Modeling Performance of a Stereo Camera Sensor for Optimization

Lei, Zike; Chen, Xiang; Chen, Xi; Chai, Lu

doi:10.1109/aim43001.2020.9158865

Cited by 5 publications

(2 citation statements)

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“…For example, at some time instants, the camera can cover less than 8(10%) landmarks, which greatly impacts the performance of the visual observer. This indicates that the position and orientation of landmarks play an important role in the visual observer on SE(3) in (2), which motivates the work of landmark deployment.…”

Section: A a Motivating Examplementioning

confidence: 79%

“…This subsection compares the performance of the visual observer on SE(3) (see (2)) by using three landmark deployment settings: the optimized deployment, uniform deployment, and random deployment. To test the landmark information that the camera can capture in various positions and orientations, the camera is set to perform random movement in the reachable area for a sufficient time, such that the camera can collect enough data for analysis.…”

Section: B Simulation Results Of Visual Observer On Se(3)mentioning

confidence: 99%

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

Lei¹,

Chen²,

Tan³

et al. 2022

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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.

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Section: A a Motivating Examplementioning

confidence: 79%

Section: B Simulation Results Of Visual Observer On Se(3)mentioning

confidence: 99%