8 citations · 19 across the 15 of their papers we have counts for
15 papers
Offline Multimodal Large Language Models for Decision Support in Air Operations
Joao P. A. Dantas, Jelton A. Cunha, Gabriel Dietzsch
Air operations rely on complex rules, established procedures, and time-critical analysis under limited connectivity and strict security constraints. In such environments, analysts…
Loyal Wingman Assessment: Social Navigation for Human-Autonomous Collaboration in Simulated Air Combat
Joao P. A. Dantas, Marcos R. O. A. Maximo, Takashi Yoneyama
This study proposes social navigation metrics for autonomous agents in air combat, aiming to facilitate their smooth integration into pilot formations. The absence of such metrics…
TartanAviation: Image, Speech, and ADS-B Trajectory Datasets for Terminal Airspace Operations
Jay Patrikar, Joao Dantas, Brady Moon +7
We introduce TartanAviation, an open-source multi-modal dataset focused on terminal-area airspace operations. TartanAviation provides a holistic view of the airport environment by…
Real-Time Surface-to-Air Missile Engagement Zone Prediction Using Simulation and Machine Learning
Joao P. A. Dantas, Diego Geraldo, Felipe L. L. Medeiros +2
Surface-to-Air Missiles (SAMs) are crucial in modern air defense systems. A critical aspect of their effectiveness is the Engagement Zone (EZ), the spatial region within which a SA…
AsaPy: A Python Library for Aerospace Simulation Analysis
Joao P. A. Dantas, Samara R. Silva, Vitor C. F. Gomes +5
AsaPy is a custom-made Python library designed to simplify and optimize the analysis of aerospace simulation data. Instead of introducing new methodologies, it excels in combining…
ASA-SimaaS: Advancing Digital Transformation through Simulation Services in the Brazilian Air Force
Joao P. A. Dantas, Diego Geraldo, Andre N. Costa +2
This work explores the use of military simulations in predicting and evaluating the outcomes of potential scenarios. It highlights the evolution of military simulations and the inc…
SoRTS: Learned Tree Search for Long Horizon Social Robot Navigation
Ingrid Navarro, Jay Patrikar, Joao P. A. Dantas +4
The fast-growing demand for fully autonomous robots in shared spaces calls for the development of trustworthy agents that can safely and seamlessly navigate in crowded environments…
Autonomous Agent for Beyond Visual Range Air Combat: A Deep Reinforcement Learning Approach
Joao P. A. Dantas, Marcos R. O. A. Maximo, Takashi Yoneyama
This work contributes to developing an agent based on deep reinforcement learning capable of acting in a beyond visual range (BVR) air combat simulation environment. The paper pres…
Learned Tree Search for Long-Horizon Social Robot Navigation in Shared Airspace
Ingrid Navarro, Jay Patrikar, Joao P. A. Dantas +4
The fast-growing demand for fully autonomous aerial operations in shared spaces necessitates developing trustworthy agents that can safely and seamlessly navigate in crowded, dynam…
Challenges in Close-Proximity Safe and Seamless Operation of Manned and Unmanned Aircraft in Shared Airspace
Jay Patrikar, Joao P. A. Dantas, Sourish Ghosh +11
We propose developing an integrated system to keep autonomous unmanned aircraft safely separated and behave as expected in conjunction with manned traffic. The main goal is to achi…
Supervised Machine Learning for Effective Missile Launch Based on Beyond Visual Range Air Combat Simulations
Joao P. A. Dantas, Andre N. Costa, Felipe L. L. Medeiros +3
This work compares supervised machine learning methods using reliable data from constructive simulations to estimate the most effective moment for launching missiles during air com…
ASA: A Simulation Environment for Evaluating Military Operational Scenarios
Joao P. A. Dantas, Andre N. Costa, Vitor C. F. Gomes +10
The Aerospace Simulation Environment (Ambiente de Simulação Aeroespacial -- ASA in Portuguese) is a custom-made object-oriented simulation framework developed mainly in C++ that en…
Enhanced Self-Organizing Map Solution for the Traveling Salesman Problem
Joao P. A. Dantas, Andre N. Costa, Marcos R. O. A. Maximo +1
Using an enhanced Self-Organizing Map method, we provided suboptimal solutions to the Traveling Salesman Problem. Besides, we employed hyperparameter tuning to identify the most cr…
Weapon Engagement Zone Maximum Launch Range Estimation Using a Deep Neural Network
Joao P. A. Dantas, Andre N. Costa, Diego Geraldo +2
This work investigates the use of a Deep Neural Network (DNN) to perform an estimation of the Weapon Engagement Zone (WEZ) maximum launch range. The WEZ allows the pilot to identif…
Engagement Decision Support for Beyond Visual Range Air Combat
Joao P. A. Dantas, Andre N. Costa, Diego Geraldo +2
This work aims to provide an engagement decision support tool for Beyond Visual Range (BVR) air combat in the context of Defensive Counter Air (DCA) missions. In BVR air combat, en…