Cognitive Supervisor for an Autonomous Swarm of Robots

作     者：Vladimir G.Ivancevic Darryn J.Reid 

作者机构：Decision SciencesJoint and Operations Analysis DivisionDefence Science&Technology GroupCanberraAustralia 

出 版 物：《Intelligent Control and Automation》 (智能控制与自动化（英文）)

年 卷 期：2017年第8卷第1期

页      面：44-65页

学科分类：07[理学] 0701[理学-数学] 070101[理学-基础数学] 

基　　金：part of the DSTG TAS SRI(Tyche)project 

主　　题：Autonomous Robotic Swarm Cognitive Supervisor Hippocampus Path Integration and Navigation Hamiltonian Path Integral Modal Logic Nonlinear Schrodinger Equation Reasoning about Actions and Plans 

摘      要：As a sequel to our recent work [1], in which a control framework was developed for large-scale joint swarms of unmanned ground (UGV) and aerial (UAV) vehicles, the present paper proposes cognitive and meta-cognitive supervisor models for this kind of distributed robotic system. The cognitive supervisor model is a formalization of the recently Nobel-awarded research in brain science on mammalian and human path integration and navigation, performed by the hippocampus. This is formalized here as an adaptive Hamiltonian path integral, and efficiently simulated for implementation on robotic vehicles as a pair of coupled nonlinear Schr?dinger equations. The meta-cognitive supervisor model is a modal logic of actions and plans that hinges on a weak causality relation that specifies when atoms may change their values without specifying that they must change. This relatively simple logic is decidable yet sufficiently expressive to support the level of inference needed in our application. The atoms and action primitives of the logic framework also provide a straight-forward way of connecting the meta-cognitive supervisor with the cognitive supervisor, with other modules, and to the meta-cognitive supervisors of other robotic platforms in the swarm.