A Prototype Harvesting Solution for White Button Mushrooms Using Collaborative Robotics
Standing
Undergraduate
Type of Proposal
Oral Research Presentation
Challenges Theme
Open Challenge
Faculty Sponsor
Dr. Urbanic and Dr. Kim
Proposal
Smart manufacturing tools and advanced design provide a foundation for building a resilient infrastructure, promoting sustainable industrialization, and fostering innovation. These core values are emphasized in accordance with UNSDG 9 and are factored into the design of automation strategies for agricultural challenges. Mushroom harvesting is a labour-intensive process. Implementing intelligent automation can improve picking cycle times and reduce work related musculoskeletal disorders caused by repetitive movements and awkward postures. This research prototypes a robotic harvesting solution for white button mushrooms to address these matters. Methodologies employed fall under three streams: constraint analysis, gripper systems design and, simulation and validation. The fungi growth cycle, bruising characteristics, picking motion dynamics and stem slicing aspects were all considered. In lab, compression loads were incrementally applied to mushrooms until visible bruising or damage occurred. A force measurement glove was used to collect data from harvesters at a mushroom farm to determine the average picking force exerted on mushrooms. Computer vision-based motion analysis was performed to define picking dynamics. Several compliant grippers were designed, simulated in Autodesk Inventor Nastran, and realized via 3D printing. Prototypes underwent durability testing using iterative cycle counts of 100 as well as moisture absorption testing to study performance in high humidity. A collaborative robot with specialty end of arm tooling was explored to harvest mature mushrooms from a selected area, validating the automation strategy. This system repeatedly located, picked, and placed mushrooms without damage. Future work includes a decision-making algorithm for mushroom grading pre-harvest and refinement of gripper tips.
Grand Challenges
Viable, Healthy and Safe Communities
A Prototype Harvesting Solution for White Button Mushrooms Using Collaborative Robotics
Smart manufacturing tools and advanced design provide a foundation for building a resilient infrastructure, promoting sustainable industrialization, and fostering innovation. These core values are emphasized in accordance with UNSDG 9 and are factored into the design of automation strategies for agricultural challenges. Mushroom harvesting is a labour-intensive process. Implementing intelligent automation can improve picking cycle times and reduce work related musculoskeletal disorders caused by repetitive movements and awkward postures. This research prototypes a robotic harvesting solution for white button mushrooms to address these matters. Methodologies employed fall under three streams: constraint analysis, gripper systems design and, simulation and validation. The fungi growth cycle, bruising characteristics, picking motion dynamics and stem slicing aspects were all considered. In lab, compression loads were incrementally applied to mushrooms until visible bruising or damage occurred. A force measurement glove was used to collect data from harvesters at a mushroom farm to determine the average picking force exerted on mushrooms. Computer vision-based motion analysis was performed to define picking dynamics. Several compliant grippers were designed, simulated in Autodesk Inventor Nastran, and realized via 3D printing. Prototypes underwent durability testing using iterative cycle counts of 100 as well as moisture absorption testing to study performance in high humidity. A collaborative robot with specialty end of arm tooling was explored to harvest mature mushrooms from a selected area, validating the automation strategy. This system repeatedly located, picked, and placed mushrooms without damage. Future work includes a decision-making algorithm for mushroom grading pre-harvest and refinement of gripper tips.