LiDAR-based Object Dimension and Volume Estimation

This repository contains the exploratory project report titled "Use of LiDAR Technology for Determination of Volume and Dimensions of Objects" conducted by Aadarsh Kumar, Vaatsalya Sinha, Harsh Kumar, and Sangle Nilesh Ganesh under the guidance of Dr. Kishor P. Sarawadekar at the Department of Electronics Engineering, IIT (BHU) Varanasi.

Abstract

The project aims to automate the determination of dimensions and volume of objects using LiDAR technology. The proposed system utilizes a single RPLiDAR and various approaches to calculate dimensions and volume accurately and efficiently. The system's average error is around 3% in dimension estimation.

Problem Statement

In Industry 4.0 logistics systems, accurate measurement of object dimensions and volume is crucial for efficient and safe transportation. Traditional manual methods are slow and prone to errors. This project addresses the need for an automated and precise solution using LiDAR technology.

Approaches

Five approaches were explored for dimension and volume estimation:

1. Using two perpendicularly oriented RPLiDARs
2. Combining one RPLiDAR and a web camera
3. Utilizing one RPLiDAR and a conveyor belt
4. Incorporating one RPLiDAR and a stepper motor
5. Employing one RPLiDAR and a servo motor

Results and Conclusion

Among the explored approaches, Approach 5 (Using one RPLiDAR and a Servo Motor) was found to be the most effective. It allows for both stationary and moving object measurements and offers good accuracy. The proposed system offers significant potential for industrial applications, especially in automated warehousing and logistics.

Repository Contents

• Code: Implementation of the proposed methodologies
• Documentation: Detailed documentation and reports of the project
• References: Relevant literature and resources used in the project

Usage

1. Clone this repository: `git clone https://github.com/Azazel0203/Volume_estimation.git'
2. Navigate to the desired approach's code directory
3. Follow the instructions in the documentation to set up and run the code
4. Analyze the results and adapt the methodology for specific use cases

Acknowledgments

We would like to express our sincere gratitude to Dr. Kishor P. Sarawadekar for his guidance and support throughout this project.

Contributors

• Aadarsh Kumar
• Vaatsalya Sinha
• Harsh Kumar
• Sangle Nilesh Ganesh