SPECIAL MODELS, ALGORITHMS AND SOFTWARE FOR PROACTIVE GROUP BEHAVIOR CONTROL OF ROBOTS
The paper describes the proactive control of robots group behavior using Behavior-Based System models, where the intellect is formed by a physical entities behavior. The observed complex is an array of distributed agents functioning in real time under disturbances. John Boyd’s OODA loop model is used to describe the control system work cycle of such network object. The input data of the control task are a planning horizon, a group action scenario, an array of agents and their possible elementary operations, a set of scenarios using restrictions and a quality indicator of the control problem solution. The output data is the distribution plan of agents in space and time to realize the scenario under restrictions. The developed technology predicts the environmental disturbances. The complex predictive modeling methodology for a self-organized robots group control is used with logical-dynamic models. One of the key advantages of developed combined models, methods, algorithms and software is the possibility to coordinate analytical and simulation control models of complex dynamic objects and their logical-algebraic analogs and models based on intelligent information technology. This coordination is on the conceptual, model-algorithmic, information and software detailing levels. The special language for modeling, planning, proactive monitoring and control task description is also developed. This language can be used for dialog interaction, calculation planning and data mining too. The proposed method main advantage is the non-isolated, but integrated solving of robotics configuration (reconfiguration) modeling, planning and management with the structural dynamics proactive control common problem solution.