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Automatic Walking Method of Construction Machinery Based on Binocular Camera Environment Perception.

Zhen Fang^1,2, Tianliang Lin^1,2, Zhongshen Li^1,2

¹College of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, China.

|May 28, 2022

Summary

This study introduces an automated walking system for construction machinery using binocular cameras for environmental perception and control. The system enables safe and smooth autonomous navigation for heavy equipment.

Keywords:

binocular detection construction machinery end-to-end ranging unmanned driving

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Area of Science:

Robotics and Automation
Computer Vision
Machine Learning

Background:

Construction machinery operation often requires human operators, posing safety risks and limiting efficiency.
Autonomous systems can enhance safety, precision, and operational efficiency in construction environments.

Purpose of the Study:

To develop an end-to-end automatic walking system for construction machinery.
To enable autonomous navigation and environmental perception for heavy equipment.

Main Methods:

Utilized binocular cameras for environmental perception and image capture.
Developed a binocular recognition ranging model for object detection and distance estimation (within 5m).
Implemented a control model integrating distance, image features, and previous control signals for real-time prediction.

Main Results:

The recognition ranging model accurately detected and ranged objects within 5 meters.
The integrated system successfully controlled construction machinery for autonomous walking tasks.
Demonstrated smooth and safe operation in a specific experimental scenario.

Conclusions:

The proposed system effectively enables autonomous walking for construction machinery.
The system enhances environmental perception and control for safe operation.
This technology has the potential to improve safety and efficiency in construction automation.