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Upon their arrival, Unmanned Autonomous Systems (UAS) brought with them many benefits for those involved in a military campaign. They can use such systems to reconnoiter dangerous areas, provide 24-hr aerial security surveillance for force protection purposes or even attack enemy targets all the while avoiding friendly human losses in the process. ...All this has the potential to turn the benefits of UAS into liabilities and although the last decade has seen great advances in the development of protection and countermeasures against the described threats and beyond the risk still endures. ...With this in mind the present work will describe a monitoring system whose purpose is to monitor UAS mission profile implementation at both high level mission execution and at lower level software code operation to tackle the specific threats of malicious code and possible spurious commands received over the vehicle's data links.

The United States Air Force’s 412th Test Wing’s Emerging Technologies (ET) Combined Test Force (CTF) completed the first flight test of Johns Hopkins University’s Testing of Autonomy in Complex Environments (TACE) system. As “middleware,” TACE serves as an “autonomy watchdog,” monitoring commands sent to an aircraft’s autopilot software from its autonomous artificial intelligence (AI) computer and transmitting autopilot information such as position, speed, and orientation back to the AI.

Airbus Aerial uses a unique combination of satellites, manned aircraft and rotorcraft, and unmanned aircraft systems (UAS) together with data analytics technology and an artificial intelligence (AI), or machine learning, platform to help organizations supporting recovery efforts better understand and react to the storm as it rolled across the southeastern U.S. into the Gulf of Mexico.

While unmanned aircraft system (UAS) operations and UAS Traffic Management (UTM) are often touted as “safety critical”, the systems and technologies are not being held to the same standards as traditional aviation, with its long pedigree of safety.

Abstract Autonomy is a key enabling factor in uncrewed aircraft system (UAS) and advanced air mobility (AAM) applications ranging from cargo delivery to structure inspection to passenger transport, across multiple sectors. ...In addition to guiding the UAS, autonomy will ensure that they stay safe in a large number of off-nominal situations without requiring the operator to intervene.

DoD to Deploy Thousands of Low Cost Autonomous Systems Under Replicator Program Top Productivity Improvement Tips for Manufacturing Turbine Discs FACE Technical Standard Offers MOSA Lessons for Safety-Critical Software in Any Sector Adamant: A Soon-to-be Open Source, Mission-Critical Flight Software Framework Written in Ada Benefits and Challenges of Direct-RF Sampling for Avionic Platforms More Airports Test RF as Counter Measure for UAS in Restricted Airspace Adapting U.S. Army Acquisition to Ensure the Reliability and Safety of Autonomous Vehicles This report presents several challenges that the U.S.

The Swarm and Search AI Challenge: 2019 Fire Hack challenge will culminate in a March 2019 showdown and explore methods for planning complex UAS or “drone” swarm operations.

Through OFFSET, DARPA envisions swarms of 250 collaborative autonomous systems – including unmanned aircraft systems (UAS) – providing critical capabilities to ground units in urban areas where challenges such as tall buildings, tight spaces, and limited sight lines constrain essential communications, sensing, maneuverability, and autonomous operations.

Breathing Life into Artificial Intelligence and Next Generation Autonomous Aerospace Systems Robotic Rotational Molding Creates New Opportunities for Military and Aerospace Applications Rim-Driven Electric Aircraft Propulsion High-Speed Midwave Infrared Cameras Enable Military Test Range Tracking System What Today's Advances in Radar Technology Mean for Testing and Training Tackling Ruggedization Challenges for RF Communications in Software Defined Radios AUVSI XPONENTIAL 2023 The Blueprint for Autonomy Multi-Scale Structuring of the Polar Ionosphere Understanding a radically new sensing capability for polar ionospheric science introduced by observational evidence recently provided by the electronically steerable Resolute Bay Incoherent Scatter Radar (RISR). Stepped-Frequency Distributed Radar for Through-the-Wall Sensing A technical analysis of the effectiveness of distributed radar for through-the-wall sensing applications.

Explaining MOSA from the Team that Led the Army Aviation Mission Computing Environment Task Order What's the Best DC Motor for Your Commercial Aerospace Application? Aerospace Production: Overcoming Challenges in Composite Machining Understanding the Limits of Artificial Intelligence for Predictive Maintenance Pushing the Limits: Engineering Advanced RF Interconnects to Meet the Challenges of Hypersonic Missile Development Expanding Possibilities for Superconducting Qubits With Niobium Researchers Help Robots Navigate Efficiently in Uncertain Environments A new algorithm reduces travel time by identifying shortcuts a robot could take on the way to its destination.

Almost exactly seven months after Unites Technologies Corporation (UTC) completed its acquisition of Rockwell Collins (now Collins Aerospace), the aerospace conglomerate announced its merger with the Raytheon Company.

This third edition of Automatic Target Recognition provides a roadmap for breakthrough ATR designs―with increased intelligence, performance, and autonomy. Clear distinctions are made between military problems and comparable commercial deep-learning problems. These considerations need to be understood by ATR engineers working in the defense industry as well as by their government customers. A reference design is provided for a next-generation ATR that can continuously learn from and adapt to its environment. The convergence of diverse forms of data on a single platform supports new capabilities and improved performance. This third edition broadens the notion of ATR to multisensor fusion. Radical continuous-learning ATR architectures, better integration of data sources, well-packaged sensors, and low-power teraflop chips will enable transformative military designs.

Automatic Target Recognition provides an inside view of the automatic target recognition (ATR) domain from the perspective of an engineer working in the field for 40 years. The algorithm descriptions and testing procedures covered in the book are appropriate for addressing military problems and unique aspects and considerations in the design, testing, and fielding of ATR systems. These considerations need to be understood by ATR engineers working in the defense industry as well as by their government customers. The final chapter discusses the future of ATR and provides a type of Turing test for determining if an ATR system is truly smart (neuromorphic or brain-like). The Appendix provides difficult-to-find resources available to the ATR engineer.

Hundreds of aerospace executives, engineers, scientists, and academics are gathering in London this week for Aerospace Systems and Technology Conference (ASTC) 2018 from SAE International in Warrendale, Pennsylvania. Discussions during the three-day industry event center on the theme of innovating air mobility. Aerospace thought leaders are at ASTC discussing current challenges, the latest enabling technologies, and future opportunities, including those related to urban air mobility (UAM) and supersonic aircraft.

The Raytheon Company is testing a new artificial intelligence (AI) tool developed to help determine when the multi-mode radar installed on U.S. Air Force CV-22 tiltrotor aircraft is in need of service.

A new “AI Innovation Challenge” tasks United Kingdom and Canadian startups and researchers to pitch ideas for how AI could improve aircraft efficiency in extreme weather.

DARPA will invest more than $2 billion in over 20 new and existing programs collectively called the “AI Next” campaign. Through AI Next, DARPA is exploring ways to advance the state-of-the-art in AI, pushing beyond second-wave machine learning techniques and toward “contextual reasoning and adaptation” capabilities.

Lockheed Martin of Bethesda, Md. and the Office of Naval Research are exploring how to apply artificial intelligence to train robots to independently oversee and optimize additive manufacturing, also known as 3D printing, of complex parts.

The new Advanced Technology and Training Center (ATTC), which opened yesterday after a ribbon-cutting ceremony, will focus on breakthroughs in condition-based maintenance and the intersection of artificial intelligence (AI), robotics, and automation within that domain.