A Coordinated Search Strategy for Solitary Robots

Abstract

The problem of coordination without a priori information about the environment is important in robotics. Applications vary from formation control to search and rescue. This paper considers the problem of search by a group of solitary robots: self-interested robots without a priori knowledge about each other, and with restricted communication capacity. When the capacity of robots to communicate is limited, they may obliviously search in overlapping regions (i.e. be subject to interference). Interference hinders robot progress, and strategies have been proposed in the literature to mitigate interference [1], [2]. Interaction of solitary robots has attracted much interest in robotics, but the problem of mitigating interference when time for search is limited remains an important area of research. We propose a coordination strategy based on the method of cellular decomposition [3] where we employ the concept of soft obstacles: a robot considers cells assigned to other robots as obstacles. The performance of the proposed strategy is demonstrated by means of simulation experiments. Simulations indicate the utility of the strategy in situations where a known upper bound on the search time precludes search of the entire environment.

A Soft Obstacle Search Strategy for Various Solitary Robots in an Unknown Environment

“…The proposed strategy provides sustainable performance when the time for search is limited (insufficient to cover the entire search area) and known. A shorter version of this work can be found in Masakuna et al (2019a) and an earlier preprint version of this work can be found in Masakuna et al (2019b). Here we extend the theoretical and practical investigation of the proposed coordination strategy (Masakuna, 2020).…”