Splat-Nav: Safe Real-Time Robot Navigation in Gaussian Splatting Maps
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866910779923496960 |
|---|---|
| author | Chen, Timothy Shorinwa, Ola Bruno, Joseph Swann, Aiden Yu, Javier Zeng, Weijia Nagami, Keiko Dames, Philip Schwager, Mac |
| author_facet | Chen, Timothy Shorinwa, Ola Bruno, Joseph Swann, Aiden Yu, Javier Zeng, Weijia Nagami, Keiko Dames, Philip Schwager, Mac |
| contents | We present Splat-Nav, a real-time robot navigation pipeline for Gaussian Splatting (GSplat) scenes, a powerful new 3D scene representation. Splat-Nav consists of two components: 1) Splat-Plan, a safe planning module, and 2) Splat-Loc, a robust vision-based pose estimation module. Splat-Plan builds a safe-by-construction polytope corridor through the map based on mathematically rigorous collision constraints and then constructs a Bézier curve trajectory through this corridor. Splat-Loc provides real-time recursive state estimates given only an RGB feed from an on-board camera, leveraging the point-cloud representation inherent in GSplat scenes. Working together, these modules give robots the ability to recursively re-plan smooth and safe trajectories to goal locations. Goals can be specified with position coordinates, or with language commands by using a semantic GSplat. We demonstrate improved safety compared to point cloud-based methods in extensive simulation experiments. In a total of 126 hardware flights, we demonstrate equivalent safety and speed compared to motion capture and visual odometry, but without a manual frame alignment required by those methods. We show online re-planning at more than 2 Hz and pose estimation at about 25 Hz, an order of magnitude faster than Neural Radiance Field (NeRF)-based navigation methods, thereby enabling real-time navigation. We provide experiment videos on our project page at https://chengine.github.io/splatnav/. Our codebase and ROS nodes can be found at https://github.com/chengine/splatnav. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_02751 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Splat-Nav: Safe Real-Time Robot Navigation in Gaussian Splatting Maps Chen, Timothy Shorinwa, Ola Bruno, Joseph Swann, Aiden Yu, Javier Zeng, Weijia Nagami, Keiko Dames, Philip Schwager, Mac Robotics We present Splat-Nav, a real-time robot navigation pipeline for Gaussian Splatting (GSplat) scenes, a powerful new 3D scene representation. Splat-Nav consists of two components: 1) Splat-Plan, a safe planning module, and 2) Splat-Loc, a robust vision-based pose estimation module. Splat-Plan builds a safe-by-construction polytope corridor through the map based on mathematically rigorous collision constraints and then constructs a Bézier curve trajectory through this corridor. Splat-Loc provides real-time recursive state estimates given only an RGB feed from an on-board camera, leveraging the point-cloud representation inherent in GSplat scenes. Working together, these modules give robots the ability to recursively re-plan smooth and safe trajectories to goal locations. Goals can be specified with position coordinates, or with language commands by using a semantic GSplat. We demonstrate improved safety compared to point cloud-based methods in extensive simulation experiments. In a total of 126 hardware flights, we demonstrate equivalent safety and speed compared to motion capture and visual odometry, but without a manual frame alignment required by those methods. We show online re-planning at more than 2 Hz and pose estimation at about 25 Hz, an order of magnitude faster than Neural Radiance Field (NeRF)-based navigation methods, thereby enabling real-time navigation. We provide experiment videos on our project page at https://chengine.github.io/splatnav/. Our codebase and ROS nodes can be found at https://github.com/chengine/splatnav. |
| title | Splat-Nav: Safe Real-Time Robot Navigation in Gaussian Splatting Maps |
| topic | Robotics |
| url | https://arxiv.org/abs/2403.02751 |