Main Article Content
This paper considers a group of autonomous robots performing collective tasks in an environment. The environment is antagonistic and has objective and subjective influence factors: uncontrolled natural conditions that hamper collective mission fulfillment (e.g., night-time, fog, or rain) and a specially organized counteraction (e.g., the defense systems of a potential target under attack). The unpredictability of possible situations in the environment complicates collective tasks for robots. Therefore, probabilistic or fuzzy variables are used to describe the attributes of influence factors. The robots execute different roles within the group, operating independently to fulfill a collective mission. The robots are equipped with observation sensors and motion detectors. The collective behavior of robots is designed within the Internet-of-Things paradigm. The functions and resources of robots are represented as external services. They are automatically used by other robots via online requests when needed. The cooperative strategies of robots are implemented for resolving problem situations caused by the environment. Such an approach realizes the principle of collectivism. The efficiency of the suggested approach is studied using an illustrative example: active robots moving to targets secured by a defense system.