arXiv (All)
open access
Terrain-Aided Navigation Without Raycasting: A Sliding Grid Approach for Point Cloud Processing
We investigate the use of a point cloud measurement in terrain-aided navigation. Our goal is to aid an inertial navigation system, by exploring ways to generate a useful measurement innovation error for effective nonlinear state estimation. We compare two such measurement models that involve the sca
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- \textbf{PLATO}: \emph{Preintegration Learning from Accurate Trajectory Observations} for Neural Inertial Odometry#974026
- RAEON: Rapid-Deployment Autonomous First-Response Observation Drone System (Technical Blueprint v1)#410728
- Online Learning via Learned Latent Bayesian Tracking#1106258
- A Unified Framework for Randomized Row-Action Methods for Structured Data Fitting and Constraint Geometry#1325660
- Uniqueness and stability of nonlinear filtering equations with unbounded random coefficients#1076641
Record · ID 1343444
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive