Article Preview
TopSince the early 1990s many researchers have explored this area of research with mobile agent(s) that can find the source of chemical release. Their main focus was on developing algorithm used to guide the heading of the robot to chemical cues. Such an early work dates back to 1991 when (Rozas, Morales, & Vega, 1991) used a single robot with six different types of semiconductor gas sensors and a fan for active sniffing. It simply followed the direction of higher concentration. In continuous endeavor, scientific community explored nature inspired animal behaviors such as silkworm moth and lobsters (Basil & Atema, 1994; H Ishida et al., 1996) and termed these as anemotaxis algorithms. A variety of bio-inspired algorithms have been developed to mimic the organisms like E. Coli to trace the chemical plume at macroscopic scale (Lytridis, Kadar, & Virk, 2006; Marques, Nunes, & de Almeida, 2002; Russell, Bab-Hadiashar, Shepherd, & Wallace, 2003). These chemotaxis algorithms only require information from chemical cues unlike anemotaxis which requires additional information of wind direction and velocity. Anemotaxis is much preferred for outdoor environment because it uses both wind information (direction/strength) and plume concentration to achieve the target of odor/gas source localization (Edwards, Rutkowski, Quinn, & Willis, 2005; Li, Farrell, Pang, & Arrieta, 2006). On the other hand, indoor conditions lack possibility of natural advection and for such scenarios chemotaxis is also suitable. However, navigation in a chemical diffusion is still far from well understood.