>
+
+- 📈 **Scalability**  
+  Stack behavior components in arbitrators to create hierarchical behavior models.
+- 💡 **Transparency**  
+  Easily follow and understand the decision-making process, e.g., with our GUI.
 - 📦 **Header-Only**  
-  Simple integration – just include this header-only C++ library!
+  Simple integration – just include this header-only C++17 library!
 - 📜 **Permissive License**  
   Published under MIT license to ensure maximum flexibility for your projects.
 
+</details>
+
+
+<details>
+<summary>🤨 How does it compare to Behavior Trees?</summary>
+
+Behavior Trees (BTs) are great for a variety of applications and thrive within a vibrant community!  
+Kudos to [Petter Ögren's](https://www.kth.se/profile/petter/) crew, [Michele Colledanchise](https://miccol.github.io/behaviortrees/) and [Davide Faconti](https://github.com/facontidavide) 🖖
+
+But, Arbitration Graphs bring great value, especially for safety critical applications like self-driving cars and mobile robots in general – by strictly coupling preconditions to behaviors and tightly integrating behavior verification.
+A bit more in detail:
+
+|                   | Behavior Trees                                                                                                                 | Arbitration Graphs                                                                                                                                                                                                    |
+| ----------------- | ------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| **Interfaces**    | Nodes return execution status (*success*, *failure*, or *running*). <br>⏵ more flexibility w.r.t. a node's actuator interfaces | Behavior components & arbitrators return commands (e.g., a trajectory). <br>⏵ control theory motivated interface ${f(\boldsymbol{x}) \to \boldsymbol{u}}$ <br>⏵ command can be verified by each arbitrator            |
+| **Preconditions** | Implemented by condition nodes distributed throughout the tree. <br>⏵ easy to reuse preconditions for multiple behaviors       | Require behavior components to define their own preconditions. <br>⏵ tight coupling of preconditions to behaviors <br>⏵ robustness and safety less dependent on node arrangement                                      |
+| **Safety**        | Each node decides on its success or failure. <br>⏵ can lead to safety and reliability issues, if not carefully managed         | Integrate safety into the selection mechanism, using node-independent verifiers. <br>⏵ reduces the burden on behavior engineers <br>⏵ allows an easy integration of unsafe behavior components (ML, probabilistic, …) |
+
+</details>
+
 
 ## Demo
 

docs/_includes/head-custom.html

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docs/assets/css/style.scss

@@ -27,6 +27,14 @@ img.github-logo {
   content: url({{ "/docs/assets/img/github-mark.svg" | relative_url }});
 }
 
+.main-content table th, .main-content table td {
+  border: none;
+  border-bottom: 1px solid #ddd;
+}
+.main-content table tr:last-child td {
+  border: none;
+}
+
 // Improve collapsible sections
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   cursor: pointer;