How robots and drones will help feed the world

A team of researchers from the University of Georgia (UGA) in the US is developing a robotic system of all-terrain rovers and unmanned aerial drones to gather and analyse data on the physical characteristics of crops, including their growth patterns, stress tolerance and general health. This information is vital for scientists who are working to increase agricultural production in a time of rapid population growth.

The current processes used by scientists to gather data on plant characteristics is expensive and painstakingly slow, as researchers must manually record data one plant at a time. The team of robots will allow researchers to compile data on entire fields of crops throughout the growing season.

The project addresses a major bottleneck that’s holding up plant genetics research, said Andrew Paterson, a co-principal investigator and world leader in the mapping and sequencing of flowering-plant genomes.

“The robots offer us not only the means to more efficiently do what we already do, but also the means to gain information that is presently beyond our reach,” he said. “For example, by measuring plant height at weekly intervals instead of just once at the end of the season, we can learn about how different genotypes respond to specific environmental parameters, such as rainfall.”

In addition to multispectral, hyperspectral and thermal cameras, the robots will be outfitted with Light Detection and Ranging, or LiDAR, a remote sensing method that uses light in the form of a pulsed laser to measure distances. The technology will allow the researchers to create precise three-dimensional images of the plants they study.

During preliminary testing of the system last year, Changying ‘Charlie’ Li, a professor in UGA’s College of Engineering and the principal investigator on the project, estimates the team collected 20 terabytes of data over the six-month growing season. He said the team will collect 30 times that amount when the robots are fully deployed.

To analyse these massive data sets, the researchers are developing an artificial intelligence algorithm similar to the facial recognition program Facebook uses to facilitate the identification and ‘tagging’ of people in a photograph. The algorithm will be able to scan an aerial photo of a large field and automatically identify the location and number of flowers on each plant.

With teams of autonomous vehicles rumbling through rows of crops and hovering overhead, algorithms will also play a key role in making sure the robots and drones perform their assigned tasks while staying out of each other’s way.

The researchers believe their work will provide a platform for plant geneticists to gather massive amounts of phenotype data and empower advances in crops that sustain the planet’s population.