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SOAR : science-based weld software for optimal automatic welding procedures

Fuerschbach, Phillip W.; Eisler, G.R.

The two primary uses for SOAR are: (1) Predictive--(i) Science based process models enable optimized automated weld procedures, (ii) virtual manufacturing enables the user to ask 'what if' and quickly find the answer, (iii) with SOAR, multiple welds do not need to be made in order to determine weld effects and required parameters; and (2) Investigative--(i) welding problem mysteries can be solved by gathering evidence, identifying problem suspects, and testing with SOAR; (ii) most SOAR models are universal and can be applied to many different weld processes; and (iii) understand your welding process.

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Cooperative control of vehicle swarms for acoustic target localization by energy flows

Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME

Dohner, Jeffrey L.; Eisler, G.R.; Driessen, B.J.; Hurtado, J.

A control algorithm has been developed and experimentally validated for guiding swarms of robotic vehicles to acoustic targets. This novel algorithm uses pressure measurements from a set of sensors, each attached to a vehicle of the swarm, to deduce energy flows from the environment, and to move in the direction of maximum reflected intensity while controlling constraints between vehicles. The algorithm was validated using a collective of eight hand-placed microphones in an open-space area with a 50-m separation between an emitter and scatterer. Copyright © 2004 by ASME.

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Robust Planning for Autonomous Navigation of Mobile Robots in Unstructured, Dynamic Environments: An LDRD Final Report

Eisler, G.R.

This report summarizes the analytical and experimental efforts for the Laboratory Directed Research and Development (LDRD) project entitled ''Robust Planning for Autonomous Navigation of Mobile Robots In Unstructured, Dynamic Environments (AutoNav)''. The project goal was to develop an algorithmic-driven, multi-spectral approach to point-to-point navigation characterized by: segmented on-board trajectory planning, self-contained operation without human support for mission duration, and the development of appropriate sensors and algorithms to navigate unattended. The project was partially successful in achieving gains in sensing, path planning, navigation, and guidance. One of three experimental platforms, the Minimalist Autonomous Testbed, used a repetitive sense-and-re-plan combination to demonstrate the majority of elements necessary for autonomous navigation. However, a critical goal for overall success in arbitrary terrain, that of developing a sensor that is able to distinguish true obstacles that need to be avoided as a function of vehicle scale, still needs substantial research to bring to fruition.

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6 Results
6 Results