Session: ASME Undergraduate Student Design Expo

Paper Number: 176080

Development of an Automated Core Feeding and Collection System for Osiris: Onboard Soil In-Situ Robot-Assisted Intelligent System 

The OSIRIS: Onboard Soil In-situ Robot-assisted Intelligent System project introduces the development of an automated soil core feeding and collection system integrated with an Unmanned Ground Vehicle (UGV). Its primary objective is to automate soil sampling across large agricultural terrains, maximizing operational efficiency while reducing the need for human involvement.

Traditional methods rely on manual labor, where operators physically traverse fields to collect soil samples using augers, probes, or shovels. While effective, this approach is labor-intensive, inconsistent, and limited to smaller-scale applications. Soil sampling is critical for measuring key properties such as pH and organic matter, which guide fertilization strategies and help predict crop yields. The OSIRIS system addresses these limitations by combining autonomous navigation with roboticized sampling mechanisms, enabling continuous, precise, and independent field operation.

A central requirement of the system is the ability to handle multiple sampling events in one deployment. To achieve this, OSIRIS employs a modular device based on multiple actuators that facilitate coring motions. A spring loaded magazine stores up to 20-30 soil core tubes in a dual-lane format, while a drill carriage automatically retrieves and positions them for use, a snap-fit joint system allows rapid attachment and detachment of drill heads. This ensures quick replacement during sequential operations. Once a sample is collected, the core is deposited into an onboard belt-driven carousel via a button-triggered release, preserving its shape for laboratory analysis. This fully automated handoff reduces human handling, prevents sample damage, and ensures systematic labeling and storage.

Beyond hardware, autonomy is embedded at the system level. The UGV incorporates GPS, LiDAR, and onboard cameras for mapping, navigation, and obstacle avoidance. With these, the rover independently plans routes, identifies sampling points, and adapts to terrain variability. A high-level mission planner generates sampling grids or routing paths, while real-time control adjusts alignment and drilling precision at each site. This integration of autonomy ensures consistent sampling with minimal positional error, even in complex field environments.

The benefits of this automated framework extend across efficiency, reliability, and scalability. Automation enhances consistency by minimizing human error and creating repeatable, high-quality data sets. The ability to collect between 20 and 30 samples in one mission significantly improves spatial resolution, allowing for a nuanced understanding of soil variability and supporting more robust agricultural decision-making. Additionally, by reducing labor-intensive fieldwork, the system frees human operators to concentrate on data analysis and management rather than routine sample collection. The OSIRIS design also provides future scalability, given its modularity and robust snap-fit and belt magazine mechanisms that simplify maintenance and expansion.

In conclusion, the OSIRIS system represents a major advancement in soil sampling by merging mechanical innovation with robotic autonomy. It transitions sampling from a labor-intensive, inconsistent practice to a scalable process that operates independently across large landscapes. This shift offers not only higher-quality data and operational efficiency but also promotes sustainable agricultural and environmental practices.

Presenting Author: Maheen Madhi Rochester Institute of Technology

Presenting Author Biography: I am currently an undergraduate student studying Mechanical Engineering at Rochester Institute of Technology with hands-on experience as a researcher. On my most recent project I have focused on advancing manufacturing technologies by optimizing the plastic injection molding process through robotic integration. My work involved designing and implementing robotic systems to automate key stages of injection molding, improving production efficiency, consistency, and scalability. Currently working on a developing project on soil sampling rovers. The mission is to create an autonomous rover to help farmers test their fields efficiently and accurately, saving millions in the agriculture sector.

Authors:

Maheen Madhi Rochester Institute of Technology
Bell Muthukumaran Rochester Institute of Technology
Jeff Lancia Rochester Institute of Technology
Jun Han Bae Rochester Institute of Technology