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

Abstract

Abstract The problem of coordination without a priori informationabout the environment is important in robotics. Applications vary fromformation control to search and rescue. This paper considers the problemof search by a group of solitary robots: self-interested robots without apriori knowledge about each other, and with restricted communicationcapacity. When the capacity of robots to communicate is limited, theymay obliviously search in overlapping regions (i.e. be subject to inter-ference). Interference hinders robot progress, and strategies have beenproposed in the literature to mitigate interference (Wellman et al., 2011;Hourani et al., 2013). Interaction of solitary robots has attracted muchinterest in robotics, but the problem of mitigating interference when timefor search is limited remains an important area of research. We proposea coordination strategy based on the method of cellular decomposition(Choset, 2001) where we employ the concept of soft obstacles: a robotconsiders cells assigned to other robots as obstacles. The performance ofthe proposed strategy is demonstrated by means of simulation experi-ments in both actual and simulated environments. Simulations indicatethe utility of the strategy in situations where a known upper bound onthe search time precludes search of the entire environment.

Research topics

  • Optimization and Search Problems
  • Modular Robots and Swarm Intelligence
  • Cellular Automata and Applications

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DOI: 10.21203/rs.3.rs-3207161/v1

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