THE CRITERION FOR FEATURE INFORMATIVENESS ESTIMATION IN MULTI ROBOT TEAMS CONTROL

Authors

  • M. O. Humeniuk Zhytomyr Military Institute named after S. P. Koroliov, Zhytomyr, Ukraine., Ukraine
  • I. M. Sashchuk Zhytomyr Military Institute named after S. P. Koroliov, Zhytomyr, Ukraine., Ukraine
  • Yu. V. Zhuravsky Zhytomyr Military Institute named after S. P. Koroliov, Zhytomyr, Ukraine., Ukraine

DOI:

https://doi.org/10.15588/1607-3274-2018-4-9

Keywords:

multi robot teams control, mutual information, informativeness criterion, feature set informativeness.

Abstract

Context. The task of automation of feature set informativeness estimation process in multi robot teams control is solved. The object of the research is the process of multi robot teams control. The subject of the research is the criterion of feature set informativeness estimation.
Objective. The research objective is to develop the criterion for feature set informativeness estimation in multi robot teams control.
Method. The criterion for feature set informativeness estimation is proposed. The developed criterion is based on the idea that feature set informativeness is computed according to values of the prior probabilitіes of finding features in the descriptions of the environment states. The use of the proposed criterion allows to efficiently solve the problem of feature set informativeness estimation, leading to effective solution of the multi robots control task. The developed criterion is based on the maximizing mutual information criterion and can be applicable when measurements are interdepended and environment has a variable number of states. The criterion doesn’t require to construct models based on the estimated feature combinations, in such a way considerably reducing time and computing costs for multi robot teams control. Application of the proposed criterion for feature set informativeness estimation allows to make a decision how much a new observation will increase the certainty of the robots’ beliefs about the environment state which is observed. Results. The software which implements the proposed criterion for feature set informativeness estimation and allows to manage multi robot teams has been developed.
Conclusions. The conducted experiments have confirmed operability of the proposed criterion for feature set informativeness estimation and allow to recommend it for multi robot teams control in practice. The prospects for further researches may include the modification of the known multi robot teams control methods and the development of new ones based on the proposed criterion for feature set informativeness estimation.

References

Charrow B. Information-theoretic active perception for

multi-robot teams, PhD thesis / Benjamin Charrow. – Philadelphia:

University of Pennsylvania, 2015. – 175 p.

The system of criteria for feature informativeness estimation

in pattern recognition / [A. A. Oliinyk, S. A. Subbotin,

V. M. Lovkin et al.] // Радіоелектроніка, інформатика,

управління. – 2017. – № 4. – C. 85–96. DOI

15588/1607-3274-2017-4-10.

McLachlan G. Discriminant Analysis and Statistical Pattern

Recognition / G. McLachlan. – New Jersey : John Wiley &

Sons. – 2004. – 526 p. DOI: 10.1002/0471725293.

Hyvarinen A. Independent component analysis / A. Hyvarinen,

J. Karhunen, E. Oja. – New York : John Wiley &

Sons, 2001. – 481 p. DOI: 10.1002/0471221317.

Grocholsky B. Information-theoretic control of multiple

sensor platforms, PhD thesis / Grocholsky Ben. – Sydney:

University of Sydney, 2002. – 199 p.

Grocholsky B. Information theoretic control of multiple

sensor platforms. / B. Grocholsky, A. Makarenko, H. Durrant-

Whyte // Proceedings of the IEEE International Conference

on Robotics and Automation. – 2003. – Vol. 1. –

P. 1521–1526.

Bourgault F. Information based adaptive robotic exploration.

/ F. Bourgault, A. Makarenko, S. B. Williams // In Proceedings

of the IEEE International Conference on Intelligent Robots

and Systems. – 2002. – P. 540–545.

Choi H. L. Continuous trajectory planning of mobile sensors

for informative forecasting / H. L. Choi, J. P. How // Automatica.

– 2011. – 145 p.

Ny J. L. On trajectory optimization for active sensing in

gaussian process models / J. L. Ny, G. J. Pappas // In Proceedings

of the Joint IEEE Conference on Decision and

Control and Chinese Control Conference. – 2009. –

P. 6282–6292.

Singh A. Efficient planning of informative paths for multiple

robots / A. Singh, A. Krause, C. Guestrin // Proceedings

of the International Joint Conference on Artificial Intelligence.

– 2007. – P. 93–105.

How to Cite

Humeniuk, M. O., Sashchuk, I. M., & Zhuravsky, Y. V. (2019). THE CRITERION FOR FEATURE INFORMATIVENESS ESTIMATION IN MULTI ROBOT TEAMS CONTROL. Radio Electronics, Computer Science, Control, (4). https://doi.org/10.15588/1607-3274-2018-4-9

Issue

Section

Neuroinformatics and intelligent systems