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Contents

Abstract

Introduction

Problem Statement

Literature Survey

Autonomous Bipedal Mechanism

Principle of Operation

Block Diagram

Methodology

Features & Applications

References

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Abstract

Controlling a biped robot with a high degree of freedom to achieve

stable and straight movement patterns is a complex problem

With growing computational power of computer hardware, high

resolution real time simulation of such robot models has become moreand more applicable

Particle Swarm Optimization (PSO) is used to calculate optimum

direction of maneuvering of bipedal motion

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Introduction

Bipedal Locomotion

The technique of using legged mechanism instead of wheels

Inspired from the Bipedal Trajectile motion of humans andsimilar creatures to develop such systems for specializedapplication

Need and advantages

Replaces Wheeled motion effectively especially in rugged anduneven terrain

Provides Insight into the Biophysics of Human Motion

Uses and application

Autonomous Maneuvering of vehicles

Intelligent Motion in rugged terrain

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Problem Statement

The Aim of the projectis to implementeffective intelligent algorithms that can

- Simplify complexity of dynamics

- Produce effectively intelligent motion forautonomous locomotion

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Literature Survey

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Project Motivation

Wheeled Motion Ineffective in uneventerrains

Legged or Bipedal Motion seems aneffective solution

But complexity of control poses a practicalproblem

Autonomous Bipedal Mechanism(A.B.M)

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Passive Dynamic Walking

Mathematical model for reflexive motion of human legs.

Represents Bipedal motion as a type of Inverted Pendulumloosely controlled through neural receptors

Self Maneuvering with Intelligent Algorithms (IAs)

Above principle of mechanism easily implemented by humanbrain control

But complex to be realized using logic algorithms

Intelligent algorithms utilizing optimization techniques areused to approximate such motion

Principle Of Operation

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Block Diagram

AVR

BASED

MOTHER

BOARD

SENSOR

CONTROL

BOARD

MOTOR

CONTROL

BOARD

MOTOR - 1

MOTOR - 2

MOTOR - 4

MOTOR - 3

S1

S2

S3 S4

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Working

Servo Motors

RC servos DC Motors withPWM control

S/W PWM generated throughmotherboard

Bipedal Operation Utilizes Partial Passive Dynamic

walking mechanism

Angle of leg joints preciselycontrolled using RC Servos

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Working (Contd)

Sensing Mechanism

4 Optical Proximity Sensors used

Two for Obstacle Detection

Two for Level Detection

Intelligent Sensing Makes use of optimization algorithms for deciding the

direction, angle, orientation of maneuvering.

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Features and Applications

Advantages

Motion on rugged surfaces

Autonomy of action

Disadvantage

Complex algorithm

Higher root locus area for instability

Application

Autonomous Maneuvering of vehicles

Obstacle Detection

Intelligent Motion in rugged terrain

Prosthetic Leg

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IEEE papers mentioned in the Literature Survey have been

referred

Hazem Ahmed, Janice Glasgow, Swarm intelligence,:

Concepts, Models and Applications, Technical Report 2012-585.

Mark Flischer, Foundations of Swarm Intelligence, University

of Maryland

Ajith Abraham, He Buo, Hongbo Liu, Swarm Intelligence

Foundations, Perspectives and applications

Davoud Sedighizadeh and Ellips Masehian, Particle Swarm

Optimization Methods, Taxonomy and Applications.

Reference

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Thank You