iCADME: A Modular Autonomy Architecture for Robotic Heterogeneous Networks in Communication-Limited Environments

Autonomy and cooperation are essential features in robotic networks, especially in the underwater domain where communications are severely limited. Robots should be able to carry out any assigned task autonomously, yet cooperate with other robots when allowed to by the environmental conditions. To enable this, there is a growing interest in robotic software solutions which are modular, scalable and easy to test. In this paper, we introduce iCADME, a novel autonomy architecture, which achieves such features thanks to a software eco-system which relies on a hierarchy of tasks, in charge of perception and decision-making, and of behaviour strategies, which act as the interface towards the robot lower level control architecture. The modularity and the attention to the system configuration are instrumental for the user to reuse the software and to expand the task portfolio. Thanks to the strong decoupling between perception/decision-making and action, achieved also with the design of an interface layer with the external middleware, iCADME can be easily integrated with various planning and control systems and with different middleware software. On top of that, a behaviour trees (BTs) mission management system is introduced. BTs enable the building of complex missions by assembling a portfolio of tasks, with features of high modularity and reactivity. All these iCADME's features were succesfully tested during MEDASWAN23 trial. They are a step forward towards the actual use in the field of increasingly cooperative robotic networks.

Authors

Institutions

Publication Details

Published
2025-06-16
DOI
https://doi.org/10.1109/oceans58557.2025.11104515
Primary Topic
Distributed systems and fault tolerance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

iCADME: A Modular Autonomy Architecture for Robotic Heterogeneous Networks in Communication-Limited Environments

Gabriele Ferri, Alessandro Faggiani, Alessandra Teseï, Federico Celi et al.
Distributed systems and fault tolerance
article

iCADME: A Modular Autonomy Architecture for Robotic Heterogeneous Networks in Communication-Limited Environments

Gabriele Ferri, Alessandro Faggiani, Alessandra Teseï, Federico Celi, Robert Been
article en

Abstract

Autonomy and cooperation are essential features in robotic networks, especially in the underwater domain where communications are severely limited. Robots should be able to carry out any assigned task autonomously, yet cooperate with other robots when allowed to by the environmental conditions. To enable this, there is a growing interest in robotic software solutions which are modular, scalable and easy to test. In this paper, we introduce iCADME, a novel autonomy architecture, which achieves such features thanks to a software eco-system which relies on a hierarchy of tasks, in charge of perception and decision-making, and of behaviour strategies, which act as the interface towards the robot lower level control architecture. The modularity and the attention to the system configuration are instrumental for the user to reuse the software and to expand the task portfolio. Thanks to the strong decoupling between perception/decision-making and action, achieved also with the design of an interface layer with the external middleware, iCADME can be easily integrated with various planning and control systems and with different middleware software. On top of that, a behaviour trees (BTs) mission management system is introduced. BTs enable the building of complex missions by assembling a portfolio of tasks, with features of high modularity and reactivity. All these iCADME's features were succesfully tested during MEDASWAN23 trial. They are a step forward towards the actual use in the field of increasingly cooperative robotic networks.

North Atlantic Treaty Organization (BE)
Openalex Percentile: Top 77%
Distributed systems and fault tolerance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.