We introduce a novel bio-inspired odor source localization algorithm (surge- cast) for environments with a main wind flow and compare it to two well-known algorithms. With all three algorithms, systematic experiments with real robots are carried out in a wind tunnel under laminar flow conditions. The algorithms are compared in terms of distance overhead when tracking the plume up to the source, but a variety of other experimental results and some theoretical considerations are provided as well. We conclude that the surge-cast algorithm yields significantly better performance than the casting algorithm, and slightly better performance than the surge-spiral algorithm
Odor plume tracing is a challenging robotics application, made difficult by the combination of the p...
Abstract — Robotic odor source localization is a promising tool with numerous applications in safety...
Finding sources of airborne chemicals with mobile sensing systems finds applications across safety, ...
We compare three bio-inspired odor source localization algorithm (casting, surge-spiral and surge-ca...
We compare two well-known algorithms for locating odor sources in environments with a main wind flow...
Abstract We compare two well-known algorithms for lo-cating odor sources in environments with a mai...
Finding the source of gaseous compounds released in the air with robots finds several applications i...
We compare six different algorithms for localizing odor sources with mobile robots. Three algorithms...
Robotic odor source localization is a promising tool with numerous applications in safety, search an...
Gas source localization is likely the most direct application of a mobile robot endowed with gas sen...
The large number of potential applications for robotic odor source localization has motivated the de...
This paper presents an analytical approach to the problem of odor plume finding by a network of swar...
In this paper we tackle the problem of finding the source of a gaseous leak with a robot in a three-...
This paper presents a method for odor plume tracking by a swarm of robots in realistic conditions. I...
AbstractThe methodology of tracing odor plume via a mobile robot is considered. In this research, tw...
Odor plume tracing is a challenging robotics application, made difficult by the combination of the p...
Abstract — Robotic odor source localization is a promising tool with numerous applications in safety...
Finding sources of airborne chemicals with mobile sensing systems finds applications across safety, ...
We compare three bio-inspired odor source localization algorithm (casting, surge-spiral and surge-ca...
We compare two well-known algorithms for locating odor sources in environments with a main wind flow...
Abstract We compare two well-known algorithms for lo-cating odor sources in environments with a mai...
Finding the source of gaseous compounds released in the air with robots finds several applications i...
We compare six different algorithms for localizing odor sources with mobile robots. Three algorithms...
Robotic odor source localization is a promising tool with numerous applications in safety, search an...
Gas source localization is likely the most direct application of a mobile robot endowed with gas sen...
The large number of potential applications for robotic odor source localization has motivated the de...
This paper presents an analytical approach to the problem of odor plume finding by a network of swar...
In this paper we tackle the problem of finding the source of a gaseous leak with a robot in a three-...
This paper presents a method for odor plume tracking by a swarm of robots in realistic conditions. I...
AbstractThe methodology of tracing odor plume via a mobile robot is considered. In this research, tw...
Odor plume tracing is a challenging robotics application, made difficult by the combination of the p...
Abstract — Robotic odor source localization is a promising tool with numerous applications in safety...
Finding sources of airborne chemicals with mobile sensing systems finds applications across safety, ...