Bio-inspired guiding strategy for robot seeking intermittent information source

Searching and tracking an information source in sporadic cue environment is a difficult task for mobile robot. The targets usually emit some cues like chemical substance, light and heat, which are dispersed and distributed in the region. Such local cues pointing towards the location of the target are usually mixed with a flowing medium. As a result, they are torn into random and disconnected patches. Thus, the cues detected by robot is intermittent and scarce, which made chemotaxis and anemotaxis become difficult and unfeasible. In this paper, inspired by biology olfactory, we propose a guiding strategy for robot to seek out the intermittent information source by combining a random walk based cue encountering progress and a expected source information gain maximized progress. Specifically, we propose a Lévy-Infotaxis algorithm by combining Lévy-taxis with Infotaxis. The Levy-taxis can efficiently get the first hit for one information cue. Then the Infotaxis algorithm is triggered and navigates the mobile robot to the information source. The proposed algorithm can help to avoid the starting assumption for Infotaxis algorithm and improve the autonomy of mobile robot in unknown environment. Simulation results show the effectiveness of the proposed strategy for mobile robot moving to the target with intermittent and sparse information. The recorded trajectories are also analyzed with regard to success rates, mean search time and path length. It demonstrates that the proposed strategy yields optimized trajectories.