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Faezeh Rahbar

6 accepted papers

2023

Towards Efficient Gas Leak Detection in Built Environments: Data-Driven Plume Modeling for Gas Sensing Robots

ICRA 2023poster

The deployment of robots for Gas Source Localization (GSL) tasks in hazardous scenarios significantly reduces the risk to humans and animals. Gas sensing using mobile robots focuses primarily on simplified scenarios, due to the complexity of gas dispersion, with a current trend towards tackling more…

Cited by 9SourceScholar
2019

An Algorithm for Odor Source Localization based on Source Term Estimation

ICRA 2019poster

Finding sources of airborne chemicals with mobile sensing systems finds applications across the security, safety, domestic, medical, and environmental domains. In this paper, we present an algorithm based on source term estimation for odor source localization that is coupled with a navigation method…

Cited by 31SourceScholar
2018

Design and Performance Evaluation of an Infotaxis-Based Three-Dimensional Algorithm for Odor Source Localization

IROS 2018poster

In this paper we tackle the problem of finding the source of a gaseous leak with a robot in a three-dimensional (3-D) physical space. The proposed method extends the operational range of the probabilistic Infotaxis algorithm [1] into 3-D and makes multiple improvements in order to increase its perfo…

Cited by 17SourceScholar
2017

A 3-D bio-inspired odor source localization and its validation in realistic environmental conditions

IROS 2017poster

Finding the source of gaseous compounds released in the air with robots finds several applications in various critical situations, such as search and rescue. While the distribution of gas in the air is inherently a 3D phenomenon, most of the previous works have downgraded the problem into 2D search,…

Cited by 37SourceScholar
2017

Adaptive Lévy Taxis for odor source localization in realistic environmental conditions

ICRA 2017poster

Odor source localization with mobile robots has recently been subject to many research works, but remains a challenging task mainly due to the large number of environmental parameters that make it hard to describe gas concentration fields. We designed a new algorithm called Adaptive Lévy Taxis (ALT)…

Cited by 15SourceScholar