Research

Animals and Robots

The goal of this project is to develop computational approaches for studying groups of agents with natural mobility and social interactions. The agents in such systems can move on their own due to complex interactions
between biotic and abiotic factors, culminating in behaviors that can be
studied and modeled using physical data, and ultimately controlled. We will
develop algorithms for adaptive data collection during a field experiment,
post-experiment data analysis for modeling behavior, and control of
the movement of the group using the learned models in field experiments
and environment data from satellite imagery.

The main motivation and application of this work is in the agricultural domain,
in the area of free-ranging animal ecology, specifically for cattle.
Groups of animals such as cattle herds are complex systems that
are affected by many factors including age, group size, landscape topography, plant phenology, and weather. These factors produce interesting interactions among
individuals such as friendship, kinship, group formation, leading and
following. There are complex interactions with the environment as well,
for example searching for drinking water or exploring a new paddock which often involves walking the perimeter along established fence lines.

This project combines computer networking, modeling, and robot motion planning and control. We  use physical data collected for extensive periods of time in the field
(by our collaborators at the USDA-ARS Jornada Experimental Range (JER)
and CSIRO, Australia and in our previous work)
to define behavior models for herds of animals, using these models to
develop planning and control algorithms for coordinating the location
of these herds, and using the location control system to manage the
stock density and optimize the use of land.
This includes: