Welcome to USMA Athena
USMA Athena is a secure digital service managed by the United States Military Academy Library to make the work of USMA scholars freely available, while also ensuring these resources are organized to preserve the legacy of USMA scholarship. The mission of USMA Athena is to showcase the academic impact and intellectual capital that has become synonymous with the celebrated heritage of educational prowess attributed to the Long Gray Line. Scholarship submitted to USMA Athena benefits from added visibility and discoverability via Google Scholar in addition to the use of persistent URLs that will provide enduring access to the work over time.
Recent Submissions
Item Video-Integrated System for Testing Augmented Reality (VISTA): A Rapid Testing Methodology for AR Platforms(Springer Nature, 2025-05-30)This paper evaluates a methodology aimed at enhancing the iterative development of augmented reality (AR) systems. We introduce the Video-Integrated System for Testing Augmented Reality (VISTA), a solution addressing two key challenges for AR developers: slow application deployment and the requirement for users to wear an AR headset for testing. Our approach leverages Holographic Remoting software and the Device Portal application to create short demonstration videos, enabling users to observe users interacting with and the physical world without deploying the application to a device or requiring headset use. To pilot VISTA, we surveyed novice software developers for feedback on an AR application we created, which yielded encouraging results.Item Exploring Hedera Hashgraph for Efficient Data Transfer in MOOS-IvP Aquaticus Testbed(IEEE, 2025)The Hedera hashgraph algorithm has been shown to be Asynchronous Byzantine Fault Tolerant (ABFT) for achieving consensus on adding a transaction into local copies of a hash-graph distributed database. The ABFT result is theoretically the best result that can be achieved for distributed ledger technology (DLT) regarding trusting that the data in each local copy of a distributed global database has not been tampered with during each transaction process to add data into the global distributed database. The hashgraph algorithm ensures that each transaction in each local copy of the global database can be trusted to be a true copy of the data submitted by each node in the set of peer nodes as long as no more than 1/3 of the peer nodes in the peer-to-peer network of hashgraph nodes have been compromised. The Aquaticus, capture the flag (CTF) force-on-force free-play competition between Artificial Intelligence (AI)/Machine Learning (ML) agents enables use of a variety of ML algorithms to build AI/ML agents to play and win the CTF game in a maritime environment by employing the MOOS-IvP autonomy stack. This paper explores the integration of Hedera hashgraph DLT into the MOOS-IvP Aquaticus testbed for efficient and secure data transfer in collaborative autonomy scenarios. The study focuses on developing a multi-node Hedera network to support decentralized, real-time, and tamper-proof communication among autonomous agents in adversarial maritime environments. A detailed network setup using Docker and solo-compose is outlined, including transitioning from single-node to multi-node configurations. The system's application is evaluated in the context of the Aquaticus capture-the-flag (CTF) environment, highlighting its role in synchronizing flag positions and tagging status among unmanned surface vehicles (USVs), Initial findings indicate that the Hedera network can enhance data integrity and scalability while reducing latency in distributed systems. Challenges in scaling and resource optimization are discussed, along with proposed future work to deploy physical nodes using Raspberry Pi and integrate reinforcement learning frameworks like PyQuaticus. This research provides a foundation for advancing decentralized communication in autonomous robotics, emphasizing its potential for secure and robust multi-agent collaboration.Item The First International Maritime Capture the Flag Competition: Lessons Learned and Future Directions(AAAI, 2025-02-25)Maritime Capture the Flag (MCTF) is a 3-vs-3 multi-agent real-time strategy game that utilizes a marine robotics simulator with support for hardware deployment. The game presents several research challenges in the areas of coordination and communication of multi-agent teams in adversarial environments with sparse rewards, and safe autonomy. In this paper, we report our experiences and challenges in deploying the MCTF game as an open, public challenge as part of the competition track at the 2024 Autonomous Agents and Multi-agent Systems (AAMAS) conference. The top performing teams were also evaluated on unmanned surface vehicles playing a 3-vs-3 MCTF game in a physical marine environment. We summarize the techniques used by the top eight competition entries that featured control algorithms ranging from multi-agent deep reinforcement learning to heuristic approaches for path planning and search algorithms. Our analysis of the competition results reveals a trade off between winning versus safety, as a key factor differentiating teams' performance was their agents' handling of safety behaviors like collisions with other players. We conclude by highlighting the key research gaps in deploying multi-player game-like encounters in the real world scenarios.Item From Detection to Traversal: a Probabilistic Framework for UAS-Assisted Landmine Mapping and Circumvention(IEEE, 2025-05)This research presents a robust probabilistic framework for minefield localization, mapping, and avoidance, addressing a technological gap in the field of aerial countermine intelligence, while bypassing the well-established techniques of landmine detection. Our approach propagates the pose uncertainty matrix delivered by a drone's flight controller's Kalman filter to probabilistically estimate the location of detected mines. This probability map then seeds an artificial potential field path generator which creates a safe path for ground traversal by producing waypoints through the minefield. The system's performance is evaluated in simulations and validated through flight trials, demonstrating its potential to improve the efficiency and safety of UAV-assisted minefield navigation and threat avoidance.Item Integrating Human-Robot Teaming Dynamics Into Mission Planning Tools for Transparent Tactics in Multi-Robot Human Integrated Teams(IEEE, 2025-05-30)This research aims to demonstrate how integrating human-robot teaming dynamics into mission planning tools impacts the abilities of robot operators as they coordinate multiple robot agents during a mission. This was investigated in a pilot study using two inter-robot collaboration modalities and interface tools, which required different human-robot interaction techniques to execute a mission with a team of four robots. In the first modality, the operator manually inserted waypoints for each robot, as they acted as individual agents. In the second modality, the operator used the Planning Execution to After-Action Review (PETAAR) toolset to plot a single waypoint for the team of robots, as the robots coordinated their movement as a group. One novel component of this study is the investigation of how human-robot teaming dynamics and the PETAAR toolset impacted robot operators' real-time situation awareness and perceived cognitive load as well as team performance. Although the teaming modalities differed greatly with respect to the level of operator input needed, the time required to complete the simulation, the participant's perceived cognitive load, and interface usability were very similar for both modalities. In contrast, the results revealed statistically significant differences between the two teaming modalities related to participants' abilities to maintain a wedge formation while remaining situationally aware. Results from this work will be used to guide development of PETAAR along with the design of future studies investigating more complex teaming scenarios and for creating a baseline for comparing future results.
Communities in USMA Athena
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