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Clancey, William J.

Publications and source records attributed to Clancey, William J..

At least 19 records

Exploration Technologies for Operations

Although the International Space Station (ISS) assembly has been completed, the Operations support teams continue to seek more efficient and effective ways to prepare for and conduct the ISS operations and future exploration missions beyond low earth orbit. This search for improvement has led to a significant collaboration between the NASA research and advanced software development community at NASA Ames Research Center and the Mission Operations community at NASA Johnson Space Center. Since 2001, NASA Ames Research Center has been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for several of the unmanned Mars missions operations. Since 2006, NASA Ames Research Center has also been developing and applying its advanced intelligent systems and human systems integration research to mission operations tools for manned operations support with the Mission Operations Directorate at NASA Johnson Space Center. This paper discusses the completion of the development and deployment of a variety of intelligent and human systems technologies adopted for manned mission operations. The technologies associated with the projects include advanced software systems for operations and human-centered computing. Human-centered computing looks to the processes and procedures that people do to perform any given job, then attempts to identify opportunities to improve these processes and procedures. In particular, for mission operations, improvements are quantified by specifically identifying how a tool can increase a persons efficiency, enhance a persons functional capability, andor improve the assurance of a persons decisions. The Ames development team has collaborated with the Mission Operations team to identify areas of efficiencies through technology infusion applications in support of the Plan, Train, and Fly activities of human-spaceflight mission operations. The specific applications discussed in this paper are in the areas of mission planning systems, mission operations design modeling and workflow automation, advanced systems monitoring, mission control technologies, search tools, training management tools, spacecraft solar array management, spacecraft power management, and spacecraft attitude planning. We discuss these specific projects between the Ames Research Center and the Johnson Space Centers Mission Operations Directorate, and how these technologies and projects are enhancing the mission operations support for the International Space Station. We also discuss the challenges, problems, and successes associated with long-distance and multi-year development projects between the research team at Ames and the Mission Operations customers at Johnson Space center. Finally, we discuss how these technology infusion applications and underlying technologies might be used in the future to support on-board operations of the crew and spacecraft systems as human exploration expands beyond low earth orbit to destinations in the solar system where communications delays will require more on-board autonomy and planning by the crew. Longer communications delays will require that the ground mission operations support will be primarily strategic in nature, while the tactical level of planning, systems monitoring and control, and failure analysisisolationrecovery will be the responsibility of both the spacecraft autonomous systems and the crew. Our expectation is that the technologies

mission operations

Aviation Safety: Modeling and Analyzing Complex Interactions between Humans and Automated Systems

The on-going transformation from the current US Air Traffic System (ATS) to the Next Generation Air Traffic System (NextGen) will force the introduction of new automated systems and most likely will cause automation to migrate from ground to air. This will yield new function allocations between humans and automation and therefore change the roles and responsibilities in the ATS. Yet, safety in NextGen is required to be at least as good as in the current system. We therefore need techniques to evaluate the safety of the interactions between humans and automation. We think that current human factor studies and simulation-based techniques will fall short in front of the ATS complexity, and that we need to add more automated techniques to simulations, such as model checking, which offers exhaustive coverage of the non-deterministic behaviors in nominal and off-nominal scenarios. In this work, we present a verification approach based both on simulations and on model checking for evaluating the roles and responsibilities of humans and automation. Models are created using Brahms (a multi-agent framework) and we show that the traditional Brahms simulations can be integrated with automated exploration techniques based on model checking, thus offering a complete exploration of the behavioral space of the scenario. Our formal analysis supports the notion of beliefs and probabilities to reason about human behavior. We demonstrate the technique with the Ueberligen accident since it exemplifies authority problems when receiving conflicting advices from human and automated systems.

Muti-agent System

Work Practice Simulation of Complex Human-Automation Systems in Safety Critical Situations: The Brahms Generalized berlingen Model

The transition from the current air traffic system to the next generation air traffic system will require the introduction of new automated systems, including transferring some functions from air traffic controllers to on­-board automation. This report describes a new design verification and validation (V&V) methodology for assessing aviation safety. The approach involves a detailed computer simulation of work practices that includes people interacting with flight-critical systems. The research is part of an effort to develop new modeling and verification methodologies that can assess the safety of flight-critical systems, system configurations, and operational concepts. The 2002 Ueberlingen mid-air collision was chosen for analysis and modeling because one of the main causes of the accident was one crew's response to a conflict between the instructions of the air traffic controller and the instructions of TCAS, an automated Traffic Alert and Collision Avoidance System on-board warning system. It thus furnishes an example of the problem of authority versus autonomy. It provides a starting point for exploring authority/autonomy conflict in the larger system of organization, tools, and practices in which the participants' moment-by-moment actions take place. We have developed a general air traffic system model (not a specific simulation of Überlingen events), called the Brahms Generalized Ueberlingen Model (Brahms-GUeM). Brahms is a multi-agent simulation system that models people, tools, facilities/vehicles, and geography to simulate the current air transportation system as a collection of distributed, interactive subsystems (e.g., airports, air-traffic control towers and personnel, aircraft, automated flight systems and air-traffic tools, instruments, crew). Brahms-GUeM can be configured in different ways, called scenarios, such that anomalous events that contributed to the Überlingen accident can be modeled as functioning according to requirements or in an anomalous condition, as occurred during the accident. Brahms-GUeM thus implicitly defines a class of scenarios, which include as an instance what occurred at Überlingen. Brahms-GUeM is a modeling framework enabling "what if" analysis of alternative work system configurations and thus facilitating design of alternative operations concepts. It enables subsequent adaption (reusing simulation components) for modeling and simulating NextGen scenarios. This project demonstrates that BRAHMS provides the capacity to model the complexity of air transportation systems, going beyond idealized and simple flights to include for example the interaction of pilots and ATCOs. The research shows clearly that verification and validation must include the entire work system, on the one hand to check that mechanisms exist to handle failures of communication and alerting subsystems and/or failures of people to notice, comprehend, or communicate problematic (unsafe) situations; but also to understand how people must use their own judgment in relating fallible systems like TCAS to other sources of information and thus to evaluate how the unreliability of automation affects system safety. The simulation shows in particular that distributed agents (people and automated systems) acting without knowledge of each others' actions can create a complex, dynamic system whose interactive behavior is unexpected and is changing too quickly to comprehend and control.

complex systems

Software Productivity of Field Experiments Using the Mobile Agents Open Architecture with Workflow Interoperability

We analyzed a series of ten systematically developed surface exploration systems that integrated a variety of hardware and software components. Design, development, and testing data suggest that incremental buildup of an exploration system for long-duration capabilities is facilitated by an open architecture with appropriate-level APIs, specifically designed to facilitate integration of new components. This improves software productivity by reducing changes required for reconfiguring an existing system.

Clancey, William J.

ISS Operations Cost Reductions Through Automation of Real-Time Planning Tasks

In 2007 the Johnson Space Center s Mission Operations Directorate (MOD) management team challenged their organizations to find ways to reduce the cost of operations for supporting the International Space Station (ISS) in the Mission Control Center (MCC). Each MOD organization was asked to define and execute projects that would help them attain cost reductions by 2012. The MOD Operations Division Flight Planning Branch responded to this challenge by launching several software automation projects that would allow them to greatly improve console operations and reduce ISS console staffing and intern reduce operating costs. These tasks ranged from improving the management and integration mission plan changes, to automating the uploading and downloading of information to and from the ISS and the associated ground complex tasks that required multiple decision points. The software solutions leveraged several different technologies including customized web applications and implementation of industry standard web services architecture; as well as engaging a previously TRL 4-5 technology developed by Ames Research Center (ARC) that utilized an intelligent agent-based system to manage and automate file traffic flow, archive data, and generate console logs. These projects to date have allowed the MOD Operations organization to remove one full time (7 x 24 x 365) ISS console position in 2010; with the goal of eliminating a second full time ISS console support position by 2012. The team will also reduce one long range planning console position by 2014. When complete, these Flight Planning Branch projects will account for the elimination of 3 console positions and a reduction in staffing of 11 engineering personnel (EP) for ISS.

Hall, Timothy A.

NASA's OCA Mirroring System: An Application of Multiagent Systems in Mission Control

Orbital Communications Adaptor (OCA) Flight Controllers, in NASA's International Space Station Mission Control Center, use different computer systems to uplink, downlink, mirror, archive, and deliver files to and from the International Space Station (ISS) in real time. The OCA Mirroring System (OCAMS) is a multiagent software system (MAS) that is operational in NASA's Mission Control Center. This paper presents OCAMS and its workings in an operational setting where flight controllers rely on the system 24x7. We also discuss the return on investment, based on a simulation baseline, six months of 24x7 operations at NASA Johnson Space Center in Houston, Texas, and a projection of future capabilities. This paper ends with a discussion of the value of MAS and future planned functionality and capabilities.

Sierhuis, Maarten

Workflow Agents vs. Expert Systems: Problem Solving Methods in Work Systems Design

During the 1980s, a community of artificial intelligence researchers became interested in formalizing problem solving methods as part of an effort called "second generation expert systems" (2nd GES). How do the motivations and results of this research relate to building tools for the workplace today? We provide an historical review of how the theory of expertise has developed, a progress report on a tool for designing and implementing model-based automation (Brahms), and a concrete example how we apply 2nd GES concepts today in an agent-based system for space flight operations (OCAMS). Brahms incorporates an ontology for modeling work practices, what people are doing in the course of a day, characterized as "activities." OCAMS was developed using a simulation-to-implementation methodology, in which a prototype tool was embedded in a simulation of future work practices. OCAMS uses model-based methods to interactively plan its actions and keep track of the work to be done. The problem solving methods of practice are interactive, employing reasoning for and through action in the real world. Analogously, it is as if a medical expert system were charged not just with interpreting culture results, but actually interacting with a patient. Our perspective shifts from building a "problem solving" (expert) system to building an actor in the world. The reusable components in work system designs include entire "problem solvers" (e.g., a planning subsystem), interoperability frameworks, and workflow agents that use and revise models dynamically in a network of people and tools. Consequently, the research focus shifts so "problem solving methods" include ways of knowing that models do not fit the world, and ways of interacting with other agents and people to gain or verify information and (ultimately) adapt rules and procedures to resolve problematic situations.

Clancey, William J.

Automating CapCom Using Mobile Agents and Robotic Assistants

Mobile Agents (MA) is an advanced Extra-Vehicular Activity (EVA) communications and computing system to increase astronaut self-reliance and safety, reducing dependence on continuous monitoring and advising from mission control on Earth. MA is voice controlled and provides information verbally to the astronauts through programs called "personal agents." The system partly automates the role of CapCom in Apollo-including monitoring and managing navigation, scheduling, equipment deployment, telemetry, health tracking, and scientific data collection. Data are stored automatically in a shared database in the habitat/vehicle and mirrored to a site accessible by a remote science team. The program has been developed iteratively in authentic work contexts, including six years of ethnographic observation of field geology. Analog field experiments in Utah enabled empirically discovering requirements and testing alternative technologies and protocols. We report on the 2004 system configuration, experiments, and results, in which an EVA robotic assistant (ERA) followed geologists approximately 150 m through a winding, narrow canyon. On voice command, the ERA took photographs and panoramas and was directed to serve as a relay on the wireless network.

Clancey, William J.

Human Activity Behavior and Gesture Generation in Virtual Worlds for Long- Duration Space Missions

A virtual worlds presentation technique with embodied, intelligent agents is being developed as an instructional medium suitable to present in situ training on long term space flight. The system combines a behavioral element based on finite state automata, a behavior based reactive architecture also described as subsumption architecture, and a belief-desire-intention agent structure. These three features are being integrated to describe a Brahms virtual environment model of extravehicular crew activity which could become a basis for procedure training during extended space flight.

Sierhuis, Maarten

To the North Coast of Devon: Collaborative Navigation While Exploring Unfamiliar Terrain

Navigation-knowing where one is and finding a safe route-is a fundamental aspect of all exploration. In unfamiliar terrain, one may use maps and instruments such as a compass or binoculars to assist, and people often collaborate in finding their way. This paper analyzes a group of people driving a humvee from a base camp to the north coast of Devon Island in the High Canadian Arctic. A complete audio recording and video during most stops allows a quantitative and semantic analysis of the conversations when the team stopped to take bearings and replan a route. Over a period of 2 hours, the humvee stopped 20 times, with an average duration of 3.15 min/pause and 3.85 min moving forward. The team failed to reach its goal due to difficult terrain causing mechanical problems. The analysis attempts to explain these facts by considering a variety of complicating factors, especially the navigation problem of relating maps and the world to locate the humvee and to plan a route. The analysis reveals patterns in topic structure and turn-taking, supporting the view that the collaboration was efficient, but the tools and information were inadequate for the task. This work is relevant for planning and training for planetary surface missions, as well as developing computer systems that could aid navigation.

Clancey, William J.

Prototype Software for Future Spaceflight Tested at Mars Desert Research Station

NASA scientists in MDRS Crew 49 (April 23-May 7, 2006) field tested and significantly extended a prototype monitoring and advising system that integrates power system telemetry with a voice commanding interface. A distributed, wireless network of functionally specialized agents interacted with the crew to provide alerts (e.g., impending shut-down of inverter due to low battery voltage), access md interpret historical data, and display troubleshooting procedures. In practical application during two weeks, the system generated speech over loudspeakers and headsets lo alert the crew about the need to investigate power system problems. The prototype system adapts the Brahms/Mobile Agents toolkit to receive data from the OneMeter (Brand Electronics) electric metering system deployed by Crew 47. A computer on the upper deck was connected to loudspeakers, four others were paired with wireless (Bluetooth) headsets that enabled crew members to interact with their personal agents from anywhere in the hab. Voice commands and inquiries included: 1. What is the {battery | generator} {volts | amps | volts and amps}? 2. What is the status of the {generator | inverter | battery | solar panel}? 3. What is the hab{itat} {power usage | volts | voltage | amps | volts and amps}? 4. What was the average hab{itat} {amps | volts | voltage} since <#> {AM | PM)? 5. When did the {generator | batteries} change status? 6. Tell {me I | everyone} when{ ever} the generator goes offline. 7. Tell {me | | everyone} when the hab{itat} {amps | volts | voltage} {exceeds | drops brelow} <#>. 8. {Send | Take | Record} {a} voice note {(for | to} } {at }. This research demonstrates the principles of design in the context of use, investigating requirements through experimental use of prototype systems in an analog setting, and use of MDRS as a research facility for designing and implementing new systems.

Clancey, William J.

Clear Speaking about Machines: People are Exploring Mars, Not Robots

The primary responsibility of all scientists is to ensure the integrity of their work. For cognitive and social scientists, this means first and foremost preserving clarity about what we know about people, and not allowing descriptions of technology to demean or obscure the reality of how people think, behave, and live. Without this clarity, engineering requirements analyses, tool design, and evaluations of people will be confused. A sharp, uncompromising understanding about the nature of people is essential if we are to design and fit new technologies that are appropriate and successful for NASA's mission operations.

Clancey, William J.

Are You Talking to Me? Dialogue Systems Supporting Mixed Teams of Humans and Robots

This position paper describes an approach to building spoken dialogue systems for environments containing multiple human speakers and hearers, and multiple robotic speakers and hearers. We address the issue, for robotic hearers, of whether the speech they hear is intended for them, or more likely to be intended for some other hearer. We will describe data collected during a series of experiments involving teams of multiple human and robots (and other software participants), and some preliminary results for distinguishing robot-directed speech from human-directed speech. The domain of these experiments is Mars-analogue planetary exploration. These Mars-analogue field studies involve two subjects in simulated planetary space suits doing geological exploration with the help of 1-2 robots, supporting software agents, a habitat communicator and links to a remote science team. The two subjects are performing a task (geological exploration) which requires them to speak with each other while also speaking with their assistants. The technique used here is to use a probabilistic context-free grammar language model in the speech recognizer that is trained on prior robot-directed speech. Intuitively, the recognizer will give higher confidence to an utterance if it is similar to utterances that have been directed to the robot in the past.

Dowding, John

Intelligence for Human-Assistant Planetary Surface Robots

The central premise in developing effective human-assistant planetary surface robots is that robotic intelligence is needed. The exact type, method, forms and/or quantity of intelligence is an open issue being explored on the ERA project, as well as others. In addition to field testing, theoretical research into this area can help provide answers on how to design future planetary robots. Many fundamental intelligence issues are discussed by Murphy [2], including (a) learning, (b) planning, (c) reasoning, (d) problem solving, (e) knowledge representation, and (f) computer vision (stereo tracking, gestures). The new "social interaction/emotional" form of intelligence that some consider critical to Human Robot Interaction (HRI) can also be addressed by human assistant planetary surface robots, as human operators feel more comfortable working with a robot when the robot is verbally (or even physically) interacting with them. Arkin [3] and Murphy are both proponents of the hybrid deliberative-reasoning/reactive-execution architecture as the best general architecture for fully realizing robot potential, and the robots discussed herein implement a design continuously progressing toward this hybrid philosophy. The remainder of this chapter will describe the challenges associated with robotic assistance to astronauts, our general research approach, the intelligence incorporated into our robots, and the results and lessons learned from over six years of testing human-assistant mobile robots in field settings relevant to planetary exploration. The chapter concludes with some key considerations for future work in this area.

Hirsh, Robert

Automating CapCom Using Mobile Agents and Robotic Assistants

We have developed and tested an advanced EVA communications and computing system to increase astronaut self-reliance and safety, reducing dependence on continuous monitoring and advising from mission control on Earth. This system, called Mobile Agents (MA), is voice controlled and provides information verbally to the astronauts through programs called personal agents. The system partly automates the role of CapCom in Apollo-including monitoring and managing EVA navigation, scheduling, equipment deployment, telemetry, health tracking, and scientific data collection. EVA data are stored automatically in a shared database in the habitat/vehicle and mirrored to a site accessible by a remote science team. The program has been developed iteratively in the context of use, including six years of ethnographic observation of field geology. Our approach is to develop automation that supports the human work practices, allowing people to do what they do well, and to work in ways they are most familiar. Field experiments in Utah have enabled empirically discovering requirements and testing alternative technologies and protocols. This paper reports on the 2004 system configuration, experiments, and results, in which an EVA robotic assistant (ERA) followed geologists approximately 150 m through a winding, narrow canyon. On voice command, the ERA took photographs and panoramas and was directed to move and wait in various locations to serve as a relay on the wireless network. The MA system is applicable to many space work situations that involve creating and navigating from maps (including configuring equipment for local topology), interacting with piloted and unpiloted rovers, adapting to environmental conditions, and remote team collaboration involving people and robots.

Clancey, William J.

Multi-Agent Modeling and Simulation Approach for Design and Analysis of MER Mission Operations

A space mission operations system is a complex network of human organizations, information and deep-space network systems and spacecraft hardware. As in other organizations, one of the problems in mission operations is managing the relationship of the mission information systems related to how people actually work (practices). Brahms, a multi-agent modeling and simulation tool, was used to model and simulate NASA's Mars Exploration Rover (MER) mission work practice. The objective was to investigate the value of work practice modeling for mission operations design. From spring 2002 until winter 2003, a Brahms modeler participated in mission systems design sessions and operations testing for the MER mission held at Jet Propulsion Laboratory (JPL). He observed how designers interacted with the Brahms tool. This paper discussed mission system designers' reactions to the simulation output during model validation and the presentation of generated work procedures. This project spurred JPL's interest in the Brahms model, but it was never included as part of the formal mission design process. We discuss why this occurred. Subsequently, we used the MER model to develop a future mission operations concept. Team members were reluctant to use the MER model, even though it appeared to be highly relevant to their effort. We describe some of the tool issues we encountered.

Seah, Chin

Expedition Memory: Towards Agent-based Web Services for Creating and Using Mars Exploration Data.

Explorers ranging over kilometers of rugged, sometimes "feature-less" terrain for over a year could be overwhelmed by tracking and sharing what they have done and learned. An automated system based on the existing Mobile Agents design [ I ] and Mars Exploration Rover experience [2], could serve as an "expedition memory" that would be indexed by voice as wel1 as a web interface, linking people, places, activities, records (voice notes, photographs, samples). and a descriptive scientific ontology. This database would be accessible during EVAs by astronauts, annotated by the remote science team, linked to EVA plans, and allow cross indexing between sites and expeditions. We consider the basic problem, our philosophical approach, technical methods, and uses of the expedition memory for facilitating long-term collaboration between Mars crews and Earth support teams. We emphasize that a "memory" does not mean a database per se, but an interactive service that combines different resources, and ultimately could be like a helpful librarian.

Clancey, William J.

The Mobile Agents 2005 Field Test at MDRS: Planning for Exploration

The Mars Society s Desert Research Station (MDRS) Rotation 38, April 3-17, 2005, was dedicated to field tests of NASA's Mobile Agents EVA communications system. MDRS provided an excellent, cost-effective venue for bringing together eighteen scientists and engineers from NASA Ames and Johnson Space Center, in an intensive two weeks of system integration and experiments. The Mobile Agents architecture and collaborative engineering methodology provides a flexible toolkit for configuring extravehicular activity (EVA) components, visualizing and formalizing EVA plans, and automating key supervisory functions.

Clancey, William J.