This 16-year-old invented a robot that can help scientists keep trees and forests healthy

ITMO UniversityLeft to right: Maksim Mikhailov and his team: Daniil Nechaev, Igor Lositsky and Gleb Zagarskikh, as they accept the gold medal at the 2017 World Robot Olympiad.

After hearing a radio program describe the labour-intensive work of forest pathologists – basically, tree doctors – Maksim Mikhailov had an idea: what if a robot helped collect their data?

Mikhailov is a 16-year-old student atITMO University, the renowned science and technology institution in St. Petersburg, Russia. As a member of the school’s Youth Robotics Lab, he was perfectly positioned to bring his idea to life.With a full team working on the the project, the robot won the gold medal at last year’s World Robot Olympiad; it can record tree locations within a forest, identify their species, measure the widths of their trunks, and even identify if a tree is healthy or not.

Its name is Forester, and most of its job is to explore forests and hit trees with its mallet. It’s a robotic adaptation of a technique that human tree experts often use, called “sounding,” to help their appraisal of a tree’s health.

“The robot hits a tree and its microphone records the sound,” Mikhailov explained. “Since sick trees have cavities or low wood density in their trunk, they make a sound with a lower overall frequency than that of a healthy tree.” The robot makes use of an algorithm that analyses the recorded sound to determine if it came from a healthy tree.

Forrester robotITMO UniversityA closer look at the Forrester robot.

Forester also takes a photograph of the tree and feeds the image to a neural network, identifying 12 different species of trees with accuracy better than 90 per cent.

This student invention is “a great idea,” says Lee Dean,lead arborist at Cornell University, simultaneously cautioning that “trees are living, dynamic systems.” He identifies the robot as a tool for the human arborist, not an automated solution that will render their work useless. “Tree risk assessment is qualifiable, not quantifiable. This can give indicators about a tree’s health, but can’t make the diagnosis.”

This jibes with Mikhailov’s own perception of his team’s creation. “While the robot can collect data about the trees, it cannot analyse that data to decide what needs to be done in order to preserve forests,” he said. That task falls to the human experts, whose jobs are perhaps made simpler by a data-collecting robot.

An arborist’s work appears to be safe from automation – at least, for now.

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