Assistive robots are developed to uplift living standards of human being. An assistive robot needs to be friendly, reliable, and understandable in order to be a human like companion. A robot should be able to understand its user effectively and the robot should be able to expand its knowledge based on experience gain from activities or conversations. Therefore the assistive robot should have a memory and a knowledge base regarding objects that it comes across in daily activities. It should be able to process data and understand relationships between attributes of objects to self-understand the need of a user. Therefore this paper propose a method to create an object memory and a knowledge base to understand relations between objects attributes and create a cognitive map to enhance interaction between human and robot which will help to make a robot more human-friendly. Conversation Management Module (CMM), Attribute Analyzing Module (AMM) and Object Knowledge Base (OKB) have been introduced in order to create a cognitive map of objects. Capabilities of the robot have been demonstrated and evaluated from experimental results.