/library/oar/handle/123456789/1024 2025-11-04T15:53:24Z 2025-11-04T15:53:24Z Koopman, C. Zammit-Mangion, David /library/oar/handle/123456789/139022 2025-09-16T08:42:45Z 2024-01-01T00:00:00Z

Title: Increasing predictability in the response of an AI-assisted stall recovery system in complex stall conditions by expanding the knowledge-base of AI Authors: Koopman, C.; Zammit-Mangion, David Abstract: The environment in the cockpit of commercial aircraft is becoming increasingly complex due to the introduction of automation systems. This complexity is especially evident when malfunctions take place, making it difficult for pilots to comprehend the interconnectedness of the systems and potentially leading to loss of control. This paper investigates a novel method for creating an Artificial Intelligence-based stall recovery assistant using Reinforcement Learning by training the agent to generate a stall and subsequently recover from it. This enables training in a large training space with a simple reward function, where the agent has the ability to develop a deep understanding of the environment. Tests show that the agent is able to recover from stall at a variety of altitudes while experiencing unreliable airspeed information originating from a blocked Pitot tube system and with a better response than all baseline agents. The results indicate that restricting AI is not always necessary and, further, that too many restrictions can lead to a system that learns only shallow features, causing it to be unreliable in unforeseen circumstances.

2024-01-01T00:00:00Z Bloch-Hansen, Craig Llucia, Santiago Kopardekar, Parimal Gandara Ossel, Roberto Ryan, Wes Martin Gomez, David Gaspar, Alberto Robles Quilca, Angelica Cristina Kunchalia, Akaki Donovan, Todd Ducci, Marco Diotalevi, Eugenio Parkinson, Alan (Stan) Jost, Daniel Chircop, Kenneth Velotto, Sergio Borgna, Ennio Zaglul González, Diego Ernesto Raju, Praveen Martin, Jose Blum, Scott Ghazavi, Noureddin Toews, Tyson Perca, Andreaa Sabatini, Roberto /library/oar/handle/123456789/137445 2025-07-21T10:44:20Z 2024-01-01T00:00:00Z

Title: JARUS whitepaper on considerations for automation of the airspace environment Authors: Bloch-Hansen, Craig; Llucia, Santiago; Kopardekar, Parimal; Gandara Ossel, Roberto; Ryan, Wes; Martin Gomez, David; Gaspar, Alberto; Robles Quilca, Angelica Cristina; Kunchalia, Akaki; Donovan, Todd; Ducci, Marco; Diotalevi, Eugenio; Parkinson, Alan (Stan); Jost, Daniel; Chircop, Kenneth; Velotto, Sergio; Borgna, Ennio; Zaglul González, Diego Ernesto; Raju, Praveen; Martin, Jose; Blum, Scott; Ghazavi, Noureddin; Toews, Tyson; Perca, Andreaa; Sabatini, Roberto Abstract: This document in its draft version is internal to JARUS. It is intended to provide an outline for considering the impact of automation across all aspects of aviation safety, while providing considerations for further developing the future of automation roll-out across the airspace. The scope is limited to safety aspects and does not specifically address broader issues related to liability, cost, or legal authority as these must be interpreted through local customs including the legal system, history, cultural practices, and public acceptance of risk and liability.

2024-01-01T00:00:00Z Bloch-Hansen, Craig Llucia, Santiago Gardi, Alex Senatore, Costantino Kazik, Tim Sayyed, Ruby Gandara Ossel, Roberto Ryan, Wes Martin Gomez, David Shedden, Michael Kopardekar, Parimal Eisele, Christopher Berry, Andrew Gaspar, Alberto Carlos Cirilo, Martin Zou, Xiang Robles Quilca, Angelica Cristina Kunchalia, Akaki Maitre, Tristan Mahelo, Keith Donovan, Todd Ducci, Marco Lyu, Renli Diotalevi, Eugenio Parkinson, Alan (Stan) Baumgartner, Marc Jost, Daniel Swider, Chris Koh, Bensen Chircop, Kenneth Johnson, Marcus Thurling, Andrew Velotto, Sergio Borgna, Ennio Wain, Gabrielle Zaglul González, Diego Ernesto Raju, Praveen Martin, Jose Blum, Scott Ghazavi, Noureddin Toews, Tyson Perca, Andreaa Sabatini, Roberto /library/oar/handle/123456789/137440 2025-07-21T10:33:46Z 2023-01-01T00:00:00Z

Title: JARUS methodology for evaluation of automation for UAS operations Authors: Bloch-Hansen, Craig; Llucia, Santiago; Gardi, Alex; Senatore, Costantino; Kazik, Tim; Sayyed, Ruby; Gandara Ossel, Roberto; Ryan, Wes; Martin Gomez, David; Shedden, Michael; Kopardekar, Parimal; Eisele, Christopher; Berry, Andrew; Gaspar, Alberto; Carlos Cirilo, Martin; Zou, Xiang; Robles Quilca, Angelica Cristina; Kunchalia, Akaki; Maitre, Tristan; Mahelo, Keith; Donovan, Todd; Ducci, Marco; Lyu, Renli; Diotalevi, Eugenio; Parkinson, Alan (Stan); Baumgartner, Marc; Jost, Daniel; Swider, Chris; Koh, Bensen; Chircop, Kenneth; Johnson, Marcus; Thurling, Andrew; Velotto, Sergio; Borgna, Ennio; Wain, Gabrielle; Zaglul González, Diego Ernesto; Raju, Praveen; Martin, Jose; Blum, Scott; Ghazavi, Noureddin; Toews, Tyson; Perca, Andreaa; Sabatini, Roberto Abstract: This document is intended to provide a standard view on how to assess functional automation for the JARUS community. The JARUS Automation WG has been tasked with defining a framework for assessing the impact of automation on an concept of operations and developing a framework for evaluating automation in proposed UAS operations. The framework includes definitions, assumptions, levels of automation, and the safety impact assessment methodology. The roles of the manufacturer, operator, pilot, service providers, and regulators are also assessed for each level of automation.

2023-01-01T00:00:00Z /library/oar/handle/123456789/137141 2025-07-11T10:48:46Z 2025-01-01T00:00:00Z

Title: Power optimization for a multistage stack of thermoelectric cooling devices Abstract: Methods and systems and systems provide for temperature control between thermoelectric coolers (TECs or TEMs) in a stack of multiple TECs, by optimizing the power suppled to each TEC in the stack. The temperatures may be continuously monitored, to continuously provide for the aforementioned power optimization.

2025-01-01T00:00:00Z