Ant robotic swarm for visualizing invisible hazardous substances
| dc.contributor.author | Oyekan, John O. | en_GB |
| dc.contributor.author | Hu, Huosheng | en_GB |
| dc.date.accessioned | 2013-08-12T08:17:17Z | |
| dc.date.available | 2013-08-12T08:17:17Z | |
| dc.date.issued | 2013 | |
| dc.identifier.citation | Oyekan, J. & HU, H. (2013) 'Ant Robotic Swarm for Visualizing Invisible Hazardous Substances', Robotics, 2(1), pp.1-18 | en_GB |
| dc.identifier.issn | 2218-6581 | |
| dc.identifier.doi | 10.3390/robotics2010001 | |
| dc.identifier.uri | http://hdl.handle.net/10547/297902 | |
| dc.description.abstract | Inspired by the simplicity of how nature solves its problems, this paper presents a novel approach that would enable a swarm of ant robotic agents (robots with limited sensing, communication, computational and memory resources) form a visual representation of distributed hazardous substances within an environment dominated by diffusion processes using a decentralized approach. Such a visual representation could be very useful in enabling a quicker evacuation of a city’s population affected by such hazardous substances. This is especially true if the ratio of emergency workers to the population number is very small. | |
| dc.language.iso | en | en |
| dc.relation.url | http://www.mdpi.com/2218-6581/2/1/1/ | en_GB |
| dc.rights | Archived with thanks to Robotics | en_GB |
| dc.subject | bio-inspiration | en_GB |
| dc.subject | ant agents | en_GB |
| dc.subject | optimal coverage | en_GB |
| dc.subject | pollution monitoring | en_GB |
| dc.subject | bacterial foraging | en_GB |
| dc.title | Ant robotic swarm for visualizing invisible hazardous substances | en |
| dc.type | Article | en |
| dc.identifier.journal | Robotics | en_GB |
| html.description.abstract | Inspired by the simplicity of how nature solves its problems, this paper presents a novel approach that would enable a swarm of ant robotic agents (robots with limited sensing, communication, computational and memory resources) form a visual representation of distributed hazardous substances within an environment dominated by diffusion processes using a decentralized approach. Such a visual representation could be very useful in enabling a quicker evacuation of a city’s population affected by such hazardous substances. This is especially true if the ratio of emergency workers to the population number is very small. |