Abstract — Robotic odor source localization is a promising tool with numerous applications in safety, search and rescue, and environmental science. In this paper, we present an algorithm for odor source localization using multiple cooperating robots equipped with chemical sensors. Laplacian feedback is employed to maintain the robots in a formation, introducing spatial diversity that is used to better establish the position of the flock relative to the plume and its source. Robots primarily move upwind but use odor information to adjust their position and spacing so that they are centered on the plume and trace its structure. Real-world experiments were performed with an ethanol plume inside a wind tunnel, and used to both validate the algo...
Finding sources of airborne chemicals with mobile sensing systems finds applications in safety, secu...
Finding the best spatial formation of stationary gas sensors in detection of odor clues is the first...
This paper deals with the problem of odor source localization using multiple mobile robots. A distri...
Robotic odor source localization is a promising tool with numerous applications in safety, search an...
The large number of potential applications for robotic odor source localization has motivated the de...
We compare six different algorithms for localizing odor sources with mobile robots. Three algorithms...
This paper deals with the problem of odor source localization based on a multi-robot system. A coope...
This paper deals with the problem of odor source localization using multiple mobile robots. A cooper...
This paper presents an investigation of odor localization by groups of autonomous mobile robots. Fir...
This paper presents a method for odor plume tracking by a swarm of robots in realistic conditions. I...
The detection of an odor source location has been enhanced by using multiple plume-tracing mobile ro...
The detection of a dangerous emission source location has the potential to be enhanced by using plum...
This paper presents an analytical approach to the problem of odor plume finding by a network of swar...
Abstract — This paper presents a method for odor plume tracking by a swarm of robots in realistic co...
This paper addresses the collective odor source localization (OSL) problem in a time-varying airflow...
Finding sources of airborne chemicals with mobile sensing systems finds applications in safety, secu...
Finding the best spatial formation of stationary gas sensors in detection of odor clues is the first...
This paper deals with the problem of odor source localization using multiple mobile robots. A distri...
Robotic odor source localization is a promising tool with numerous applications in safety, search an...
The large number of potential applications for robotic odor source localization has motivated the de...
We compare six different algorithms for localizing odor sources with mobile robots. Three algorithms...
This paper deals with the problem of odor source localization based on a multi-robot system. A coope...
This paper deals with the problem of odor source localization using multiple mobile robots. A cooper...
This paper presents an investigation of odor localization by groups of autonomous mobile robots. Fir...
This paper presents a method for odor plume tracking by a swarm of robots in realistic conditions. I...
The detection of an odor source location has been enhanced by using multiple plume-tracing mobile ro...
The detection of a dangerous emission source location has the potential to be enhanced by using plum...
This paper presents an analytical approach to the problem of odor plume finding by a network of swar...
Abstract — This paper presents a method for odor plume tracking by a swarm of robots in realistic co...
This paper addresses the collective odor source localization (OSL) problem in a time-varying airflow...
Finding sources of airborne chemicals with mobile sensing systems finds applications in safety, secu...
Finding the best spatial formation of stationary gas sensors in detection of odor clues is the first...
This paper deals with the problem of odor source localization using multiple mobile robots. A distri...