Optimization Solution of Laser Plane Generated from Maximum Likelihood Estimation of Projection Plane

doi:10.18494/sam.2018.1665

Abstract

Highlights

Laser planes demonstrate remarkable applications in robotic automation, position detection, and profile meters.[1,2,3] The accurate coordinates of the laser plane are a key point of the measurement precision in active vision.[4,5] Researchers have developed many approaches to obtain the coordinates of the laser plane
On the basis of the dimensions of the target used in the solution process, the solution methods in the active vision are approximately divided into 3D, 2D, and 1D target-based solution methods.[6,7,8,9,10] The 2D planar target is chosen to obtain the laser plane because of the simple operation and abundant information on the target
A camera with 512 × 384 image resolution and a 160 × 160 mm2 target with a 10 × 10 mm2 checkerboard pattern are employed to examine the performance of the proposed maximum likelihood estimation (MLE) method

Summary

Introduction

Laser planes demonstrate remarkable applications in robotic automation, position detection, and profile meters.[1,2,3] The accurate coordinates of the laser plane are a key point of the measurement precision in active vision.[4,5] Researchers have developed many approaches to obtain the coordinates of the laser plane. Xu et al employed a 2D target and solved the laser plane by the Plücker matrices of the projection laser lines.[20] Another method employing a 3D target and the distance between the global origin and the point on the laser plane is reported in the previous work.[21] The existing 2D target solution methods utilize the cross ratio invariability or Plücker matrix to construct the coordinates of a laser plane.[22] As the Plücker matrix directly presents the 3D projection laser line on the target, the measurement technique with the Plücker matrix is considered to be the better method to obtain the laser plane. The solution of the laser plane is enhanced by optimizing the logarithmic likelihood function theoretically and experimentally

Solution Model

Experimental Results and Analysis

Conclusion