Open AccessAn Environment for Indoor Testing and Diagnosis of Drones using Co-simulation
Author(s) -
Renato Ricardo de Abreu,
Thyago Oliveira,
Leydson Silva,
Tiago P. Nascimento,
Alisson V. Brito
Publication year - 2019
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/sbesc_estendido.2019.8639
Subject(s) - drone , computer science , high level architecture , real time computing , anomaly detection , synchronization (alternating current) , embedded system , simulation , data mining , operating system , interoperability , computer network , channel (broadcasting) , genetics , biology
The objective of this work is to present a testing tool, which analyzes and evaluates drones during the flight in indoor environments. For this purpose, the framework Ptolemy II was extended for communication with real drones using the High-Level Architecture (HLA) for data exchanging and synchronization. The presented testing environment is extendable for other testing routines and is ready for integration with other simulation and analysis tools. In this paper, two failure detection experiments were performed, with a total of 20 flights for each one, which 80% were used to train a decision tree algorithm, and the other 20% flights to test the algorithm in which one of the propellers had an anomaly. The failure rate or detection rate was 70% for the first experiment and 90% for the second one.