Botany Meets Robotics in Alpine Scree Monitoring

TL;DR

This paper introduces a robotic system using legged robots and deep learning to improve the efficiency and effectiveness of monitoring endangered alpine scree habitats, reducing resource needs and enhancing data collection.

Contribution

It presents a novel robotics-assisted habitat monitoring protocol combining legged robots and deep learning for plant species detection in challenging terrains.

Findings

Robots successfully navigated difficult alpine terrains.

Robotics increased monitoring frequency and data quality.

Enhanced collaboration between robots and botanists.

Abstract

According to the European Union's Habitat Directive, habitat monitoring plays a critical role in response to the escalating problems posed by biodiversity loss and environmental degradation. Scree habitats, hosting unique and often endangered species, face severe threats from climate change due to their high-altitude nature. Traditionally, their monitoring has required highly skilled scientists to conduct extensive fieldwork in remote, potentially hazardous locations, making the process resource-intensive and time-consuming. This paper presents a novel approach for scree habitat monitoring using a legged robot to assist botanists in data collection and species identification. Specifically, we deployed the ANYmal C robot in the Italian Alpine bio-region in two field campaigns spanning two years and leveraged deep learning to detect and classify key plant species of interest. Our results demonstrate that agile legged robots can navigate challenging terrains and increase the frequency and efficiency of scree monitoring. When paired with traditional phytosociological surveys performed by botanists, this robotics-assisted protocol not only streamlines field operations but also enhances data acquisition, storage, and usage. The outcomes of this research contribute to the evolving landscape of robotics in environmental science, paving the way for a more comprehensive and sustainable approach to habitat monitoring and preservation.