Related papers: ASA: A Simulation Environment for Evaluating Milit…
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 increased capabilities that have arisen due to the advancement…
Adaptive simulated annealing (ASA) is a global optimization algorithm based on an associated proof that the parameter space can be sampled much more efficiently than by using other previous simulated annealing algorithms. The author's ASA…
We describe AMUSE, the Astrophysical Multipurpose Software Environment, a programming framework designed to manage multi-scale, multi-physics simulations in a hierarchical, extensible, and internally consistent way. Constructed as a…
The European Space Agency (ESA) uses an engine to perform tests in the Ground Segment infrastructure, specially the Operational Simulator. This engine uses many different tools to ensure the development of regression testing infrastructure…
The aerial manipulator (AM) is a systematic operational robotic platform in high standard on algorithm robustness. Directly deploying the algorithms to the practical system will take numerous trial and error costs and even cause destructive…
We present a new simulator of Uncrewed Aerial Vehicles (UAVs) that is tailored to the needs of testing cyber-physical security attacks and defenses. Recent investigations into UAV safety have unveiled various attack surfaces and some…
Within academia and industry, there has been a need for expansive simulation frameworks that include model-based simulation of sensors, mobile vehicles, and the environment around them. To this end, the modular, real-time, and open-source…
This article introduces a software framework for benchmarking robot task scheduling algorithms in dynamic and uncertain service environments. The system provides standardized interfaces, configurable scenarios with movable objects, human…
Failures in safety-critical Cyber-Physical Systems (CPS), both software and hardware-related, can lead to severe incidents impacting physical infrastructure or even harming humans. As a result, extensive simulations and field tests need to…
Auditory scene analysis (ASA) aims to retrieve information from the acoustic environment, by carrying out three main tasks: sound source location, separation, and classification. These tasks are traditionally executed with a linear data…
This paper presents the ARCAD simulator for the rapid development of Unmanned Aerial Systems (UAS), including underactuated and fully-actuated multirotors, fixed-wing aircraft, and Vertical Take-Off and Landing (VTOL) hybrid vehicles. The…
Developing trustworthy multi-agent systems for practical applications is challenging due to the complicated communication of situational awareness (SA) among agents. This paper showcases a novel efficient and easy-to-use software framework…
Computer-Using Agents (CUAs) are rapidly extending large language models (LLMs) beyond text-based reasoning toward action execution in more complex environments, such as web browsers and graphical user interfaces (GUIs). However, existing…
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 various established techniques, creating a unified,…
Traditional AI reasoning techniques have been used successfully in many domains, including logistics, scheduling and game playing. This paper is part of a project aimed at investigating how such techniques can be extended to coordinate…
We introduce a new software toolbox for agent-based simulation. Facilitating rapid prototyping by offering a user-friendly Python API, its core rests on an efficient C++ implementation to support simulation of large-scale multi-agent…
Scenario-based development and test processes are a promising approach for verifying and validating automated driving functions. For this purpose, scenarios have to be generated during the development process in a traceable manner. In early…
Traditional AI reasoning techniques have been used successfully in many domains, including logistics, scheduling and game playing. This paper is part of a project aimed at investigating how such techniques can be extended to coordinate…
This work presents a Hierarchical Multi-Agent Reinforcement Learning framework for analyzing simulated air combat scenarios involving heterogeneous agents. The objective is to identify effective Courses of Action that lead to mission…
The rapidly evolving field of autonomous driving systems (ADSs) is full of promise. However, in order to fulfil these promises, ADSs need to be safe in all circumstances. This paper introduces ISS-Scenario, an autonomous driving testing…