Publications

Abstract not provided.

As Sandia National Laboratories serves its mission to provide support for the security-related interests of the United States, it is faced with considering the behavioral responses that drive problems, mitigate interventions, or lead to unintended consequences. The effort described here expands earlier works in using healthcare simulation to develop behavior-aware decision support systems. This report focuses on using qualitative choice techniques and enhancing two analysis models developed in a sister project.

This is the final report for a LDRD effort to address human behavior in decision support systems. One sister LDRD effort reports the extension of this work to include actual human choices and additional simulation analyses. Another provides the background for this effort and the programmatic directions for future work. This specific effort considered the feasibility of five aspects of model development required for analysis viability. To avoid the use of classified information, healthcare decisions and the system embedding them became the illustrative example for assessment.

Abstract not provided.

The need to anticipate the consequences of policy decisions becomes ever more important as the magnitude of the potential consequences grows. The multiplicity of connections between the components of society and the economy makes intuitive assessments extremely unreliable. Agent-based modeling has the potential to be a powerful tool in modeling policy impacts. The direct mapping between agents and elements of society and the economy simplify the mapping of real world functions into the world of computation assessment. Our modeling initiative is motivated by the desire to facilitate informed public debate on alternative policies for how we, as a nation, provide healthcare to our population. We explore the implications of this motivation on the design and implementation of a model. We discuss the choice of an agent-based modeling approach and contrast it to micro-simulation and systems dynamics approaches.

Abstract not provided.

Increasingly constrained budgets in the defense community, both DoD and DOE, have created a need to emphasize affordability in the development of future weapons systems and components. Increased use of commercially compatible components will play an important role, but there will always remain a need for specialized production, especially at the system level. We will present on-going work at Sandia National Laboratories (referred to from here as Sandia) aimed at insuring the affordability of low-volume, defence-specific systems.

The work in this program covered four primary areas: solid modeling, path planning, modular fixturing, and stability analysis. This report contains highlights of results from the program, references to published reports, and, in an appendix, a currently unpublished report which has been accepted for journal publication, but has yet to appear.

Archimedes is a prototype mechanical assembly system which generates and executes robot assembly programs from a CAD model input. The system seeks to increase flexibility in robotic mechanical assembly applications by automating the programming task. Input is a solid model of the finished assembly, augmented by additional design information such as weld specifications. Parts relationships and geometric constraints are deduced from the solid model. A rule-based planner generates a ``generic`` assembly plan that satisfies the geometric constraints, as well as other constraints embodied in the rules. A plan compiler then converts the generic plan into code specific to an application environment. Other outputs include fixture designs, workcell layout information, object-recognition (vision) routines, grasp plans, and executable code for controlling the robot and workcell accessories. Lessons from operating and demonstrating the system are presented, with a particular emphasis on the implications for future systems. 12 refs.

Archimedes is a prototype mechanical assembly system which generates and executes robot assembly programs from a CAD model input. The system addresses the unrealized potential for flexibility in robotic mechanical assembly applications by automating the programming task. Input is a solid model of the finished assembly. Parts relationships and geometric constraints are deduced from the solid model. A rule-based planner generates a generic'' assembly plan that satisfies the geometric constraints, as well as other constraints embodied in the rules. A retargetable plan compiler converts the generic plan into code specific to an application environment. Execution of the compiled plan in a workcell containing an Adept Two robot, a vision system, and other parts handling equipment will be shown on videotape.