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Exploration, Mapping and Scalar Field Estimation using a Swarm of Resource-Constrained Robots

Abstract Robotic swarms can potentially perform complicated tasks such as exploration and mapping at large space and time scales in a parallel and robust fashion. This thesis presents strategies for mapping environmental features of interest – specifically obstacles, collision-free paths, generating a metric map and estimating scalar density fields– in an unknown domain using data obtained by a swarm of resource-constrained robots. First, an approach was developed for mapping a single obstacle using a swarm of point-mass robots with both directed and random motion. The swarm population dynamics are modeled by a set of advection-diffusion-reaction partial differential equations (PDEs) in which a spatially-dependent indicator function marks the presen... (more)
Created Date 2018
Contributor Ramachandran, Ragesh Kumar (Author) / Berman, Spring M (Advisor) / Mignolet, Marc (Committee member) / Artemiadis, Panagiotis (Committee member) / Marvi, Hamid (Committee member) / Robinson, Michael (Committee member) / Arizona State University (Publisher)
Subject Robotics / Engineering / Applied mathematics / GPS denied / Mapping / Network theory / Scalar field estimation / Swarm robotics / Topological data analysis
Type Doctoral Dissertation
Extent 226 pages
Language English
Note Doctoral Dissertation Mechanical Engineering 2018
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis