Research

Peer Reviewed Publications

Sierra N. Young, Joshua M. Peschel, and Erkan Kayacan. (2018) “Design and Field Evaluation of a Ground Robot for High-Throughput Phenotyping of Energy Sorghum ”. Precision Agriculturehttps://doi.org/10.1007/s11119-018-9601-6.

Sierra N. Young and Joshua M. Peschel. (2018) “Human-Robot Interaction of Small, Manipulating Unmanned Aerial Systems ”. IEEE Transactions on Human-Machine Systems, under review.

Erkan Kayacan,  Sierra N. Young, Joshua Peschel, and Girish Chowdhary. (2018) “High Precision Control of Tracked Field Robots in the presence of Unknown Traction Coefficients”. Journal of Field Robotics, https://doi.org/10.1002/rob.21794

Gopal Penny, Veena Srinivasan, Apoorva R., Joshua M. Peschel,  Sierra N. Young, and Sally E. Thompson. (2018) “A Process-Based Hydrologic Reconstruction to Understand Streamflow Decline in a Human-Dominated Semiarid Catchment”. Hydrological Processes, under review.

Sierra N. Young, Joshua M. Peschel, Gopal Penny, Sally Thompson, and Veena Srinivasan. (2017). “Robot-Assisted Measurement for Hydrologic Understanding in Data Sparse Regions.” Water, 9(7).


Some of the completed research projects I’ve worked on are shown below.

Transportation Energy Resources from Renewable Agriculture – Mobile Energy-Crop Phenotyping Platform (TERRA-MEPP)
Cn-depcWYAEMQ1V While high throughput phenotyping platforms have been used in isolated growth chambers or greenhouses, there is a growing need for field-based platforms to measure large quantities of plants throughout the growing season at high spatial and temporal resolutions. During this project we developed and tested a low-cost, tracked mobile robot for phenotyping of energy sorghum named TERRA-MEPP (Transportation Energy Resources from Renewable Agriculture – Mobile Energy-Crop Phenotyping Platform ). I was involved with designing, developing, and continuously testing the first-generation prototype. Field testing demonstrated satisfactory field performance and illustrated benefits of the robot’s compact, variable design that can be used in different phenotyping applications which require views of the plant from in between the rows.
Linking Remote Sensing, Citizen Science, and Robotics to Address Critical Environmental Problems in Data Sparse Regions
  This work evaluated a team of two different robots, including an unmanned aerial vehicle (UAV) and an unmanned surface vehicle (USV), to collect hydrologic surface data utilizing sonar and visual sensors were conducted at three different field sites within the Arkavathy Basin river network located near Bangalore in Karnataka, South India. This new methodology collected storage capacity data at previously unmapped locations and revealed strong power-type relationships between surface area, stage, and storage volume, which can be incorporated into modeling of landscape-scale hydrology. Read the full paper here.
UILabs CityWorks Project: Smart Green Stormwater Infrastructure
Picture1 I worked on a one-year UILabs CityWorks project to quantitatively assess the effectiveness and performance of the design of green storm water infrastructure in the City of Chicago by deploying innovative sensors for five urban streetscapes. I served as a thought-leader on the technical aspects of this project, including the development of sensing methodology and instrumentation, system architecture, and monitoring success criteria. My involvement in this project resulted in the development of sensor packages to drive future green infrastructure design and investments and demonstrated the applicability and feasibility of the new sensing technology to monitor green infrastructure performance.
Chicago O’Hare International Airport Taxiway A and B Condition Assessment and Rehabilitation Strategies
Flight1_Orthophoto I worked on an interdisciplinary project team, along with the Center of Excellence for Airport Technology (CEAT) and O’Hare Modernization Program (OMP) to investigate and test the use of unmanned aerial vehicles to evaluate surface and subsurface drainage conditions of airport taxiways. Test flights were performed to demonstrate the value of image-based evaluation of pavement. Our test flights used a 3D Robotics Iris quadcopter and a high-resolution Sony camera, and Agisoft PhotoScan (commercially available photogrammetry software) was used for post-analyses.
Characterizing Stiffness Degradation in High Performance Welded Aluminum Structures
Screen Shot 2017-10-09 at 8.17.44 PM At Cornell University I conducted research under Professor Derek Warner to characterize stiffness degradation in high-performance welded aluminum structures. I assisted in conducting a full-scale horizontal fatigue test based on ASTM Standard F2711 to investigate the relationship between stiffness degradation and total number of load cycles using an Instron test system. Frame displacement and load data were collected at various time points via voltage calibrations and the use of a Linear Variable Differential Transformer (LVDT). After 1.2 million, displacement controlled, loading cycles the stiffness appeared to degrade in a decreasing linear relationship between stiffness and total number of load cycles.