Automatic approach to stabilization and control for multi robot teams by multilayer network operator

Askhat Diveev,Elizaveta Shmalko,E.V Nikulchev,E.I Veremey

doi:10.1051/itmconf/20160602004

Askhat Diveev, Elizaveta Shmalko + Show 2 more

Open Access

https://doi.org/10.1051/itmconf/20160602004

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Abstract

The paper describes a novel methodology for synthesis a high-level control of autonomous multi robot teams. The approach is based on multilayer network operator method that belongs to a symbolic regression class. Synthesis is accomplished in three steps: stabilizing robots about some given position in a state space, finding optimal trajectories of robots’ motion as sets of stabilizing points and then approximating all the points of optimal trajectories by some multi-dimensional function of state variables. The feasibility and effectiveness of the proposed approach is verified on simulations of the task of control synthesis for three mobile robots parking in the constrained space.

Highlights

The research and development of autonomous multi robot teams become a hot topic in recent years
Potential fields [3] method has gained popularity recently. In this method a feedback control function is synthesized in order to minimize Euclidean norm of the difference between the value of the state vector of the robot and the point of stabilization
In the present paper we propose a single method of multilayer network operator to feedback control system synthesis

Summary

Introduction

The research and development of autonomous multi robot teams become a hot topic in recent years. The optimal trajectories consist of sets of points where robots are stabilized. Potential fields [3] method has gained popularity recently In this method a feedback control function is synthesized in order to minimize Euclidean norm of the difference between the value of the state vector of the robot and the point of stabilization. We apply different techniques for different parts of the synthesis problem Another drawback of the existing methods is that they provide a set of optimal trajectories for different possible initial conditions. The method allows automatically constructing such multidimensional function of the robots’ state variables that can substitute the whole set of optimal trajectories of robots moving from different initial positions. Simulation results are presented for a team of three mobile robots aiming to move to a given terminal position from eight different initial conditions

Problem statement of control synthesis for multi robot team

Multilayer network operator

Simulations