Update schwager_23.md

_talks/schwager_23.md

@@ -5,7 +5,7 @@ website: "https://web.stanford.edu/~schwager/"
 date: 2023-09-29T12:30:00-0000
 location: Skilling Auditorium
 location-url: "https://campus-map.stanford.edu/?id=04-550&lat=37.42697371527761&lng=-122.17280664808126&zoom=18"
-title: "TBD"
-abstract: "TBD"
+title: "Perception-Rich Robot Autonomy with Neural Environment Models"
+abstract: "New developments in computer vision and deep learning have led to the rise of neural environment representations: 3D maps that are stored as deep networks that spatially register occupancy, color, texture, and other physical properties.  These environment models can generate photo-realistic synthetic images from unseen view points, and can store 3D information in exquisite detail.  In this talk, I investigate the questions: How can robots use neural environment representations for perception, motion planning, manipulation, and simulation?  I will present recent work from my lab in navigating a robot through a neural radiance field map of an environment while preserving safety guarantees.  I will talk about realtime NeRF training, where we produce a neural map online in a SLAM-like fashion.  I will also discuss open-vocabulary semantic navigation in a neural map, where we find or avoid objects specified at runtime.  I will present the concept of dynamics-augmented neural objects, which are assets captured from RGB images whose motion (including contact) can be simulated in a differentiable physics engine.  I will show how such models can be used in real-to-sim transfer and robot manipulation planning scenarios.  I will conclude with future opportunities and challenges in integrating neural environment representations into the robot autonomy stack."
 youtube-code: "TBD"
 ---