Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “human autonomy teaming”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

Exploring the role of judgement and shared situation awareness when working with AI recommender systems

Abstract AI-advised Decision Making is a form of human-autonomy teaming in which an AI recommender system suggests a solution to a human operator, who is responsible for the final decision. This work seeks to examine the importance of judgement and shared situation awareness between humans and automated agents when interacting together in the form of a recommender systems. We propose manipulating both human judgement and shared situation awareness by providing the human decision maker with relevant information that the automated agent (AI), in the form of a recommender system, uses to generate possible courses of action. This paper presents the results of a two-phase between-subjects study in which participants and a recommender system jointly make a high-stakes decision. We varied the amount of relevant information the participant had, the assessment technique of the proposed solution, and the reliability of the recommender system. Findings indicate that this technique of supporting the human’s judgement and establishing a shared situation awareness is effective in (1) boosting the human decision maker’s situation awareness and task performance, (2) calibrating their trust in AI teammates, and (3) reducing overreliance on an AI partner. Additionally, participants were able to pinpoint the limitations and boundaries of the AI partner’s capabilities. They were able to discern situations where the AI’s recommendations could be trusted versus instances when they should not rely on the AI’s advice. This work proposes and validates a way to provide model-agnostic transparency into recommender systems that can support the human decision maker and lead to improved team performance.

Srivastava, Divya↗

Autonomous experimentation systems for materials development: A community perspective

Solutions to many of the world's problems depend upon materials research and development. However, advanced materials can take decades to discover and decades more to fully deploy. Humans and robots have begun to partner to advance science and technology orders of magnitude faster than humans do today through the development and exploitation of closed-loop, autonomous experimentation systems. This review discusses the specific challenges and opportunities related to materials discovery and development that will emerge from this new paradigm. Our perspective incorporates input from stakeholders in academia, industry, government laboratories, and funding agencies. We outline the current status, barriers, and needed investments, culminating with a vision for the path forward. We intend the article to spark interest in this emerging research area and to motivate potential practitioners by illustrating early successes. We also aspire to encourage a creative reimagining of the next generation of materials science infrastructure. To this end, we frame future investments in materials science and technology, hardware and software infrastructure, artificial intelligence and autonomy methods, and critical workforce development for autonomous research.

36 MATERIALS SCIENCE↗

Are humans still necessary? Expanding the discussion

The rise of automation, artificial intelligence (AI), and autonomous systems raises important questions about the future role of humans and the field of human factors/ergonomics in workplaces. This paper builds on Dr. Peter Hancock’s 2023 ‘Are Humans Still Necessary?’ article published in the Ergonomics journal. Using a multi-method approach that included a debate, opinion polling, roundtable discussions, and AI queries, the current effort examined the necessity of human involvement in future work environments. Debate team members presented arguments for and against the need for human workers, considering human factors, technology, and socioeconomic factors. Observations indicate that while AI may handle routine tasks, humans will likely remain essential for complex decision making, creativity, and ethical considerations. The paper advocates for viewing workplace dynamics as collaborative human-AI partnerships rather than competition, highlighting the need for a transdisciplinary approach in which human factors/ergonomics professionals play a vital role in enhancing these relationships.

99 - GENERAL AND MISCELLANEOUS↗

Purpose-Built UAVs for Physical Sampling of Trace Contamination at the Portsmouth Gaseous Diffusion Plant - 17331

The sampling of trace amounts of contamination, particularly of low-energy byproducts such as americium, presents a challenge for non-contact sensing. In many cases, such as determining the need for cleaning inside the exhaust shaft of the Waste Isolation Pilot Plant or sampling the walls of the enormous Gaseous Diffusion Plant at Portsmouth, it may be desirable to take physical swab samples at carefully distributed sample locations for analysis by mass spectrometry. Because of the danger posed to human workers in such scenarios, including risk of falls from lethal heights and exposure to low levels of radiation and the hassle of donning and doffing PPE, a low-cost robotic solution is desired. The inaccessibility of the heights involved suggest Unmanned Aerial Vehicle (UAV) solutions, rather than Unmanned Ground Vehicle (UGV) solutions, but conventional quadrotor UAVs are ill-suited to precise physical interaction with their surroundings. Quadrotors are under-actuated, rendering them non-holonomic and preventing the dexterous application of arbitrary generalized force/torques in interaction with the environment. At Purdue University, the authors have developed a number of novel UAV platforms suitable for dexterous interaction with the environment, making them ideal for such applications. These platforms can independently control forces in all directions, allowing for controlled application of the swab to the surface. Because of the scale of these structures (over 2 km in the case of the Gaseous Diffusion Plant), flight efficiency is of supreme importance. The Purdue team is took a variety of vehicles to the Gaseous Diffusion Plant for field trials on site in August, 2016. (With results available prior to the meeting.) The Purdue Dexterous Hexrotor is a fully-actuated Hexrotor capable of exerting forces in all six directions of force and torque. Operating alone or in swarms, the Dexterous Hexrotor can fly in free space, transition to contact through impact control, and sample the surface through force control. The Purdue I-BoomCopter is a tri-copter with an extra horizontal propeller that enables long-distance flight without pitching and the ability to apply closed-loop forces horizontally. Finally, the Purdue Tiltrotor VTOL is an under-actuated hybrid UAV that combines tilting rotors for vertical takeoff and landing, with a fixed-wing, flying-body design that is ultra-efficient for long-distance flight. The Dexterous Hexrotor provided two demonstrations of physical sampling of walls and crane rails. In sampling the large open sections of the inside of the plant, a small swarm of three UAVs is commanded to sample three distinct points on an internal map of the building. Human-supervised autonomy permits the UAVs to take off by themselves, find a clear elevation at which to fly through uncluttered space, navigate to their designated sampling points, and pause for confirmation by the human supervisor. The supervisor is presented with a video image of the intended sampling spot, which, if confirmed, the UAV will automatically approach and sample. The UAVs then autonomously return to the take-off spot. The second demo involved a single UAV searching upwards, then transitioning into 3-D SLAM mode to wait for a safe sampling spot on the 3-D scan to acquire the sample from the crane rail. The human supervisor, in this case, is responsible for ensuring the absence of cables and other obstacles. I-BoomCopter demonstrated its high-speed, long-distance coverage ability by making a few fast passes before homing in on a mock-up electrical panel with door, which it opened and closed. The dexterity of the I-BoomCopter results from its large propellers, which allow for controlled hovering and the horizontal thruster for applying forces of significant magnitude. Finally, the Tiltrotor VTOL is highly efficient in fixed-wing mode, but the tilt-rotor is under-actuated in hover. The tilt-rotor will take off vertically, then transition to high-speed, long-distance flight to make a number of passes inside the facility. The significance of these demos is the low-cost implementation of physical sampling over prescribable locations in difficult-to-reach areas of potentially contaminate facilities. To make this tractable over very large facilities, the demonstration of combinations of dexterous hovering ability and long-distance/high-speed flight is also in evidence. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗