Multidimensional materials sensing systems and methods

Abstract

Multidimensional Light Imaging, Detection, and Ranging (LIDAR) systems and methods optionally include a laser device configured to generate a plurality of light pulses emitted towards an object, a detector configured to receive a portion of the plurality of light pulses returned from the object, and a processor configured to generate a point cloud representing the object based on the plurality of light pulses received by the detector, the point cloud having a plurality of points, each point having a three- dimensional positional coordinate representing a location of the point on the object and having at least one additional value representing at least one of material information indicating a material of the object at the location of the point on the object or optical information indicating at least one optical characteristic of the plurality of light pulses returned from the surface of the object from the location of the point on the object.

Description

[0001] Cross References to Related Applications [0002] This application claims the benefit of U.S. Provisional Application No. 62 / 835,256, filed April 17, 2019. The entire disclosure of the above application is incorporated herein by reference. technical field [0003] The present disclosure relates to material sensing systems and methods, and more particularly, to multi-dimensional material sensing systems and methods for making and using these systems. Background technique [0004] This section provides background information related to the present disclosure which is not necessarily prior art. [0005] LIDAR is a surveying method that measures the distance to an object by illuminating the object with pulsed laser light and measuring the reflected pulse with a sensor. The difference in laser return time and wavelength can then be used to make a digital 3D representation of the detected object. LIDAR can be used to produce high-resolution maps and has applications in g...

AI Technical Summary

Problems solved by technology

In addition, conventional LIDAR hardware makes adequate object recognition and classification more difficult because current beam steering methods cause clustering and grouping of points in the LIDAR cloud, which leads to ambiguous interpretation of the 3D image and its individual points

Therefore, perception of the surrounding environment based on geometric shapes requires high computational cost, high energy consumption and long processing time

Images