The BEAST: Modular Open-Source Framework for BVLOS Drone Flights with Long-Term Autonomy

The rapid growth of the drone market, driven by cost-effective computing and sensor advancements, has expanded applications in safety, security, agriculture, logistics, and infrastructure inspection. The introduction of EU drone regulations in 2020 has enabled Beyond Visual Line-of-Sight (BVLOS) and autonomous operations, opening opportunities for longterm unmanned missions. However, commercial drone systems remain reliant on Remote Piloted Aircraft Systems (RPAS) and predefined waypoint navigation, while autonomous operations are often confined to research settings. In this work, we present The BEAST framework, a modular open-source framework for long-term, robust, and autonomous BVLOS operations. This framework is designed to integrate intelligent drones into real-world environments while ensuring regulatory compliance. The BEAST framework includes essential components such as obstacle avoidance, intelligent fail-safe mechanisms, reliable communication, and a weather-proof docking station. Unlike previous approaches that address isolated BVLOS challenges, The BEAST provides a comprehensive, end-to-end solution encompassing mission planning, autonomous navigation, and operational safety. The framework has been implemented and validated across multiple drone platforms in safety and security applications.

Authors

Publication Details

Published
2025-05-14
DOI
https://doi.org/10.1109/icuas65942.2025.11007855
Citations
2
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
2.55
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The BEAST: Modular Open-Source Framework for BVLOS Drone Flights with Long-Term Autonomy

Abeje Y. Mersha, Benjamin Ronald van Manen, Gerjen Ter Maat, Mick Boe
2 citations
Robotic Path Planning Algorithms
2.55
article

The BEAST: Modular Open-Source Framework for BVLOS Drone Flights with Long-Term Autonomy

Abeje Y. Mersha, Benjamin Ronald van Manen, Gerjen Ter Maat, Mick Boe
article en
2 citations

Abstract

The rapid growth of the drone market, driven by cost-effective computing and sensor advancements, has expanded applications in safety, security, agriculture, logistics, and infrastructure inspection. The introduction of EU drone regulations in 2020 has enabled Beyond Visual Line-of-Sight (BVLOS) and autonomous operations, opening opportunities for longterm unmanned missions. However, commercial drone systems remain reliant on Remote Piloted Aircraft Systems (RPAS) and predefined waypoint navigation, while autonomous operations are often confined to research settings. In this work, we present The BEAST framework, a modular open-source framework for long-term, robust, and autonomous BVLOS operations. This framework is designed to integrate intelligent drones into real-world environments while ensuring regulatory compliance. The BEAST framework includes essential components such as obstacle avoidance, intelligent fail-safe mechanisms, reliable communication, and a weather-proof docking station. Unlike previous approaches that address isolated BVLOS challenges, The BEAST provides a comprehensive, end-to-end solution encompassing mission planning, autonomous navigation, and operational safety. The framework has been implemented and validated across multiple drone platforms in safety and security applications.

Openalex Percentile: Top 11%
Robotic Path Planning Algorithms
2.55
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.