2.  Advances in
mechatronics have resulted in
widespread of robotics.
 Today robots are controlled by computers.
 Technical advances are gradually increasing
their similarity to human.
 Engineers are attempting to add sensors to
enhance their ability to perform function.

3. 

Intelligence
Vision

4.  Robots could
not perform difficult tasks.
 AI to robots gives the power to make decision
and logical inferences.
 Robots use sensors and cameras to obtain
information from environment.
 Use of microprocessor in robotics is to
enhance their intelligence.

5.  ANN
is a network of processing elements
capable of doing processing in parallel and in
distributed manner.
 ANN is a mechanism work same as that of
human brain.
 ANNS are mathematical models of infoProcessing.
 It has two types:
a) Single layer Neural Network
b) Multi layer Neural Network

6.  Back
propagation is a technique with
backward error propagation.
 It reduces the error from hidden layers.
 In back propagation network the activation
function chosen is the tan sigmoid function.
 The sigmoid function accommodate large
signals without saturation.
 Sigmoid Transfer function is…
Yi = 1/1+e^-X

7.  Such
like AI vision is also essential for robots.
 Machine vision can be defined as the
acquisition of image, followed by processing
and interpretation of image by computer.

8.  A mini
robot was developed which was
capable of pushing the components.
 This robot consists of two cameras for vision.
These cameras capture the top and front image
of minimum resolution 128 128.
 There is a gripper used to place the
components into the bin.
 The gripper and cameras are controlled using
computers.

9.  The
captured image should be processed to
obtain the best results.
 There are three steps of image processing:
a) Image acquisition
b) Image processing I
c) Image processing II

10. 
In this stage the captured image is read by dividing
the bit map image into pixel.
 Each pixel has a value that is proportional to the light
intensive of that small proportion of the scene.
 The new divided image is stored from bottom to top.

11. 
ANN is developed in such a way that it will operate
only on binary codes, i.e. 0 and 1
 The captured image contains red, blue and green
ranges.
 Colored image should convert to black and white
image.
 This image contains a large amount of noise. Various
parameters are used to remove these noises.
 After removing the noises the tilted image is obtained.

12. 


The size of captured image is varying due to some eternal
factors.
To reset the size of image a technique, Set Partitioning In
Hierarchical Tree (SPIHT) method is used.
By SPIHT normal size image can be obtained.

13.  Camera
does not require a driver to operate.
 Brightness, resolution and other settings can
change.
 Separate module is provided for controlling
the robot.
 ANN is generalized network.
 Image identification time is faster.

14.  Learning time
increases as the number of
training cases increases.
 It requires some memory for Database
operation.
 If the position of cameras changed then it
requires training .

15.  The
developed ANN system has been tested
and the results are satisfactory.
 The proposed system can be implemented
without substantial modification, using
available equipment, thus the cost is very low.
 This research has two main directions,
a) Improvement in the integration of the system
b) Identification of components at various light
sources and environments.