add raven research post

Author: seungchan-kim

_posts/2026-01-31-raven.md

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+---
+layout: post
+title: "RAVEN: Resilient Aerial Navigation via Open-Set Semantic Memory and Behavior Adaptation"
+date: 2026-01-31 10:33:01
+categories: research
+description: "RAVEN is a 3D open-set memory-based behavior tree framework for aerial semantic outdoor navigation."
+author: "Seungchan Kim"
+published: true
+redirect: "https://raven-semantic.github.io/"
+show_sidebar: false
+# slim_content_width: true
+permalink: /raven/
+image: /img/posts/2026-01-31-raven/raven-teaser.gif
+datatable: true
+title_image: None
+hero_image: /img/posts/2026-01-31-raven/raven-teaser.gif
+hero_height: is-large
+remove_hero_title: false
+menubar_toc: false
+tags: Perception, Planning, Learning
+---
+
+RAVEN is a 3D open-set memory-based behavior tree framework for aerial semantic outdoor navigation. RAVEN not only navigates reliably toward detected targets, but also performs long-range reasoning to plan toward distant cues and continues informed search even when direct visual evidence is limited. It further supports multi-class object search and on-the-fly task switching within a mission.