The 1990 progress report and future plans

This document describes the progress and plans of the Artificial Intelligence Research Branch (RIA) at ARC in 1990. Activities span a range from basic scientific research to engineering development and to fielded NASA applications, particularly those applications that are enabled by basic research carried out at RIA. Work is conducted in-house and through collaborative partners in academia and industry. Our major focus is on a limited number of research themes with a dual commitment to technical excellence and proven applicability to NASA short, medium, and long-term problems. RIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at JPL and AI applications groups at all NASA centers

Autonomous Systems, Robotics, and Computing Systems Capability Roadmap: NRC Dialogue

Contents include the following: Introduction. Process, Mission Drivers, Deliverables, and Interfaces. Autonomy. Crew-Centered and Remote Operations. Integrated Systems Health Management. Autonomous Vehicle Control. Autonomous Process Control. Robotics. Robotics for Solar System Exploration. Robotics for Lunar and Planetary Habitation. Robotics for In-Space Operations. Computing Systems. Conclusion

Progress in AI Planning Research and Applications

Planning has made significant progress since its inception in the 1970s, in terms both of the efficiency and sophistication of its algorithms and representations and its potential for application to real problems. In this paper we sketch the foundations of planning as a sub-field of Artificial Intelligence and the history of its development over the past three decades. Then some of the recent achievements within the field are discussed and provided some experimental data demonstrating the progress that has been made in the application of general planners to realistic and complex problems. The paper concludes by identifying some of the open issues that remain as important challenges for future research in planning

3D Path planning using a fuzzy logic navigational map for Planetary Surface Rovers

This work proposes an innovative app navigation path-planning problem exploration rovers by including terrain characteristics. The objective is to enhance the typical 2D arithmetical cost function by adding 3D information computed from the laser-scanned terrain such as terrain height, slopes, shadows, orientation and terrain roughness. This paper describes the algorithm developed by UPM and GMV and the tests made at the GMV outdoor test facilities using the Moon-Hound rover. This rover is a 50 Kg rover including a Sick laser mounted on a pan&tilt unit for generation of 3D Digital Elevation Models (DEM’s). Experimental results have shown the effectiveness of the proposed approach

Simulating Operational Concepts for Autonomous Robotic Space Exploration Systems: A Framework for Early Design Validation

During mission design, the concept of operations (ConOps) describes how the system operates during various life cycle phases to meet stakeholder expectations. ConOps is sometimes declined in a simple evaluation of the power consumption or data generation per mode. Different operational timelines are typically developed based on expert knowledge. This approach is robust when designing an automated system or a system with a low level of autonomy. However, when studying highly autonomous systems, designers may be interested in understanding how the system would react in an operational scenario when provided with knowledge about its actions and operational environment. These considerations can help verify and validate the proposed ConOps architecture, highlight shortcomings in both physical and functional design, and help better formulate detailed requirements. Hence, this study aims to provide a framework for the simulation and validation of operational scenarios for autonomous robotic space exploration systems during the preliminary design phases. This study extends current efforts in autonomy technology for planetary systems by focusing on testing their operability and assessing their performances in different scenarios early in the design process. The framework uses Model-Based Systems Engineering (MBSE) as the knowledge base for the studied system and its operations. It then leverages a Markov Decision Process (MDP) to simulate a set of system operations in a relevant scenario. It then outputs a feasible plan with the associated variation of a set of considered resources as step functions. This method was applied to simulate the operations of a small rover exploring an unknown environment to observe and sample a set of targets

Engineering Resilient Space Systems

Several distinct trends will influence space exploration missions in the next decade. Destinations are becoming more remote and mysterious, science questions more sophisticated, and, as mission experience accumulates, the most accessible targets are visited, advancing the knowledge frontier to more difficult, harsh, and inaccessible environments. This leads to new challenges including: hazardous conditions that limit mission lifetime, such as high radiation levels surrounding interesting destinations like Europa or toxic atmospheres of planetary bodies like Venus; unconstrained environments with navigation hazards, such as free-floating active small bodies; multielement missions required to answer more sophisticated questions, such as Mars Sample Return (MSR); and long-range missions, such as Kuiper belt exploration, that must survive equipment failures over the span of decades. These missions will need to be successful without a priori knowledge of the most efficient data collection techniques for optimum science return. Science objectives will have to be revised ‘on the fly’, with new data collection and navigation decisions on short timescales. Yet, even as science objectives are becoming more ambitious, several critical resources remain unchanged. Since physics imposes insurmountable light-time delays, anticipated improvements to the Deep Space Network (DSN) will only marginally improve the bandwidth and communications cadence to remote spacecraft. Fiscal resources are increasingly limited, resulting in fewer flagship missions, smaller spacecraft, and less subsystem redundancy. As missions visit more distant and formidable locations, the job of the operations team becomes more challenging, seemingly inconsistent with the trend of shrinking mission budgets for operations support. How can we continue to explore challenging new locations without increasing risk or system complexity? These challenges are present, to some degree, for the entire Decadal Survey mission portfolio, as documented in Vision and Voyages for Planetary Science in the Decade 2013–2022 (National Research Council, 2011), but are especially acute for the following mission examples, identified in our recently completed KISS Engineering Resilient Space Systems (ERSS) study: 1. A Venus lander, designed to sample the atmosphere and surface of Venus, would have to perform science operations as components and subsystems degrade and fail; 2. A Trojan asteroid tour spacecraft would spend significant time cruising to its ultimate destination (essentially hibernating to save on operations costs), then upon arrival, would have to act as its own surveyor, finding new objects and targets of opportunity as it approaches each asteroid, requiring response on short notice; and 3. A MSR campaign would not only be required to perform fast reconnaissance over long distances on the surface of Mars, interact with an unknown physical surface, and handle degradations and faults, but would also contain multiple components (launch vehicle, cruise stage, entry and landing vehicle, surface rover, ascent vehicle, orbiting cache, and Earth return vehicle) that dramatically increase the need for resilience to failure across the complex system. The concept of resilience and its relevance and application in various domains was a focus during the study, with several definitions of resilience proposed and discussed. While there was substantial variation in the specifics, there was a common conceptual core that emerged—adaptation in the presence of changing circumstances. These changes were couched in various ways—anomalies, disruptions, discoveries—but they all ultimately had to do with changes in underlying assumptions. Invalid assumptions, whether due to unexpected changes in the environment, or an inadequate understanding of interactions within the system, may cause unexpected or unintended system behavior. A system is resilient if it continues to perform the intended functions in the presence of invalid assumptions. Our study focused on areas of resilience that we felt needed additional exploration and integration, namely system and software architectures and capabilities, and autonomy technologies. (While also an important consideration, resilience in hardware is being addressed in multiple other venues, including 2 other KISS studies.) The study consisted of two workshops, separated by a seven-month focused study period. The first workshop (Workshop #1) explored the ‘problem space’ as an organizing theme, and the second workshop (Workshop #2) explored the ‘solution space’. In each workshop, focused discussions and exercises were interspersed with presentations from participants and invited speakers. The study period between the two workshops was organized as part of the synthesis activity during the first workshop. The study participants, after spending the initial days of the first workshop discussing the nature of resilience and its impact on future science missions, decided to split into three focus groups, each with a particular thrust, to explore specific ideas further and develop material needed for the second workshop. The three focus groups and areas of exploration were: 1. Reference missions: address/refine the resilience needs by exploring a set of reference missions 2. Capability survey: collect, document, and assess current efforts to develop capabilities and technology that could be used to address the documented needs, both inside and outside NASA 3. Architecture: analyze the impact of architecture on system resilience, and provide principles and guidance for architecting greater resilience in our future systems The key product of the second workshop was a set of capability roadmaps pertaining to the three reference missions selected for their representative coverage of the types of space missions envisioned for the future. From these three roadmaps, we have extracted several common capability patterns that would be appropriate targets for near-term technical development: one focused on graceful degradation of system functionality, a second focused on data understanding for science and engineering applications, and a third focused on hazard avoidance and environmental uncertainty. Continuing work is extending these roadmaps to identify candidate enablers of the capabilities from the following three categories: architecture solutions, technology solutions, and process solutions. The KISS study allowed a collection of diverse and engaged engineers, researchers, and scientists to think deeply about the theory, approaches, and technical issues involved in developing and applying resilience capabilities. The conclusions summarize the varied and disparate discussions that occurred during the study, and include new insights about the nature of the challenge and potential solutions: 1. There is a clear and definitive need for more resilient space systems. During our study period, the key scientists/engineers we engaged to understand potential future missions confirmed the scientific and risk reduction value of greater resilience in the systems used to perform these missions. 2. Resilience can be quantified in measurable terms—project cost, mission risk, and quality of science return. In order to consider resilience properly in the set of engineering trades performed during the design, integration, and operation of space systems, the benefits and costs of resilience need to be quantified. We believe, based on the work done during the study, that appropriate metrics to measure resilience must relate to risk, cost, and science quality/opportunity. Additional work is required to explicitly tie design decisions to these first-order concerns. 3. There are many existing basic technologies that can be applied to engineering resilient space systems. Through the discussions during the study, we found many varied approaches and research that address the various facets of resilience, some within NASA, and many more beyond. Examples from civil architecture, Department of Defense (DoD) / Defense Advanced Research Projects Agency (DARPA) initiatives, ‘smart’ power grid control, cyber-physical systems, software architecture, and application of formal verification methods for software were identified and discussed. The variety and scope of related efforts is encouraging and presents many opportunities for collaboration and development, and we expect many collaborative proposals and joint research as a result of the study. 4. Use of principled architectural approaches is key to managing complexity and integrating disparate technologies. The main challenge inherent in considering highly resilient space systems is that the increase in capability can result in an increase in complexity with all of the 3 risks and costs associated with more complex systems. What is needed is a better way of conceiving space systems that enables incorporation of capabilities without increasing complexity. We believe principled architecting approaches provide the needed means to convey a unified understanding of the system to primary stakeholders, thereby controlling complexity in the conception and development of resilient systems, and enabling the integration of disparate approaches and technologies. A representative architectural example is included in Appendix F. 5. Developing trusted resilience capabilities will require a diverse yet strategically directed research program. Despite the interest in, and benefits of, deploying resilience space systems, to date, there has been a notable lack of meaningful demonstrated progress in systems capable of working in hazardous uncertain situations. The roadmaps completed during the study, and documented in this report, provide the basis for a real funded plan that considers the required fundamental work and evolution of needed capabilities. Exploring space is a challenging and difficult endeavor. Future space missions will require more resilience in order to perform the desired science in new environments under constraints of development and operations cost, acceptable risk, and communications delays. Development of space systems with resilient capabilities has the potential to expand the limits of possibility, revolutionizing space science by enabling as yet unforeseen missions and breakthrough science observations. Our KISS study provided an essential venue for the consideration of these challenges and goals. Additional work and future steps are needed to realize the potential of resilient systems—this study provided the necessary catalyst to begin this process