A LIDAR-Based Tree Canopy Characterization under Simulated Uneven Road Condition: Advance in Tree Orchard Canopy Profile Measurement

Abstract EN

In real outdoor canopy profile detection, the accuracy of a LIDAR scanner to measure canopy structure is affected by a potentially uneven road condition.

The level of error associated with attitude angles from undulations in the ground surface can be reduced by developing appropriate correction algorithm.

This paper proposes an offline attitude angle offset correction algorithm based on a 3D affine coordinate transformation.

The validity of the correction algorithm is verified by conducting an indoor experiment.

The experiment was conducted on an especially designed canopy profile measurement platform.

During the experiment, an artificial tree and a tree-shaped carved board were continuously scanned at constant laser scanner travel speed and detection distances under simulated bumpy road conditions.

Acquired LIDAR laser scanner raw data was processed offline by exceptionally developed MATLAB program.

The obtained results before and after correction method show that the single attitude angle offset correction method is able to correct the distorted data points in tree-shaped carved board profile measurement, with a relative error of 5%, while the compound attitude angle offset correction method is effective to reduce the error associated with compound attitude angle deviation from the ideal scanner pose, with relative error of 7%.