Autonomous robot navigation system as part of a human-machine team based on self-organization of distributed neurocognitive architectures

Inna Pshenokova; Kantemir Bzhikhatlov; Olga Nagoeva; Idar Mambetov; Alim Unagasov

Inna Pshenokova The Federal State Institution of Science Federal Scientific Center Kabardino-Balkarian Scientific Center of Russian Academy of Sciences
Kantemir Bzhikhatlov The Federal State Institution of Science Federal Scientific Center Kabardino-Balkarian Scientific Center of Russian Academy of Sciences
Olga Nagoeva The Federal State Institution of Science Federal Scientific Center Kabardino-Balkarian Scientific Center of Russian Academy of Sciences
Idar Mambetov The Federal State Institution of Science Federal Scientific Center Kabardino-Balkarian Scientific Center of Russian Academy of Sciences
Alim Unagasov The Federal State Institution of Science Federal Scientific Center Kabardino-Balkarian Scientific Center of Russian Academy of Sciences

Keywords: Autonomous Robot, Human-Machine Team, Artificial Intelligence, Intelligent Agent, Multi-Agent Neurocognitive Architectures

Abstract

The relevance of this study is due to the solution of the problem of developing the basic principles and algorithms for providing adaptive settings for autonomous robots intelligent control systems as part of a human-machine team based on the general method of machine learning. To do this, the paper proposes to use a formalism based on multi-agent neurocognitive architectures. Implementation of the possibility of adaptation is considered on the example of performing the task of orientation and navigation of an autonomous robot in an unfamiliar environment.

An autonomous robot navigation system based on self-organization of distributed neurocognitive architectures has been developed.

A multi-agent neurocognitive architecture is presented, which forms an active map containing all the locative information necessary to ensure the orientation and navigation of an autonomous robot between loci.

The use of a multi-agent architecture to provide the representation of locative information in the task of implementing an interface in human-machine team will make it possible to build an ontology responsible for representing the location of objects in the external environment, as well as provide interaction with the user in natural language, taking into account its semantics. Further development of the approach is aimed at the implementation of the natural language interface of the human-machine team, which is not inferior in efficiency to the interaction between people.