Robotic Monitoring of Habitats

the Natural Intelligence Approach

Journal article (2023)

Authors

Franco Angelini University of Pisa
Claudia Angiolini University of Siena
Simonetta Bagella Università degli Studi di Sassari
Marco Caccianiga University of Milan
C. Della Santina Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering , Deutsches Zentrum für Luft- und Raumfahrt (DLR)
Daniela Gigante University of Perugia
Marco Hutter ETH Zürich
Thrishantha Nanayakkara Imperial College London
More Authors... External organisation
Research Group
Learning & Autonomous Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2023 Franco Angelini, Pierangela Angelini, Claudia Angiolini, Simonetta Bagella, Marco Caccianiga, C. Della Santina, Daniela Gigante, Marco Hutter, Thrishantha Nanayakkara, More Authors
DOI: https://doi.org/10.1109/ACCESS.2023.3294276
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Published Date

2023

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Learning & Autonomous Control

Abstract

In this paper, we first discuss the challenges related to habitat monitoring and review possible robotic solutions. Then, we propose a framework to perform terrestrial habitat monitoring exploiting the mobility of legged robotic systems. The idea is to provide the robot with the Natural Intelligence introduced as the combination of the environment in which it moves, the intelligence embedded in the design of its body, and the algorithms composing its mind. This approach aims to solve the challenges of deploying robots in real natural environments, such as irregular and rough terrains, long-lasting operations, and unexpected collisions, with the final objective of assisting humans in assessing the habitat conservation status. Finally, we present examples of robotic monitoring of habitats in four different environments: forests, grasslands, dunes, and screes.