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CONTENTS

CONTENTS. Types of intelligence Methods used for mobile robots Computational intelligence in robotics system Sensory network for perceiving environment Mobile Robotic system based on a fuzzy controller Collision avoidance by a fuzzy controller Case Study of Mirosot Robot .

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CONTENTS

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  1. CONTENTS • Types of intelligence • Methods used for mobile robots • Computational intelligence in robotics system • Sensory network for perceiving environment • Mobile Robotic system based on a fuzzy controller • Collision avoidance by a fuzzy controller • Case Study of Mirosot Robot

  2. INTRODUCTION TO INTELLIGENT ROBOTIC SYSTEM • BASIC DEFINITION OF INTELLIGENT ROBOT: Robots that are able to perceive the environment, make decision, represent sensed data and can acquire and usefully apply knowledge or skills are called as intelligent robot. • TYPES OF INTELLIGENCE: (1) Artificial (2) Biological (3) Computational

  3. INTRODUCTION TO METHODS INTELLIGENT ROBOTIC SYSTEM • METHODS USED FOR MOBILE ROBOTS: (1) Subsumption Architecture (2) Behavior Based Artificial Intelligence (BBAI ) (3) Monalysa architecture (4) Model based learning (5) Hierarchical intelligent control

  4. COMPUTATIONAL INTELLIGENCE IN ROBOTICS SYSTEMS • Emerging Synthesis of NN, FS and EC: (1) NN: NEURAL NETWORKS are useful for recognizing patterns, classifying input and adapting to dynamic environments by learning. (2) FS:FUZZY SYSTEMS can cope easily with human knowledge and can be used to perform inference, but FS do not fundamentally incorporate any learning mechanism. (3)EC: EVOLUTIONARY COMPUTATION tunes neural network and FS. Furthermore, EC has been used for optimizing the structure of neural network and fuzzy system. The goal is for an intelligent system to quickly adapt to a dynamically changing environment.

  5. (1) Skill (2) Neurodynamics (3) Recursive “consciousness”. Structured Intelligence for A Robotic System • ARCHITECTURE OF STRUCTURED INTELLIGENCE

  6. A SENSORY NETWORK FOR PERCEIVING ENVIRONMENT The robot recognizes quantitative information of the environment. Next, the robot perceives its external environment through the interpretation of selective attention into the qualitative information by sensor fusion/integration and focus/release The action comprises of reactive motion (reflex), skilled motion, primitive motion planning, and final motion planning.

  7. MOBILE ROBOTIC SYSTEM BASED ON A FUZZYCONTROLLER • Target Trace and Collision Avoidance for A Mobile Robotic System: SENSING DIRECTION Di FOR DETECTING OBSTACLES CANDIDATE PATHS AVOIDING COLLISION WITH OBSTACLES

  8. COLLISION AVOIDANCE BY A FUZZY CONTROLLER A TRIANGULAR MEMBERSHIP FUNCTION CONCERNING THE DISTANCE Xk BETWEEN THE MOBILE ROBOT AND OBSTACLES Sensory Network for Mobile Robots - used to construct compact & useful fuzzy rules. - fuzzy rules are usually not generalized, but are to be changed in different environments.

  9. CASE STUDY OF A MIROSOT ROBOT BASED ON FUZZY CONTROLLER • DESCRIPTION OF ENVIRONMENT AND ITS OBJECTIVE: CONTROL STRUCTURE BLOCK DIAGRAM

  10. CASE STUDY • FUZZY MOTION CONTROLLER:

  11. CASE STUDY • Fuzzy Membership Function:

  12. CASE STUDY • Fuzzy Associative Memory (FAM): TABLE: 1 TABLE: 2 • Table 1 for left motor which is FAM rule (NL,VN: ME) corresponds to the following fuzzy association: IF θe = NL( negative large)ANDDe = VN (very near) THEN VL = ME(medium)

  13. CONCLUSION • This seminar presents an entire integrated structure of intelligent robotic system based on fuzzy controller • I have focused mainly on the perception capabilities based on the sensory network.

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