# Low-Cost Optical–Inertial Point Cloud Acquisition and Sketch System

## TL;DR

A low-cost system combines optical and inertial sensors to capture 3D point clouds and sketches of objects efficiently.

## Contribution

A novel low-cost optical-inertial system for 3D point cloud acquisition with efficient algorithms and real-time visualization.

## Key findings

- The system achieves 4.7% maximum error on 2D planes with 2.1% RMS error.
- For 3D objects, the maximum error is 5.3% with 2.4% RMS error.
- The system is suitable for large-sized 3D objects and offers real-time scanning visualization.

## Abstract

This paper proposes an optical three-dimensional (3D) point cloud acquisition and sketching system, which is not limited by the measurement size, unlike traditional 3D object measurement techniques. The system employs an optical displacement sensor for surface displacement scanning and a six-axis inertial sensor (accelerometer and gyroscope) for spatial attitude perception. A microprocessor control unit (MCU) is responsible for acquiring, merging, and calculating data from the sensors, converting it into 3D point clouds. Butterworth filtering and Mahoney complementary filtering are used for sensor signal preprocessing and calculation, respectively. Furthermore, a human–machine interface is designed to visualize the point cloud and display the scanning path and measurement trajectory in real time. Compared to existing works in the literature, this system has a simpler hardware architecture, more efficient algorithms, and better operation, inspection, and observation features. The experimental results show that the maximum measurement error on 2D planes is 4.7% with a root mean square (RMS) error of 2.1%, corresponding to the reference length of 10.3 cm. For 3D objects, the maximum measurement error is 5.3% with the RMS error of 2.4%, corresponding to the reference length of 9.3 cm. Finally, it was verified that this system can also be applied to large-sized 3D objects for outlines.