Designing an Autonomous Robot for Monitoring Open-Mouth Behavior of Chickens in Commercial Chicken Farms
Journal
Journal of the ASABE
Journal Volume
68
Journal Issue
1
Start Page
25-36
ISSN
2769-3287
Date Issued
2025
Author(s)
DOI
10.13031/ja.16056
Abstract
In the conventional management of commercial floor-rearing chicken farms, farmers regularly patrol to observe chicken status and to check the environment. For countries with a subtropical climate (e.g., Taiwan), heat stress (HS) is a common environmental stressor for chickens due to high temperature and humidity. Open-mouth behavior (OMB) of chickens is an indicator of HS and is closely monitored in patrols. Manual patrols are laborious and time-consuming. Moreover, frequent patrols may increase the risk of pathogen spread while entering and exiting chicken farms. Therefore, this study developed a mobile robot to autonomously patrol in chicken farms and to automatically monitor OMB of chickens. Considering the commercial chicken farms in Taiwan usually have narrow aisles between feed buckets, a compact robot was designed. An ultra-wideband (UWB) module was utilized to localize the mobile robot. The mobile robot performed navigation and obstacle avoidance using a depth camera and the navigation stack of the Robot Operating System (ROS). For monitoring OMB of chickens, an image acquisition component was developed to acquire chicken images. A YOLO v7 model was trained to detect the chickens with OMB in the collected images. Subsequently, OMB ratios, defined as the ratios of chickens with OMB, were calculated to quantify this behavior. Experimental results showed that the mean absolute error of the UWB was 0.17 m in robot localization, complying with the requirements for navigating the robot in the narrow aisles of chicken farms. The trained YOLO v7 model achieved an average precision of 86.1%. Experimental results indicated that the mean OMB ratios between summer and winter were significantly different. In addition, the OMB ratio and temperature in summer were found to be moderately and positively correlated, indicating that OMB ratio was an effective indicator to represent chicken behaviors under different temperatures. The developed mobile robot provides a solution to automate the regular patrols performed by chicken farmers.
Subjects
Deep learning
Depth image
Heat stress
Indoor positioning
Ultra-wideband (UWB)
Unmanned vehicle
Publisher
American Society of Agricultural and Biological Engineers (ASABE)
Type
journal article