ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
- Artemiadis, Panagiotis
- 1 Arizona State University
- 1 Berman, Spring M
- 1 Marvi, Hamid
- 1 Mignolet, Marc
- 1 Ramachandran, Ragesh Kumar
- 1 Robinson, Michael
- 1 Public
- Swarm robotics
- Mapping
- 1 Applied mathematics
- 1 Engineering
- 1 GPS denied
- 1 Network theory
- 1 Robotics
- 1 Scalar field estimation
- more
- 1 Topological data analysis
- Dwarf Galaxies as Laboratories of Protogalaxy Physics: Canonical Star Formation Laws at Low Metallicity
- Evolutionary Genetics of CORL Proteins
- Social Skills and Executive Functioning in Children with PCDH-19
- Deep Domain Fusion for Adaptive Image Classification
- Software Defined Pulse-Doppler Radar for Over-The-Air Applications: The Joint Radar-Communications Experiment
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 …
- Contributors
- Ramachandran, Ragesh Kumar, Berman, Spring M, Mignolet, Marc, et al.
- Created Date
- 2018