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DTSTART:20240310T030000
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DTSTAMP:20241127T005640Z
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DTSTART;TZID=America/Denver:20240918T180000
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DESCRIPTION:Presentation: Relative Localization in Multi-Robot and Wireless
  Networked Systems\n\nAbstract: Dr Parasuraman will present his recent wor
 k in the research of relative localization in mobile robots and sensors\, 
 where the robots collaborate their measurements and apply Bayesian samplin
 g and graph-theoretic approaches to perform relative localization and expl
 oration in a distributed manner. The novelty of these approaches lies in t
 heir ubiquity of relying only on minimal sensor data\, making them applica
 ble to SWAP-constrained devices like IoT nodes and swarm robots. Dr Parasu
 raman will also present some extensions of these works to an autonomous mu
 lti-robot exploration domain by presenting a distributed earning technique
  using ad-hoc map merging and significantly reducing communication and com
 putation costs.\n\nSpeaker(s): Ramviyas Parasuraman\, \n\nVirtual: https:/
 /events.vtools.ieee.org/m/433650
LOCATION:Virtual: https://events.vtools.ieee.org/m/433650
ORGANIZER:gowansj@ieee.org
SEQUENCE:3
SUMMARY:CIR & CIS: Relative Localization in Multi-Robot and Wireless Networ
 ked Systems
URL;VALUE=URI:https://events.vtools.ieee.org/m/433650
X-ALT-DESC:Description: <br /><div class="presentation-title"><strong>Prese
 ntation: Relative Localization in Multi-Robot and Wireless Networked Syste
 ms</strong></div>\n<div class="presentation-title">&nbsp\;</div>\n<div cla
 ss="abstract"><strong>Abstract:</strong> Dr Parasuraman will present his r
 ecent work in the research of relative localization in mobile robots and s
 ensors\, where the robots collaborate their measurements and apply Bayesia
 n sampling and graph-theoretic approaches to perform relative localization
  and exploration in a distributed manner. The novelty of these approaches 
 lies in their ubiquity of relying only on minimal sensor data\, making the
 m applicable to SWAP-constrained devices like IoT nodes and swarm robots. 
 Dr Parasuraman will also present some extensions of these works to an auto
 nomous multi-robot exploration domain by presenting a distributed earning 
 technique using ad-hoc map merging and significantly reducing communicatio
 n and computation costs.</div>
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