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Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
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Published on: August 29, 2025

CVIWM: A Tightly Coupled State Estimation Method for Poultry House Inspection Robots in Structurally Degraded

Hongfeng Deng1,2, Canhuan Lu1,2, Jiacheng Jiang1,2

  • 1College of Engineering, South China Agricultural University, Guangzhou 510642, China.

Animals : an Open Access Journal From MDPI
|June 26, 2026
PubMed
Summary
This summary is machine-generated.

Accurate robot positioning in chicken houses is achieved using a new method called Coupled Visual-Inertial-Wheel Odometry with Markers (CVIWM). This system enables precise navigation for automated poultry inspection tasks.

Keywords:
AprilTagmulti-sensor fusionpoultry house inspection robotstate estimationtight coupling

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Area of Science:

  • Robotics
  • Computer Vision
  • Sensor Fusion

Background:

  • Accurate robot positioning is critical for automated inspection in environments like caged chicken houses.
  • Challenges include long corridors, sparse textures, and repetitive structures that hinder conventional positioning methods.

Purpose of the Study:

  • To develop and evaluate a novel, tightly coupled state estimation method for precise robot localization in caged chicken houses.
  • To improve the accuracy and reliability of automated poultry inspection systems.

Main Methods:

  • Proposed CVIWM (Coupled Visual-Inertial-Wheel Odometry with Markers), a factor graph optimization framework fusing visual, IMU, wheel odometry, and AprilTag marker data.
  • Utilized wheel odometry preintegration to mitigate IMU drift and establish absolute scale.
  • Employed sparse AprilTag markers for periodic error correction.

Main Results:

  • CVIWM achieved average positioning errors of 2.402 cm and 3.253 cm at different speeds in an 80 m commercial chicken house corridor.
  • High positioning accuracy enabled reliable image acquisition with minimal image shift (<83 pixels).
  • Facilitated high detection rates: 95.7% for dead hens and 98.9% for eggs.

Conclusions:

  • CVIWM provides a low-cost, easily deployable, and highly accurate solution for automated poultry house inspection.
  • The system supports the advancement of smart livestock farming through precise robotic navigation and data acquisition.