An Innovative Cognitive Architecture for Humanoid Robot

Abstract

Humanoid robot is appearing as most popular research tool and emerging research field. The greatest challenge in the development of robot is cognition, advancement and the understanding in the human like cognition. Humanoid robot requires a self-learning behavior like the humans that is able to get the experience from environment. Based on experience, it can modify their actions, or having conscious intellectual capability to reduce empirical factual knowledge. In this regard, we propose a novel framework called an Innovative Cognitive Architecture for Humanoid Robot (ICAHR) that is capable to develop cognitive through social interaction and autonomous exploration. It combines the modules of active memory, decision processor, and sensor listener that has capability to perform self-learning behavior like human, to make decisions in dynamic environment, and perform more valid and intelligent actions with better precision. The proposed architecture may result in safe, robust, flexible, and reliable machines that can be substitute of human beings in different tasks. The feasibility of new proposed ICAHR design has been examined through real-world case studies.