nabo is a fast K Nearest Neighbour (KNN) library for low-dimensional spaces. It is a re-implementation in pure Rust of the C++ library of the same name by its original author. This work has been sponsored by Enlightware GmbH.
To use nabo in your project, you need to implement the nabo::Point trait for your point type.
You can see an example in src/dummy_point which is available when nabo is compiled with the dummy_point feature (default).
If you want to avoid a dependency to rand, disable the dummy_point feature.
You can benchmark nabo using the following command:
cargo bench
If you use nabo in the academic context, please cite this paper that evaluates its performances in the context of robotics mapping research:
@article{elsebergcomparison,
title={Comparison of nearest-neighbor-search strategies and implementations for efficient shape registration},
author={Elseberg, J. and Magnenat, S. and Siegwart, R. and N{\"u}chter, A.},
journal={Journal of Software Engineering for Robotics (JOSER)},
pages={2--12},
volume={3},
number={1},
year={2012},
issn={2035-3928}
}
Licensed under either of
- Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)
at your option.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this project by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.