# Optimization of Directional Landmark Deployment for Visual Observer on SE(3)

arXiv: https://arxiv.org/abs/2203.14485 · HTML: https://mlsanity.com/paper/2203.14485/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 38 references that are in the map.
- First posted on arXiv 28 Mar 2022.

## Builds on (most cited first, 2 of 2)

- [Global visual localization in LiDAR-maps through shared 2D-3D embedding space](https://mlsanity.com/paper/1910.04871/) (2019)
- [Gradient-like observer design on the Special Euclidean group SE(3) with system outputs on the real projective space](https://mlsanity.com/paper/1505.05450/) (2015)

## Built on by (most cited first, 1 of 1)

- [Optimizing Fiducial Marker Placement for Improved Visual Localization](https://mlsanity.com/paper/2211.01513/) (2022)

## Abstract (arXiv)

An optimization method is proposed in this paper for novel deployment of given number of directional landmarks (location and pose) within a given region in the 3-D task space. This new deployment technique is built on the geometric models of both landmarks and the monocular camera. In particular, a new concept of Multiple Coverage Probability (MCP) is defined to characterize the probability of at least n landmarks being covered simultaneously by a camera at a fixed position. The optimization is conducted with respect to the position and pose of the given number of landmarks to maximize MCP through globally exploration of the given 3-D space. By adopting the elimination genetic algorithm, the global optimal solutions can be obtained, which are then applied to improve the convergent performance of the visual observer on SE(3) as a demonstration example. Both simulation and experimental results are presented to validate the effectiveness of the proposed landmark deployment optimization method.