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Project # 63
A Multimodal Sensor System for Robot Localization, Mapping, and Monitoring in Cotton Fields

Team Lead: Chandler Wilson
Other Team Members:
Faculty Advisor(s): William Beksi
Department: CSE
Project Type: REU
Title: A Multimodal Sensor System for Robot Localization, Mapping, and Monitoring in Cotton Fields
Abstract: This research project focuses on developing and implementing a multimodal sensor system for a Clearpath Husky unmanned ground vehicle (UGV) to advance automated agricultural phenotyping. The system integrates diverse sensing capabilities, including an EVK4 neuromorphic camera, stereo RGB cameras, and LiDAR for comprehensive environmental perception. Navigational sensors, including wheel odometry, IMU, and RTK-GPS, provide centimeter-level positioning, while a long-range wireless system enables remote operation and data collection. Working in collaboration with the USDA, Stiles Farm, and Cotton Incorporated, we are applying this technology to systematically monitor cotton crops throughout the growing season in Texas, capturing repeated measurements to track plant development over time. The project encompasses three phases: optimal sensor mounting and hardware fixturing, ROS-based software integration, and field data collection. This automated approach addresses the challenges of traditional manual phenotyping methods, particularly for consistent long-term monitoring. The resulting framework will facilitate rapid identification and screening of genetically diverse, high-yielding, heat and drought-tolerant cotton varieties. Furthermore, the collected multimodal datasets and developed software will be publicly released to support broader research in robotics and computer vision, including applications in localization, mapping, scene understanding, and multimodal learning.
Poster: View Poster #63 (PDF)
Judges Scoring: Submit Evaluation (judges only)