Published April 8, 2024
| Accepted
Journal Article
Open
CATNIPS: Collision Avoidance Through Neural Implicit Probabilistic Scenes
Abstract
We introduce a transformation of a Neural Radiance Field (NeRF) to an equivalent Poisson Point Process (PPP). This PPP transformation allows for rigorous quantification of uncertainty in NeRFs, in particular, for computing collision probabilities for a robot navigating through a NeRF environment. The PPP is a generalization of a probabilistic occupancy grid to the continuous volume and is fundamental to the volumetric ray-tracing model underlying radiance fields. Building upon this PPP representation, we present a chance-constrained trajectory optimization method for safe robot navigation in NeRFs. Our method relies on a voxel representation called the Probabilistic Unsafe Robot Region (PURR) that spatially fuses the chance constraint with the NeRF model to facilitate fast trajectory optimization. We then combine a graph-based search with a spline-based trajectory optimization to yield robot trajectories through the NeRF that are guaranteed to satisfy a user-specific collision probability. We validate our chance constrained planning method through simulations and hardware experiments, showing superior performance compared to prior works on trajectory planning in NeRF environments.
Copyright and License
© 2024 IEEE.
Acknowledgement
The NASA University Leadership Initiative (grant #80NSSC20M0163) provided funds to assist the authors with their research, but this article solely reflects the opinions and conclusions of its authors and not any NASA entity. Toyota Research Institute provided funds to support this work. The first author was supported by a NASA NSTGRO Fellowship, and the second author was supported on a NASA NSTRF Fellowship.
We would like to thank Keiko Nagami, Adam Caccavale, Gadi Camps, and Jun En Low for their insights throughout this project.
Code Availability
Our code can be found at https://github.com/chengine/catnips.
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CATNIPS_Collision_Avoidance_Through_Neural_Implicit_Probabilistic_Scenes.pdf
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Additional details
- ISSN
- 1941-0468
- National Aeronautics and Space Administration
- 80NSSC20M0163
- Toyota Research Institute
- National Aeronautics and Space Administration
- NASA Space Technology Graduate Research Opportunities
- National Aeronautics and Space Administration
- NASA Space Technology Research Fellowship
- Caltech groups
- Center for Autonomous Systems and Technologies (CAST)