Center for Digital Agriculture

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Projects

Title: Advancing AI for Learning to Navigate Agricultural Fields Autonomously
Team: Dr. Girish Chowdhary, Dr. Saurabh Gupta, Dr. Alexander Schwing, Dr. Adam Davis, Dr, Bruno Basso (Michigan State University), and Dr. DoKyoung (DK) Lee
Goals: To enable Level 5 autonomous field navigation of mobile robots using AI to drive down cost.

 

Title: Advancing Robot Perception, Planning, and Control for Plant Manipulation
Team: Dr. Girish Chowdhary, Dr. Kris Hauser, Dr. Girish Krishnan and Dr. Todd Mockler (Donald Danforth Plant Science Center)
External Collaborators: Kevin Wolz (Savanna Institute)
Goals: To enable robots to understand and manipulate plants for sampling, harvesting, and pruning.

 

Title: Natural Language Communication, Knowledge Acquisition and Reasoning for Ag Robots
Team: Dr. Katherine Driggs-Campbell, Dr. Heng Ji, Dr. Julia Hockenmaeir, Dr. Girish Chowdhary and Dr. Madhu Khanna
Goals: To enable agbots to understand, communication, and reason through natural language for human-robot teams

 

Title: Federated ML for Adaptive Reinforcement Learning across Farm Robots
Team: Dr. Sanmi Koyejo, Dr. Girish Chowdhary, Dr. Paris Smaragdis and Dr. Vikram Adve
External collaborators: Indranil Gupta (Illinois), Mladen Kolar (University of Chicago)
Goals: To leverage federated ML to reduce communication overhead compared to collecting all the data in a single location, to enable robots to better adapt to dynamic environments, and to leverage data across farms.

 

Title: CPS: Frontier: Collaborative Research COALESCE: Context Aware Learning for Sustainable Cyber-Agricultural Systems (Joint with Iowa State University)
Illinois Project Director: Dr. Girish Chowdhary
Goals: This project seeks to transform agriculture by developing a novel, context-aware cyber-agricultural system that encompasses sensing, modeling, and actuation to enable farmers to respond to crop stressors with lower cost, greater agility, and significantly lower environmental impact than current practices. The technical objectives are to create better AI for individualized plant health estimation, to implement data-driven, multi-scale planning and reasoning, and to develop individualized sensing and actuation via autonomous robots with dexterous manipulators.

 

Title: NRI: INT: Increasing the Level of Autonomy for Agricultural Robots Through Effective Interaction and Programming Paradigms
Team: Dr. Katie Driggs-Campbell (PI), Dr. Girish Chowdhary, Dr. Roy Dong, Dr. Sasa Misailovic, Dr. Sayan Mitra
Goals: This project will enable agricultural robots to autonomously perform crop scouting tasks with minimal interventions, while being remotely supervised by farmers. These robots will be resilient on the field through improved contextual awareness and runtime monitoring, which will allow users to command larger fleets of robots dispersed across the fields. Our work will be evaluated on an experimental farm and we will work closely with farmers to remove barriers to adoption. The team brings together expertise from agricultural field robotics, verification and validation, and human behavioral modeling

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