BEAM ROBOTICS

PRESENTED BY, -RAJIV R -1YD06EC051

This presentation will include…

• Introduction to Digital Robotics.• Kinds of Digital Robots.• Strengths and weaknesses of digital robotics.• Introduction to BEAM(Biomorphic) robotics. • Strengths and weaknesses of Biomorphic

robotics.• Videos of beam robots. • Design.

Digital Robotics

Introduction to Digital Robotics

• Programmed with If/Then statements, providing criteria and appropriate, pre-set behavior for each situation.

• Any defects in sensors used leads to malfunction.

• Examples: QRio (Sony), Asimo (Honda)

Kinds of Digital Robots

• Entertainment (example: Sony Aibo or QRio)

• Industrial (example: painting and welding arms)

• Special-Effects (example: Jurrasic Park Dinosaurs)

• Research-based (example: Mars Rover, Honda Humanoid)

Digital RoboticsStrengths

• Precise, controllable movements.

• If/Then statements dictate exact behavior.

• Can repeat same task over and over.

Weaknesses• Can only deal with

predicted events.• Less scalable technology.• Requires massive

computing power for simple tasks.

• Usually not self-contained. (separate computer)

• Cannot function if damaged.

• Not suited to natural environment.

BEAM Robotics

Introduction to BEAM Robotics

• What it means: Biology, Electronics, Aesthetics, Mechanics.

• Design philosophy: Simplest possible design to perform a specific task. (No unessential features).

• Uses no programming.• Mimics organic life.• Actions dictated by physical design.• High survivability.

Different types of BEAM Robots.

• AUDIOTROPE-which reacts to the sound sources

• RADIOTROPE-which reacts to the Radio frequency sources.

• PHOTOTROPE-which reacts to light sources.

• THERMOTROPE-which reacts to heat sources.

BEAM Robotics

Strengths• Adaptable behavior to

fit situation.• Energy efficient.• Durable.• Renewable power

source.• Adaptable to damage.• Protects self.• Can survive outside

laboratory environment.

Weaknesses• Random behavior.• Not as taskable.• Inexact movements.• Not suited to “factory”

environment.• Reflexive.

Simple autonomous Robot-RADIOTROPE

IMPLEMENTATION

Design

• 4 limbs.• 2 solar cells i.e 1 for use and one for

backup.• RF sensor i.e only to sense the

enemy signals.• Neural networks to avoid collision• Wireless camera.• A position locater to locate the robot.

ARITIFICIAL NEURAL NETWORKS(ANN)

• An artificial neural network is composed of many artificial neurons that are linked together according to a specific network architecture

• Neurons mimic the properties of biological neurons.

• Each neuron of an artificial network learn from the environment in which robot is left.

ANN-implementation

• try to create an learning environment which comprises of enemy TX, host TX and actual war field environment.

• make neural networks to learn in this environment and make motors(which drives the wheels of robot) to run according to knowledge gained from neurons.

• Now the robot is left in the war field to find enemy TX.

• Robot reach the enemy TX without any collision due to neural networks implementation.

Robot-env 1

HOST TX

ENEMY TX

Robot-env 2

Robot-env 3

Robot-env 4

Robot-env 5

Robot-env 6

LEARNING ENVIRONMENT

Gaining Knowledge about Surrounding environment

Learning process is

completed

radiotrope

Solar cell 1

Solar cell 2

Low charge

Charging

Robot specifications

Position Locater

Navigation of robot using neural netw

Enemy tx.

RF SIGNALS

radiotrope

our tx.RF signals

Enemy signal detected

Missile launcherPosition

obtained

Conclusion

• The application of BEAM robots will be most effective for defence purpose.

• Navigation of robot is more accurate by using ANN.

• The end product is reliable and efficient.

REFERENCE• Solarbotics, Inc., “Connecting Nv Nets”

http://bftgu.solarbotics.net/starting_nvnet_connect.html

• Wilf Righter, “Tom Gray’s Junkbot Walker”, http://www.solarbotics.net/library/circuits/bot_walker_grayJunkbot.html

• Mark Tilden, "Design of Living Biomech machines", http://www.solarbotics.net/library/pdflib/pdf/DesignOfLivingBiomechMechn s.pdf

• "Living Machines" By: Mark Tilden and Brosl Hasslacher”

http://www.solarbotics.net/library/pdflib/pdf/living_machines.pdf

• Wikipedia: http://en.wikipedia.org/wiki/BEAM_robotics

• Neural Networks in Mobile Robot Motion. IEEE paperJanglová, D. / Neural Networks in Mobile Robot Motion, pp. 15-22, Inernational Journal of Advanced Robotic Systems,Volume 1 Number 1 (2004), ISSN 1729-8806

• Neural Networks- A Comprehensive Foundation: SIMON HAYIN,2nd edition.

THANK YOU!!!