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At least 1,531 records · Page 85
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Challenges and Opportunities of International Cooperation for Safety & Mission Assurance (SMA) on the European Service Module (ESM) of the Orion Program

ESA is providing the ESM to NASA for the Orion Program in accordance with the Implementing Arrangement (IA) established between the two Agencies in 2012. This IA is a barter agreement, in which ESA provides Service Module vehicles for the first two flights of Orion in exchange for two servicing missions to the ISS. This arrangement has provided opportunities and challenges to both communities. It represents an important opportunity for ESA to build on its experience in the development and operations of ATV and play an active role in the development and flight of a manned space vehicle. This paper will explore some of the unique aspects of this arrangement as it affects Safety & Mission Assurance (SMA).The assessment of ESM compliance with applicable safety requirements is the responsibility of the Joint Safety and Engineering Review Panel (JSERP). The JSERP has two features that are relatively unique amongst NASA safety panels. First, NASA Engineering and SMA organizations co-chair this Panel. Previously, Safety has chaired, with Engineering as a member of the Panel. Inclusion of Engineering as a co-chair has offered greater leverage within the technical community. Second, the JSERP includes a second set of co-chairs from ESA Engineering and ESA Product Assurance and Safety (PA/S) organizations. This recognizes the international arrangement as one of partnership.Another source of both opportunity and challenge is the differing experience base of ESA and NASA. NASA has decades of experience in manned spaceflight, dating back to the Mercury program and following through Gemini, Apollo, Apollo-Soyuz, Skylab, Shuttle and the International Space Station. The risk posture for manned missions is much more rigorous than for unmanned missions. ESA brings a wealth of knowledge as well, with their flights of Ariane and Automated Transfer Vehicle (ATV), development and operation of the Columbus module on ISS, and satellite programs. The result is that both parties have developed paradigms related to risk and failure that contribute to ESM discussions.Orion represents humanity's first venture beyond Low-Earth Orbit (LEO) in over fifty years. Much of that experience is captured in program documents, but first-hand knowledge is limited to a few spaceflight veterans. Missions to LEO have offered the opportunity of direct, near-instantaneous communications and assistance, and the ability to return to Earth within a matter of hours in case of emergency. Outward-bound missions do not have these features and will require a more autonomous spacecraft with attendant safety-related issues.This paper will explore these and other challenges as we approach the flight of the first Orion vehicle.

Ciancone, Michael L.↗
NASA NTRSDate not supplied

Deep Learning-Based Negotiation Strategy Selection for Cooperative Conflict Resolution in Urban Air Mobility

This paper presents a collaborative conflict resolution technique using deep neural network-based intelligent search of the solution space. This approach offers a rapid convergence to a mutually acceptable solution for real-time conflict resolution, suitable for urban air mobility operations. Furthermore, the presented technique allows operational flexibility to the urban air mobility agents where these agents can collaboratively devise the solution via integrative negotiation, based on their local utility functions, as long as such a solution does not violate the global safety thresholds. The presented machine-to-machine negotiation method is built on our prior work on holistic assessment of the airspace and potential conflict detection implemented at-the-edge, onboard the unmanned aircraft systems. This paper extends the prior work to augment decision-making at-the-edge, thereby, promising a true distributed control architecture for urban air mobility. In this approach, each agent (a) builds a potential in-flight conflict map, (b) identifies the conflicting agents, (c) dynamically prepares a list of alternatives based on its current utility functions, (d) negotiates with the conflicting agents to pick one of these alternatives, and (e) implements the negotiated alternative to mutually resolve the conflict. Note that such an approach does not require a contingency plan to be made pre-flight, as the conflict resolution strategies are decided and negotiated in real time based on the present state of the agent. The contingency plan, if available, can serve as an input to the real-time conflict resolution strategy formulation, and also can be used as a fallback plan in case the negotiation fails and the impacted agents need to switch to a rule-based/supervisory resolution mode from the discussed distributed resolution mode. The presented collaborative negotiation-based conflict resolution technique incorporates a time-dependent reward function to catalyze collaborative resolution by incentivizing the agents with local and global rewards beneficial to their business operations.

Advanced Air Mobility↗
NASA NTRS2018

Methods for Passive Optical Detection and Relative Navigation for Rendezvous with a Non-Cooperative Object at Mars

Long-range passive optical detection of an orbiting inert sphere by a robotic Mars orbiter is investigated and trades are described in terms of detectability via reflected visible light in the presence of orbit uncertainty, gravitational perturbations, and camera electronics noise. A new approximate equation for signal-tonoise ratio (SNR) is developed to include most relevant camera imperfections, diffraction, and stray light from the Mars limb as relevant to this scenario. Using this method, a notional camera suite is designed to meet detection, navigation, and redundancy requirements for an example mission scenario. Results from a simulation tool demonstrate the long-range initial detection strategy in the presence of perturbations from various sources. Finally, navigation analysis shows that the information gathered using passive optical detection is sufficient to begin orbit matching.

Woolley, Ryan C.↗
NASA NTRS2020

A Visual Analytics Approach to Debugging Cooperative, Autonomous Multi-Robot Systems’ Worldviews

Autonomous multi-robot systems, where a team of robots shares information to perform tasks that are beyond an individual robot’s abilities, hold great promise for a number of applications, such as planetary exploration missions. Each robot in a multi- robot system autonomously schedules which robots should perform a given task and when, using its worldview–the robot’s internal representation of its belief about the environment and other robots’ states. A key problem for operators is that robots’ worldviews can fall out of sync (often due to weak communication links), leading to desynchronization of the robots’ scheduling decisions and inconsistent emergent behavior (e.g., tasks not performed, or performed by multiple robots). Operators face the time-consuming and difficult task of making sense of the robots’ scheduling decisions, detecting de-synchronizations, and pinpointing their cause by comparing every robot’s worldview. To address these challenges, we introduce MOSAIC Viewer, a visual analytics system that helps operators (i) make sense of the robots’ schedules and (ii) detect and conduct a root cause analysis of the robots’ desynchronized worldviews. Over a year-long partnership with roboticists at the NASA Jet Propulsion Laboratory, a formative study was performed to identify the necessary system design requirements, which supports the design of the system. A qualitative study with 12 roboticists reveals that MOSAIC Viewer is faster- and easier-to-use than the users’ current approaches, and it allows them to stitch low-level details to formulate a high-level understanding of the robots’ schedules and detect and pin-point the cause of desynchronized worldviews.

Ma, Kwan-Liu↗