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Algorithms and Methods for Simplifying Autonomy for Field Robots

Project Team

  • Dr. Katherine Driggs-Campbell, Assistant Professor, Dept. of Electrical and Computer Engineering
  • Dr. Sasa Misailovic, Assistant Professor, Dept. of Computer Science
  • Dr. Sayan Mitra, Associate Professor, Dept. of Electrical and Computer Engineering
  • Dr. Girish Chowdhary, Assistant Professor, Dept. of Agricultural and Biological Engineering

Abstract

The ability of a farmer to program a team of robots to accomplish complicated tasks over long-durations in harsh, uncertain, and time-varying field environments will be critical to realizing the digital farm of the future. On a digital farm of the future, farmers will have at their command a massively distributed and highly automated teams of small below-canopy robots, large over-the-canopy equipment, aerial vehicles, and static-sensors. Yet, the farmer’s task will be what it has always been: command the resources at hand to optimally manage thousands of acres of crops reliably, effectively, efficiently, profitably, and securely. We envision a far higher level of autonomy, where a distributed team of automated agricultural equipment can be assigned a series of interdependent tasks over massive spatial and temporal scales.

We propose a collaborative research effort to enable technologies that will make it easier for the farmers to command the new tools at their disposal by creating an intuitive and versatile system for programming distributed resources for performing complex tasks spanning large spatial and temporal scales. To effectively transfer large-scale and distributed autonomy and enable farmers to utilize these technologies, there is a need to understand the appropriate roles for human operator as well as methods for handling such multi-agent systems in a robust and guaranteed manner.