[docs]: update doc

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-            <h1 class="title is-2 publication-title">FC-Planner: A Skeleton-guided Planning Framework for Fast Aerial Coverage of Complex 3D Scenes</h1>
+            <h1 class="title is-1 publication-title">⚽ FC-Planner</h1>
+            <h1 class="title is-2 publication-title">A Skeleton-guided Planning Framework for Fast Aerial Coverage of Complex 3D Scenes</h1>
             <div class="is-size-5 publication-authors">
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@@ -153,24 +154,17 @@ <h2 class="subtitle has-text-centered">
         <h2 class="title is-3">Abstract</h2>
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           <p>
-            3D coverage path planning for UAVs is a crucial
-            problem in diverse practical applications. However, existing
-            methods have shown unsatisfactory system simplicity, computation efficiency, and path quality in large and complex
-            scenes. To address these challenges, we propose FC-Planner,
-            a skeleton-guided planning framework that can achieve fast
-            aerial coverage of complex 3D scenes without pre-processing.
-            We decompose the scene into several simple subspaces by a
-            skeleton-based space decomposition (SSD). Additionally, the
-            skeleton guides us to effortlessly determine free space. We
-            utilize the skeleton to efficiently generate a minimal set of
-            specialized and informative viewpoints for complete coverage. Based on SSD, a hierarchical planner effectively divides
-            the large planning problem into independent sub-problems,
-            enabling parallel planning for each subspace. The carefully
-            designed global and local planning strategies are then incorporated to guarantee both high quality and efficiency in
-            path generation. We conduct extensive benchmark and realworld tests, where FC-Planner computes over 10 times faster
-            compared to state-of-the-art methods with shorter path and
-            more complete coverage. The source code will be open at
-            https://github.com/HKUST-Aerial-Robotics/FC-Planner.
+            3D coverage path planning for UAVs is a crucial problem in diverse practical applications.
+            However, existing methods have shown unsatisfactory system simplicity, computation efficiency, and path quality in large and complex scenes.
+            To address these challenges, we propose <strong>FC-Planner</strong>, a skeleton-guided planning framework that can achieve fast aerial coverage of complex 3D scenes without pre-processing.
+            We decompose the scene into several simple subspaces by a skeleton-based space decomposition (SSD).
+            Additionally, the skeleton guides us to effortlessly determine free space.
+            We utilize the skeleton to efficiently generate a minimal set of specialized and informative viewpoints for complete coverage.
+            Based on SSD, a hierarchical planner effectively divides the large planning problem into independent sub-problems, enabling parallel planning for each subspace.
+            The carefully designed global and local planning strategies are then incorporated to guarantee both high quality and efficiency in path generation.
+            We conduct extensive benchmark and real-world tests, where <strong>FC-Planner</strong> computes over 10 times faster compared to state-of-the-art methods with shorter path and more complete coverage. 
+            The source code will be made publicly available to benefit the community at https://github.com/HKUST-Aerial-Robotics/FC-Planner.
+            Project page: https://hkust-aerial-robotics.github.io/FC-Planner.
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@@ -385,9 +379,7 @@ <h2 class="title">BibTeX</h2>
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           <p>
-            This page was built using the <a href="https://github.com/eliahuhorwitz/Academic-project-page-template" target="_blank">Academic Project Page Template</a> which was adopted from the <a href="https://nerfies.github.io" target="_blank">Nerfies</a> project page.
-            You are free to borrow the of this website, we just ask that you link back to this page in the footer. <br> This website is licensed under a <a rel="license"  href="http://creativecommons.org/licenses/by-sa/4.0/" target="_blank">Creative
-            Commons Attribution-ShareAlike 4.0 International License</a>.
+            This page was built using the <a href="https://github.com/eliahuhorwitz/Academic-project-page-template" target="_blank">Academic Project Page Template</a> which was adopted from the <a href="https://nerfies.github.io" target="_blank">Nerfies</a> project page. This page is designed by <a href="https://chen-albert-feng.github.io/AlbertFeng.github.io/" target="_blank">Chen Feng</a>. 
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