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Insect-controlled Robot: A Mobile Robot Platform to Evaluate the Odor-tracking Capability of an Insect

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Visual Navigation of Caged Chicken Coop Inspection Robot Based on Road Features.

Hongfeng Deng^1,2, Tiemin Zhang^1,2,3, Kan Li^1,2

¹State Key Laboratory of Swine and Poultry Breeding Industry, South China Agricultural University, Guangzhou 510642, China.

Animals : an Open Access Journal From MDPI

|September 14, 2024

Summary

This summary is machine-generated.

A new visual navigation system for chicken coop robots offers faster, more accurate road extraction. This enhances inspection efficiency and stability, promoting automated large-scale poultry farming.

Keywords:

cage chicken coop inspection robot road features visual navigation

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Area of Science:

Agricultural Engineering
Robotics
Computer Vision

Background:

Inspection robots in cage chicken coops require accurate navigation for efficient monitoring.
Current navigation methods face challenges in speed, accuracy, and driving stability.

Purpose of the Study:

To develop a novel visual navigation system for enhancing the inspection accuracy of cage chicken coop robots.
To improve the speed and stability of road extraction and robot navigation.

Main Methods:

Proposed a new grayscale factor (4B-3R-2G) for rapid and precise road extraction.
Developed a navigation line fitting algorithm utilizing road boundary features for enhanced stability.
Implemented and tested a visual navigation system, comparing its performance against inertial navigation.

Main Results:

The proposed grayscale factor achieved 92.918% segmentation accuracy, six times faster than deep learning models.
Visual navigation demonstrated high accuracy (max deviation 4 cm, avg 1.561 cm) and stability (max acceleration 1.122 m/s², avg 0.292 m/s²).
Inspection detection number and accuracy increased by 21.125% and 1.228%, respectively, with visual navigation.

Conclusions:

The developed visual navigation system significantly improves robot navigation accuracy and driving stability.
This system enhances inspection efficiency and effect, reducing operational costs for large-scale poultry farming.
The technology is crucial for advancing automation and rapid monitoring in cage chicken breeding.