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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.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Interactive autonomy and robotic skills

Current concepts of robot-supported operations for space laboratories (payload servicing, inspection, repair, and ORU exchange) are mainly based on the concept of 'interactive autonomy' which implies autonomous behavior of the robot according to predefined timelines, predefined sequences of elementary robot operations and within predefined world models supplying geometrical and other information for parameter instantiation on the one hand, and the ability to override and change the predefined course of activities by human intervention on the other hand. Although in principle a very powerful and useful concept, in practice the confinement of the robot to the abstract world models and predefined activities appears to reduce the robot's stability within real world uncertainties and its applicability to non-predefined parts of the world, calling for frequent corrective interaction by the operator, which in itself may be tedious and time-consuming. Methods are presented to improve this situation by incorporating 'robotic skills' into the concept of interactive autonomy.

Kellner, A.↗
NASA NTRS1989

Global models: Robot sensing, control, and sensory-motor skills

Robotics research has begun to address the modeling and implementation of a wide variety of unstructured tasks. Examples include automated navigation, platform servicing, custom fabrication and repair, deployment and recovery, and science exploration. Such tasks are poorly described at onset; the workspace layout is partially unfamiliar, and the task control sequence is only qualitatively characterized. The robot must model the workspace, plan detailed physical actions from qualitative goals, and adapt its instantaneous control regimes to unpredicted events. Developing robust representations and computational approaches for these sensing, planning, and control functions is a major challenge. The underlying domain constraints are very general, and seem to offer little guidance for well-bounded approximation of object shape and motion, manipulation postures and trajectories, and the like. This generalized modeling problem is discussed, with an emphasis on the role of sensing. It is also discussed that unstructured tasks often have, in fact, a high degree of underlying physical symmetry, and such implicit knowledge should be drawn on to model task performance strategies in a methodological fashion. A group-theoretic decomposition of the workspace organization, task goals, and their admissible interactions are proposed. This group-mechanical approach to task representation helps to clarify the functional interplay of perception and control, in essence, describing what perception is specifically for, versus how it is generically modeled. One also gains insight how perception might logically evolve in response to needs of more complex motor skills. It is discussed why, of the many solutions that are often mathematically admissible to a given sensory motor-coordination problem, one may be preferred over others.

Schenker, Paul S.↗
NASA NTRS1989

Instruction dialogues: Teaching new skills to a robot

Extended dialogues between a human user and a robot system are presented. The purpose of each dialogue is to teach the robot a new skill or to improve the performance of a skill it already has. The particular interest is in natural language dialogues but the illustrated techniques can be applied to any high level language. The primary purpose is to show how verbal instruction can be integrated with the robot's autonomous learning of a skill.

Crangle, Colleen↗
NASA NTRS2003

A new method to evaluate human-robot system performance

One of the key issues in space exploration is that of deciding what space tasks are best done with humans, with robots, or a suitable combination of each. In general, human and robot skills are complementary. Humans provide as yet unmatched capabilities to perceive, think, and act when faced with anomalies and unforeseen events, but there can be huge potential risks to human safety in getting these benefits. Robots provide complementary skills in being able to work in extremely risky environments, but their ability to perceive, think, and act by themselves is currently not error-free, although these capabilities are continually improving with the emergence of new technologies. Substantial past experience validates these generally qualitative notions. However, there is a need for more rigorously systematic evaluation of human and robot roles, in order to optimize the design and performance of human-robot system architectures using well-defined performance evaluation metrics. This article summarizes a new analytical method to conduct such quantitative evaluations. While the article focuses on evaluating human-robot systems, the method is generally applicable to a much broader class of systems whose performance needs to be evaluated.

Space Flight/instrumentation↗
NASA NTRS1991

Fusing human and machine skills for remote robotic operations

The question of how computer assists can improve teleoperator trajectory tracking during both free and force-constrained motions is addressed. Computer graphics techniques which enable the human operator to both visualize and predict detailed 3D trajectories in real-time are reported. Man-machine interactive control procedures for better management of manipulator contact forces and positioning are also described. It is found that collectively, these novel advanced teleoperations techniques both enhance system performance and significantly reduce control problems long associated with teleoperations under time delay. Ongoing robotic simulations of the 1984 space shuttle Solar Maximum EVA Repair Mission are briefly described.

Schenker, Paul S.↗
NASA NTRS1994

Integrating deliberative planning in a robot architecture

The role of planning and reactive control in an architecture for autonomous agents is discussed. The postulated architecture seperates the general robot intelligence problem into three interacting pieces: (1) robot reactive skills, i.e., grasping, object tracking, etc.; (2) a sequencing capability to differentially ativate the reactive skills; and (3) a delibrative planning capability to reason in depth about goals, preconditions, resources, and timing constraints. Within the sequencing module, caching techniques are used for handling routine activities. The planning system then builds on these cached solutions to routine tasks to build larger grain sized primitives. This eliminates large numbers of essentially linear planning problems. The architecture will be used in the future to incorporate in robots cognitive capabilites normally associated with intelligent behavior.

Elsaesser, Chris↗
NASA NTRS1991

Sensor fusion III: 3-D perception and recognition; Proceedings of the Meeting, Boston, MA, Nov. 5-8, 1990

The volume on data fusion from multiple sources discusses fusing multiple views, temporal analysis and 3D motion interpretation, sensor fusion and eye-to-hand coordination, and integration in human shape perception. Attention is given to surface reconstruction, statistical methods in sensor fusion, fusing sensor data with environmental knowledge, computational models for sensor fusion, and evaluation and selection of sensor fusion techniques. Topics addressed include the structure of a scene from two and three projections, optical flow techniques for moving target detection, tactical sensor-based exploration in a robotic environment, and the fusion of human and machine skills for remote robotic operations. Also discussed are K-nearest-neighbor concepts for sensor fusion, surface reconstruction with discontinuities, a sensor-knowledge-command fusion paradigm for man-machine systems, coordinating sensing and local navigation, and terrain map matching using multisensing techniques for applications to autonomous vehicle navigation.

Schenker, Paul S.↗
NASA NTRS1994

Mobile robot exploration and navigation of indoor spaces using sonar and vision

Integration of skills into an autonomous robot that performs a complex task is described. Time constraints prevented complete integration of all the described skills. The biggest problem was tuning the sensor-based region-finding algorithm to the environment involved. Since localization depended on matching regions found with the a priori map, the robot became lost very quickly. If the low level sensing of the world is not working, then high level reasoning or map making will be unsuccessful.

Kortenkamp, David↗
NASA NTRS1992

Tool for simulating space exploration initiative (SEI) operations as a means of obtaining intelligent systems requirements

The Lyndon B. Johnson Space Center Automation and Robotics Division has developed a simulation tool for use in evaluating the feasibility and effectiveness of proposed candidate mission concepts, such as the First Lunar Outpost design reference missions. The tool helps in defining requirements for such missions at the beginning of the definition activities and can be applied iteratively thereafter on a short cycle basis as changes are made to the mission definition. The simulation is applicable to the amount and capabilities of automation and robotics; number and skills of crew; amount of engineering work, science, and in-space materials utilization to be accomplished; impact of provision for maintenance and repair; and flight schedules and manifests. The simulation accounts for supply and demand of resources to accomplish tasks and accounts for elapsed time in carrying out mission processes and tasks.

Erickson, Jon D.↗
NASA NTRS2017

Assimilation of AERONET and MODIS AOT Observations Using Variational and Ensemble Data Assimilation Methods and Its Impact on Aerosol Forecasting Skill

Data assimilation of Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness (AOT) for aerosol forecasting was tested within the Navy Aerosol Analysis Prediction System (NAAPS) framework, using variational and ensemble data assimilation methods. Navy aerosol forecasting currently makes use of a deterministic NAAPS simulation coupled to Navy Variational Data Assimilation System for aerosol optical depth, a two-dimensional variational data assimilation system, for MODIS AOT assimilation. An ensemble version of NAAPS (ENAAPS) coupled to an ensemble adjustment Kalman filter (EAKF) from the Data Assimilation Research Testbed was recently developed, allowing for a range of data assimilation and forecasting experiments to be run with deterministic NAAPS and ENAAPS. The main findings are that the EAKF, with its flow-dependent error covariances, makes better use of sparse observations such as AERONET AOT. Assimilating individual AERONET observations in the two-dimensional variational system can increase the analysis errors when observations are located in high AOT gradient regions. By including AERONET with MODIS AOT assimilation, the magnitudes of peak aerosol events (AOT> 1) were better captured with improved temporal variability, especially in India and Asia where aerosol prediction is a challenge. Assimilating AERONET AOT with MODIS had little impact on the 24 h forecast skill compared to MODIS assimilation only, but differences were found downwind of AERONET sites. The 24 h forecast skill was approximately the same for forecasts initialized with analyses from AERONET AOT assimilation alone compared to MODIS assimilation, particularly in regions where the AERONET network is dense; including the United States and Europe, indicating that AERONET could serve as a backup observation network for over-land synoptic-scale aerosol events.

Rubin, Juli I.↗
NASA NTRS2011

Lunabotics Mining Competition: Inspiration Through Accomplishment

NASA's Lunabotics Mining Competition is designed to promote the development of interest in space activities and STEM (Science, Technology, Engineering, and Mathematics) fields. The competition uses excavation, a necessary first step towards extracting resources from the regolith and building bases on the moon. The unique physical properties of lunar regolith and the reduced 1/6th gravity, vacuum environment make excavation a difficult technical challenge. Advances in lunar regolith mining have the potential to significantly contribute to our nation's space vision and NASA space exploration operations. The competition is conducted annually by NASA at the Kennedy Space Center Visitor Complex. The teams that can use telerobotic or autonomous operation to excavate a lunar regolith geotechnical simulant, herein after referred to as Black Point-1 (or BP-1) and score the most points (calculated as an average of two separate 10-minute timed competition attempts) will eam points towards the Joe Kosmo Award for Excellence and the scores will reflect ranking in the on-site mining category of the competition. The minimum excavation requirement is 10.0 kg during each competition attempt and the robotic excavator, referred to as the "Lunabot", must meet all specifications. This paper will review the achievements of the Lunabotics Mining Competition in 2010 and 2011, and present the new rules for 2012. By providing a framework for robotic design and fabrication, which culminates in a live competition event, university students have been able to produce sophisticated lunabots which are tele-operated. Multi-disciplinary teams are encouraged and the extreme sense of accomplishment provides a unique source of inspiration to the participating students, which has been shown to translate into increased interest in STEM careers. Our industrial sponsors (Caterpillar, Newmont Mining, Harris, Honeybee Robotics) have all stated that there is a strong need for skills in the workforce related to robotics and automated machines. In 2010, 22 United States (US) universities competed, and in May 2011 the competition was opened to international participation, with 46 Universities attending. There were 12 international teams and 34 US teams. This combined total directly inspired an estimated 544 university students. More students and the public were engaged via internet broadcasting and social networking media. This is expected to be of value for actual future space missions, as knowledge is gained from testing many innovative prototypes in simulated lunar regolith. More information is available at www.nasa.gov/lunabotics/.

Mueller, Robert P.↗
NASA NTRS1989

Applications of artificial intelligence to space station and automated software techniques: High level robot command language

The objective is to develop a system that will allow a person not necessarily skilled in the art of programming robots to quickly and naturally create the necessary data and commands to enable a robot to perform a desired task. The system will use a menu driven graphical user interface. This interface will allow the user to input data to select objects to be moved. There will be an imbedded expert system to process the knowledge about objects and the robot to determine how they are to be moved. There will be automatic path planning to avoid obstacles in the work space and to create a near optimum path. The system will contain the software to generate the required robot instructions.

Mckee, James W.↗
NASA NTRS2015

Telerobotic Perception During Asteroid and Mars Regolith Operations Project

Current space telerobotic systems are constrained to only operating in bright light and dust-free conditions. This project will study the effects of difficult lighting and dust conditions on telerobotic perception systems to better assess and refine regolith operations on other neighboring celestial bodies. In partnership with Embry-Riddle Aeronautical University and Caterpillar, Inc., optical, LiDAR and RADAR sensing equipment will be used in performing the study. This project will create a known dust environment in the Swamp Works Granular Mechanics & Regolith Operations (GMRO) Laboratory regolith test bin to characterize the behavior of the sensing equipment in various calibrated lighting and dust conditions. It will also identify potential methods for mitigating the impacts of these undesirable conditions on the performance of the sensing equipment. Enhancing the capability of telerobotic perception systems will help improve life on earth for those working in dangerous, dusty mining conditions, as well as help advance the same technologies used for safer self-driving automobiles in various lighting and weather conditions. It will also prove to be a critical skill needed for advancing robotic and human exploration throughout our solar system, for activities such as mining on an asteroid or pioneering the first colony on Mars.

Technology Portfolio System↗
NASA NTRS2012

EVA Skills Training

Dr. Parazynski and a colleague from Extravehicular Activity (EVA), Robotics, & Crew Systems Operations (DX) worked closely to build the EVA Skills Training Program, and for the first time, defined the gold standards of EVA performance, allowing crewmembers to increase their performance significantly. As part of the program, individuals had the opportunity to learn at their own rate, taking additional water time as required, to achieve that level of performance. This focus on training to one's strengths and weaknesses to bolster them enabled the Crew Office and DX to field a much larger group of spacewalkers for the daunting "wall of EVA" required for the building and maintenance of the ISS. Parazynski also stressed the need for designers to understand the capabilities and the limitations of a human in a spacesuit, as well as opportunities to improve future generations of space. He shared lessons learned (how the Crew Office engaged in these endeavors) and illustrated the need to work as a team to develop these complex systems.

Parazynski, Scott↗
NASA NTRS2008

Developing Humanoid Robots for Real-World Environments

Humanoids are steadily improving in appearance and functionality demonstrated in controlled environments. To address the challenges of operation in the real-world, researchers have proposed the use of brain-inspired architectures for robot control, and the use of robot learning techniques that enable the robot to acquire and tune skills and behaviours. In the first part of the paper we introduce new concepts and results in these two areas. First, we present a cerebellum-inspired model that demonstrated efficiency in the sensory-motor control of anthropomorphic arms, and in gait control of dynamic walkers. Then, we present a set of new ideas related to robot learning, emphasizing the importance of developing teaching techniques that support learning. In the second part of the paper we propose the use in robotics of the iterative and incremental development methodologies, in the context of practical task-oriented applications. These methodologies promise to rapidly reach system-level integration, and to early identify system-level weaknesses to focus on. We apply this methodology in a task targeting the automated assembly of a modular structure using HOAP-2. We confirm this approach led to rapid development of a end-to-end capability, and offered guidance on which technologies to focus on for gradual improvement of a complete functional system. It is believed that providing Grand Challenge type milestones in practical task-oriented applications accelerates development. As a meaningful target in short-mid term we propose the 'IKEA Challenge', aimed at the demonstration of autonomous assembly of various pieces of furniture, from the box, following included written/drawn instructions.

Stoica, Adrian↗
NASA NTRS2002

Pittsburgh Public School District / Carnegie Mellon University Robotics Team Participation in the US First Competition

FIRST, For Inspiration and Recognition of Science and Technology, is an international program designed to encourage junior and senior high school students to participate in science and technology related activities. FIRST attempts to increase enthusiasm for technology by providing a competitive environment in which to demonstrate robotics technology designed for a particular set of tasks. Carnegie Mellon University provided student members of the project the opportunity to complete the design, construction, testing, and operation of a robot. Electrical, mechanical, and programming skills were stressed, with both adult and senior students acting as mentors for more junior members. Teamwork and integration was also stressed in order to provide students with a realistic feel for project-based work. Finally, an emphasis was placed on recruiting students with greater difficulty in entering technological fields: girls and ethnic minorities and students leaning toward humanities (especially art). Carnegie Mellon built a relationship with Taylor Allderdice High School that lasted four years. For four years, the success of the project increased each year. Each term, the students successfully designed and built a working robot that could fully participate in the competition. The enthusiasm of the students has been the cornerstone of the recruit of new students, keeping the project growing and vital. Carnegie Mellon's participation with Allderdice has been an overall great success.

Stroupe, Ashley↗