Ground controlled robotic assembly operations for Space Station Freedom

A number of dextrous robotic systems and associated positioning and transportation devices are available on Space Station Freedom (SSF) to perform assembly tasks that would otherwise need to be performed by extravehicular activity (EVA) crewmembers. The currently planned operating mode for these robotic systems during the assembly phase is teleoperation by intravehicular activity (IVA) crewmembers. While this operating mode is less hazardous and expensive than manned EVA operations, and has insignificant control loop time delays, the amount of IVA time available to support telerobotic operations is much less than the anticipated requirements. Some alternative is needed to allow the robotic systems to perform useful tasks without exhausting the available IVA resources; ground control is one such alternative. The issues associated with ground control of SSF robotic systems to alleviate onboard crew time availability constraints are investigated. Key technical issues include the effect of communication time delays, the need for safe, reliable execution of remote operations, and required modifications to the SSF ground and flight system architecture. Time delay compensation techniques such as predictive displays and world model-based force reflection are addressed and collision detection and avoidance strategies to ensure the safety of the on-orbit crew, Orbiter, and SSF are described. Although more time consuming and difficult than IVA controlled teleoperations or manned EVA, ground controlled telerobotic operations offer significant benefits during the SSF assembly phase, and should be considered in assembly planning activities

Semi-Structured Decision Processes: A Conceptual Framework for Understanding Human-Automation Decision Systems

The purpose of this work is to improve understanding of existing and proposed decision systems, ideally to improve the design of future systems. A "decision system" is defined as a collection of information-processing components -- often involving humans and automation (e.g., computers) -- that interact towards a common set of objectives. Since a key issue in the design of decision systems is the division of work between humans and machines (a task known as "function allocation"), this report is primarily intended to help designers incorporate automation more appropriately within these systems. This report does not provide a design methodology, but introduces a way to qualitatively analyze potential designs early in the system design process. A novel analytical framework is presented, based on the concept of "semi-Structured" decision processes. It is believed that many decisions involve both well-defined "Structured" parts (e.g., formal procedures, traditional algorithms) and ill-defined "Unstructured" parts (e.g., intuition, judgement, neural networks) that interact in a known manner. While Structured processes are often desired because they fully prescribe how a future decision (during "operation") will be made, they are limited by what is explicitly understood prior to operation. A system designer who incorporates Unstructured processes into a decision system understands which parts are not understood sufficiently, and relinquishes control by deferring decision-making from design to operation. Among other things, this design choice tends to add flexibility and robustness. The value of the semi-Structured framework is that it forces people to consider system design concepts as operational decision processes in which both well-defined and ill-defined components are made explicit. This may provide more insight into decision systems, and improve understanding of the implications of design choices. The first part of this report defines the semi-Structured process and introduces a diagrammatic notation for decision process models. In the second part, the semi-Structured framework is used to understand and explain highly evolved decision system designs (these are assumed to be representative of "good" designs) whose components include feedback controllers, alerts, decision aids, and displays. Lastly, the semi-Structured framework is applied to a decision system design for a mobile robot.Charles Stark Draper Laboratory, Inc., under IR&D effort 101

Fourth Annual Workshop on Space Operations Applications and Research (SOAR 90)

The papers from the symposium are presented. Emphasis is placed on human factors engineering and space environment interactions. The technical areas covered in the human factors section include: satellite monitoring and control, man-computer interfaces, expert systems, AI/robotics interfaces, crew system dynamics, and display devices. The space environment interactions section presents the following topics: space plasma interaction, spacecraft contamination, space debris, and atomic oxygen interaction with materials. Some of the above topics are discussed in relation to the space station and space shuttle

Autonomous, Context-Sensitive, Task Management Systems and Decision Support Tools I: Human-Autonomy Teaming Fundamentals and State of the Art

Recent advances in artificial intelligence, machine learning, data mining and extraction, and especially in sensor technology have resulted in the availability of a vast amount of digital data and information and the development of advanced automated reasoners. This creates the opportunity for the development of a robust dynamic task manager and decision support tool that is context sensitive and integrates information from a wide array of on-board and off aircraft sourcesa tool that monitors systems and the overall flight situation, anticipates information needs, prioritizes tasks appropriately, keeps pilots well informed, and is nimble and able to adapt to changing circumstances. This is the first of two companion reports exploring issues associated with autonomous, context-sensitive, task management and decision support tools. In the first report, we explore fundamental issues associated with the development of an integrated, dynamic, flight information and automation management system. We discuss human factors issues pertaining to information automation and review the current state of the art of pilot information management and decision support tools. We also explore how effective human-human team behavior and expectations could be extended to teams involving humans and automation or autonomous systems

Space station automation and robotics study. Operator-systems interface

This is the final report of a Space Station Automation and Robotics Planning Study, which was a joint project of the Boeing Aerospace Company, Boeing Commercial Airplane Company, and Boeing Computer Services Company. The study is in support of the Advanced Technology Advisory Committee established by NASA in accordance with a mandate by the U.S. Congress. Boeing support complements that provided to the NASA Contractor study team by four aerospace contractors, the Stanford Research Institute (SRI), and the California Space Institute. This study identifies automation and robotics (A&R) technologies that can be advanced by requirements levied by the Space Station Program. The methodology used in the study is to establish functional requirements for the operator system interface (OSI), establish the technologies needed to meet these requirements, and to forecast the availability of these technologies. The OSI would perform path planning, tracking and control, object recognition, fault detection and correction, and plan modifications in connection with extravehicular (EV) robot operations