Publications

Abstract not provided.

In this paper an optimization-based method of drift prevention is presented for learning control of underdetermined linear and weakly nonlinear time-varying dynamic systems. By defining a fictitious cost function and the associated model-based sub-optimality conditions, a new set of equations results, whose solution is unique, thus preventing large drifts from the initial input. Moreover, in the limiting case where the modeling error approaches zero, the input that the proposed method converges to is the unique feasible (zero error) input that minimizes the fictitious cost function, in the linear case, and locally minimizes it in the (weakly) nonlinear case. Otherwise, under mild restrictions on the modeling error, the method converges to a feasible sub-optimal input.

The Intelligent Systems and Robotics Center (ISRC) at Sandia National Laboratories (SNL) is developing technologies for glovebox size reduction in the DOE nuclear complex. A study was performed for Kaiser-Hill (KH) at the Rocky Flats Environmental Technology Site (RFETS) on the available technologies for size reducing the glovebox lines that require size reduction in place. Currently, the baseline approach to these glovebox lines is manual operations using conventional mechanical cutting methods. The study has been completed and resulted in a concept of the robotic system for in-situ size reduction. The concept makes use of commercially available robots that are used in the automotive industry. The commercially available industrial robots provide high reliability and availability that are required for environmental remediation in the DOE complex. Additionally, the costs of commercial robots are about one-fourth that of the custom made robots for environmental remediation. The reason for the lower costs and the higher reliability is that there are thousands of commercial robots made annually, whereas there are only a few custom robots made for environmental remediation every year. This paper will describe the engineering analysis approach used in the design of the robotic system for glovebox size reduction.

Many hazardous material handling needs exist in remote unstructured environments. Currently these operations are accomplished using personnel in direct contact with the hazards. A safe and cost effective alternative to this approach is the use of intelligent robotic systems for safe handling, packaging, transport, and even excavation of hazardous materials. The Intelligent Systems and Robotics Center of Sandia National Laboratories has developed and deployed robotic technologies for use in hazardous environments, three of which have been deployed in DOE production facilities for handling of special nuclear materials. Other systems are currently under development for packaging special nuclear materials. This paper presents an overview of the research activities, including five delivered systems, at %ndia National Laboratories on the use of robotics in hazardous environments.

This work considers the problem of causing multiple (100's) autonomous mobile robots to converge to a target and provides a "follow-the- leader" approach to the problem. Each robot has only a limited-range sensor for sensing the target and also larger but also limited-range robot-to-robot communication capability. Because of the small amount of information available to the robots, a practical approach to improve convergence to the target is to have a robot follow the robot with the best quality of information. Specifically, each robot emits a signal that informs in-range robots what its status is. A robot has a status value of 0 if it is itself in range of the target. A robot has a status of 1 if it is not in range of the target but is is communication range of a robot that is in range of the target. A robot has a status of 2 if it is not in range of the target but is within range of another robot that has status 1, and so on. Of all the mobile robots that any given robot is in range of, it follows the one with the best status. The emergent behavior is the ant-like trails of robots following each other toward the target. If the robot is not in range of another robot that is either in range of the target or following another robot, the robot will assign -1 to its quality-of-information, and will execute an exhaustive search. The exhuastive search will continue until it encounters either the target or another robot with a nonnegative quality-of-information. The quality of information approach was extended to the case where each robot only has two-bit signals informing it of distance to in-range robots.

This work considers the problem of maximum utilization of a set of mobile robots with limited sensor-range capabilities and limited travel distances. The robots are initially in random positions. A set of robots properly guards or covers a region if every point within the region is within the effective sensor range of at least one vehicle. We wish to move the vehicles into surveillance positions so as to guard or cover a region, while minimizing the maximum distance traveled by any vehicle. This problem can be formulated as an assignment problem, in which we must optimally decide which robot to assign to which slot of a desired matrix of grid points. The cost function is the maximum distance traveled by any robot. Assignment problems can be solved very efficiently. Solution times for one hundred robots took only seconds on a Silicon Graphics Crimson workstation. The initial positions of all the robots can be sampled by a central base station and their newly assigned positions communicated back to the robots. Alternatively, the robots can establish their own coordinate system with the origin fixed at one of the robots and orientation determined by the compass bearing of another robot relative to this robot This paper presents example solutions to the multiple-target-multiple-agent scenario using a matching algorithm. Two separate cases with one hundred agents in each were analyzed using this method. We have found these mobile robot problems to be a very interesting application of network optimization methods, and we expect this to be a fruitful area for future research.

A system for automatic tool path generation was developed at Sandia National Laboratories for finish machining operations. The system consists of a commercially available 5-axis milling machine controlled by Sandia developed software. This system was used to remove overspray on cast turbine blades. A laser-based, structured-light sensor, mounted on a tool holder, is used to collect 3D data points around the surface of the turbine blade. Using the digitized model of the blade, a tool path is generated which will drive a 0.375 inch grinding pin around the tip of the blade. A fuzzified digital filter was developed to properly eliminate false sensor readings caused by burrs, holes and overspray. The digital filter was found to successfully generate the correct tool path for a blade with intentionally scanned holes and defects. The fuzzified filter improved the computation efficiency by a factor of 25. For application to general parts, an adaptive scanning algorithm was developed and presented with simulation and experimental results. A right pyramid and an ellipsoid were scanned successfully with the adaptive algorithm in simulation studies. In actual experiments, a nose cone and a turbine blade were successfully scanned. A complex shaped turbine blade was successfully scanned and finished machined using these algorithms.

A system for automatic tool path generation was developed at Sandia National Laboratories for finish machining operations. The system consists of a commercially available 5-axis milling machine controlled by Sandia developed software. This system was used to remove overspray on cast turbine blades. A laser-based, structured-light sensor, mounted on a tool holder, is used to collect 3D data points around the surface of the turbine blade. Using the digitized model of the blade, a tool path is generated which will drive a 0.375″ CBN grinding pin around the tip of the blade. A fuzzified digital filter was developed to properly eliminate false sensor readings caused by burrs, holes and overspray. The digital filter was found to successfully generate the correct tool path for a blade with intentionally scanned holes and defects. The fuzzified filter improved the computation efficiency by a factor of 25. For application to general parts, an adaptive scanning algorithm was developed and presented with simulation results. A right pyramid and an ellipsoid were scanned successfully with the adaptive algorithm.

A team has developed an improved resolution ultrasound system for low cost diagnostics. This paper describes the development of an ultrasound based imaging system capable of generating 3D images showing surface and subsurface tissue and bone structures. We include results of a comparative study between images obtained from X-Ray Computed Tomography (CT) and ultrasound. We found that the quality of ultrasound images compares favorably with those from CT. Volumetric and surface data extracted from these images were within 7% of the range between ultrasound and CT scans. We also include images of porcine abdominal scans from two different sets of animal trials.

A dynamic simulator of the TOPAZ II reactor system has been developed for the Nuclear Electric Propulsion Space Test Program. The simulator is a self-contained IBM-PC compatible based system that executes at a speed faster than real-time. The simulator combines first-principle modeling and empirical correlations in its algorithm to attain the modeling accuracy and computational through-put that are required for real-time execution. The overall execution time of the simulator for each time step is 15 ms when no data is written to the disk, and 18 ms when nine double precision data points are written to the disk once in every time step. The simulation program has been tested and it is able to handle a step decrease of $8 worth of reactivity. It also provides simulation of fuel, emitter, collector, stainless steel, and ZrH moderator failures. Presented in this paper are the models used in the calculations, a sample simulation session, and a discussion of the performance and limitations of the simulator. The simulator has been found to provide realistic real-time dynamic response of the TOPAZ II reactor system under both normal and causality conditions.

A dynamic simulator of the TOPAZ II reactor system has been developed for the Nuclear Electric Propulsion Space Test Program. The simulator combines first-principle modeling and empirical correlations in its algorithm to attain the modeling accuracy and computational through-put that are required for real-time execution. The overall execution time of the simulator for each time step is 15 ms when no data is written to the disk, and 18 ms when nine double precision data points are written to the disk once in every time step. The simulation program has been tested and it is able to handle a step decrease of $8 worth of reactivity. It also provides simulations of fuel, emitter, collector, stainless steel, and ZrH moderator failures. Presented in this paper are the models used in the calculations, a sample simulation session, and a discussion of the performance and limitations of the simulator. The simulator has been found to provide realistic real-time dynamic response of the TOPAZ II reactor system under both normal and casualty conditions.