Mobile robot gas source localization via top-down visual attention mechanism and shape analysis

A novel mobile robot based gas source localization method in which the top-down visual attention mechanism (TDVAM) is combined with shape analysis is proposed. At each location, three different images which cover the scene in front of the robot are captured via changing the horizontal angle of an onboard pan/tilt camera. In each image, three salient regions are computed using TDVAM model, and maximal one plausible gas source from three salient regions is identified by using the shape analysis. The positions of recognized plausible gas sources are determined with a laser range scanner. The robot is navigated to the plausible gas sources one by one and gas concentration information is used to judge if the plausible sources are real ones. Experimental results in a complex indoor airflow environment in which valves are used to simulate gas sources demonstrate the feasibility and high efficiency of the proposed gas source localization approach.

I. Introduction

In natural world, many animals such as drosophila, moth, lobster, etc. [[1], [2]], use olfaction and vision cues to find same species, avoid predators and search for food. Those successful examples have encouraged the development of mobile robots for gas so urces localization. Existing methods of gas source localization can be categorized along two lines. One is olfaction-based methods, which mainly use olfaction to search for gas sources without visual information. The other is vision-bas ed methods, which take the visual information as an assistant of olfaction to localize gas sources.