Special Issue: Robot Behavior. Architecture. Hierarchical Control Architecture for Intelligent Behavior. Sophistication of System by Adaptation and Learning.

A Behavior - Based Intelligent Control Architecture withApplication

The paper presents a behavior-based intelligent control architecture for designing controllers which, based on their observation of sensor signals, compute the discrete control actions. These control actions then serve as the \set-points" for the lower level controllers. The behavior-based approach yields an intelligent controller which is a cascade of a perceptor and a response controller. The...

A hierarchical fuzzy-genetic multi-agent architecture for intelligent buildings online learning, adaptation and control

In this paper, we describe a new application domain for intelligent autonomous systems – Intelligent Buildings (IB). In doing so we present a novel approach to the implementation of IB agents based on a hierarchical fuzzy genetic multi embedded-agent architecture comprising a low-level behaviour based reactive layer whose outputs are co-ordinated in a fuzzy way according to deliberative plans. ...

A behavior-based mobile robot architecture for Learning from Demonstration

Autonomous mobile robots (AMRs), to be truly flexible, should be equipped with learning capabilities, which allow them to adapt effectively to a dynamic and changing environment. This paper proposes a modular, behavior-based control architecture, which is particularly suited for “Learning from Demonstration” experiments in the spatial domain. The robot learns sensory-motor behaviors online by o...

Autonomous behavior control architecture of entertainment humanoid robot SDR-4X

A Self-Adaptive Intelligent Control System with Hierarchical Architecture

This paper presents an Intelligent Control System with Hierarchical Architecture, namely ICSHA. The advantages of three-layered ICSHA are able to carry out multiple tasks and to adjust its control rules automatically to adapt environments. The first layer, Planning Layer, we propose the ASGO (an extension version of Ant System with Genetic Operators) to determine the executing order of subtasks...