A breakthrough in poultry processing automation has emerged as researchers at the University of Arkansas develop a robotic system that closely mimics human hand movements to perform the complex rehanging task in poultry plants.
Thank you for reading this post, don't forget to subscribe!The innovation is led by Dongyi Wang, Assistant Professor of Biological and Agricultural Engineering at the Arkansas Agricultural Experiment Station.
Human-Like Learning for Better Precision
Unlike traditional automation systems that rely on fixed mechanical patterns, this new robotic solution learns directly from human actions. By capturing real human movement data, the system adapts to variations in poultry size and carcass characteristics.
According to Wang, this approach allows the robot to respond more naturally and efficiently, similar to skilled human workers, rather than depending on rigid programmed movements.
Improving Worker Safety in Poultry Plants
The move toward robotics is driven by increasing concerns about worker health and safety. Poultry rehanging is performed in cold environments with repetitive motions over long shifts, often leading to musculoskeletal disorders among workers.
This robotic system is designed not to replace humans, but to support them by reducing physical strain and improving workplace conditions.
Introducing “ChicGrasp” – A Human-Like Robotic Hand
A key feature of the system is a specially designed two-jawed gripper called “ChicGrasp,” engineered to replicate the human grip on poultry drumsticks. This improves handling accuracy during the rehanging process and enhances operational efficiency.
Beyond Traditional Automation Limitations
Existing poultry automation technologies often assume uniform bird size, which is rarely the case in real-world operations. While some systems use sensors and cameras, they struggle to convert that data into precise robotic actions.
This new system bridges that gap by using imitation learning, enabling robots to adapt dynamically to variations just like human workers.
Current Challenges and Future Potential
Although the system has demonstrated promising results in research published in Advanced Robotics AI, it is not yet ready for commercial deployment.
One major challenge is speed, as the current system operates at only about 10% of the required industrial processing rate.
To accelerate development, the research team has made its code open access, allowing industry partners to build upon the technology using industrial-grade robotics.
Next Phase: Real-World Integration
The team is now working on integrating the system with moving conveyor belts, a critical requirement for real poultry processing lines.
They are also actively seeking industry collaboration to bring this technology closer to commercial use.
Funding and Support
The project is supported by a $1 million grant under the National Robotics Initiative 3.0, funded by the National Science Foundation and the USDA National Institute of Food and Agriculture.