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" Collaborative Execution of Exploration and Tracking using Move Value Estimation for Robot Teams (MVERT) "


Document Type : Latin Dissertation
Language of Document : English
Record Number : 149737
Doc. No : ET21529
Main Entry : Ashley W. Stroupe
Title Proper : Collaborative Execution of Exploration and Tracking using Move Value Estimation for Robot Teams (MVERT)
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : This work presents Move Value Estimation for Robot Teams (MVERT), an architecture specificallydesigned for selecting low-level actions for multi-agent teams. The design goal for MVERT is to producereasonable performance that takes advantage of a heterogeneous team while maintaining computationalefficiency. MVERT is fully distributed - each agent selects actions based on its knowledge and knowledgeprovided it by teammates. Each robot approximates the expected next-step teammate contributions and,given these predictions, each robot can select its action to maximize the team's progress. MVERTrepresents progress with mathematical valuejinctions that map state and robot task performance models toa numerical value representing mission utility.Many action selection approaches (optimal trajectory planning, for example) in large state-spaces may becomputationally prohibitive, particularly for online mission replanning. However, taking advantage of ateam's multi-agent nature to provide efficiency requires consideration of teammate contributions. Thus, inselecting an action with MVERT, each robot approximates the next-step contributions of teammates byapplying their sensing models, task capabilities, and currenttested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL44701.pdf
Title and statement of responsibility and : Collaborative Execution of Exploration and Tracking using Move Value Estimation for Robot Teams (MVERT) [Thesis]
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TL44701.pdf
TL44701.pdf
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