Robotics assignment 2

2013

Kartikey Totewar – BT11MEC080

Harshal Wankhede - BT11MEC089

Tushar Dhanwani - BT11MEC083

Nikita Ankem - BT11MEC015

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Details of Research Paper Author name: Fusaomi Nagata, Sho Yoshitake, Akimasa Otsuka, Keigo Watanabe, Maki K. Habib.

Paper Title: Development of CAM system based on industrial robotic servo controller without using

robot language

Name of journal: Robotics and Computer-Integrated Manufacturing

Volume: 30

Issue: 4 October 2012

Page number: 9

Year of publication: 2012

Introduction Until now according to the tasks needed to be performed by the industrial robots, several promising

teaching techniques have been developed. The following are some of the examples:

A joystick teaching system for a polishing robot to safely obtain desirable orientation data of a sanding

tool attached to the tip of robot arm.

A simple teaching method including human demonstration to teach an Industrial Robot was proposed

by Maeda in which the automated camera calibration avoided the absolute positional error and the

labor involved in teaching an Industrial Robot.

For the control of an industrial articulated arm Kushida proposed a force free control method in which

the robot arm was directly moved by human force.

Two kinds of teaching support devices, a three-wire type and an arm-type were proposed by Sugita for

deburring and finishing a robot.

Kamisetty and McDermott designed a CAD/CAM translator for the IBM 7535 SCARA (Selective

Compliance Assembly Robotic Arm) robot and reported the successful development of the translator to

convert the simulation data from McDonnell Douglas’ Place system to Aml/e robotic language. This was

done by off line teaching.

Ge developed a basic transformation of CAD data to robot control commands for a polishing robot.

Using Vision Information for robotic task assembly an off line teaching method was proposed by Ahn &

Lee.

Masood developed a server- client model and a protocol for networked motion control based on G-

code, so that an industrial robot could be automatically programmed offline using a common CAM

software.

Transformative robot program generation method was proposed by Chen which can generate new

robot programs for similar parts based on the existing ones in the database. Studying the robot path

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planning based on the CAD models of parts for spray painting he applied it to surface manufacturing to

reduce programming efforts.

Neto proposed CAD-based off-line teaching system which allows users with basic CAD skills to generate

robot programs off-line, without stopping the robot integrated within a production line.

Besides Pan provided a comprehensive review of the recent research progress on the programming

methods for industrial robots, including online and offline programming and programming using

Augmented Reality (AR), and concluded that the development of a more powerful 3D CAD system,

computer vision, sensor technology etc are important to develop new programming methods.

When performing any task nearly all the industrial robots require position and orientation data which is

provided to them through online teaching using teaching pendant and/or offline teaching using currently

available CAD/CAM system but on using a CAM system specifically for industrial robot there are very limited no.

of research papers available. There had been some advances in using CAM system specifically for industrial

robots like in order to cope up with the rapid prototyping 3D CAD defined products, Andres developed an

implementation of a post-processor to adapt the tool path generated by a CAM system. Further Solvang

introduced ‘Step NC’ based industrial robots but their actual application on them was not described. As

compared to NC machines in which the common CAD/CAM has been widely studied and explored the

relationship between common CAD/CAM system and industrial robot has not yet been explored sufficiently. This

is because as compared to NC machines the configuration of an industrial robot needs some extra information

and further path planning algorithms, for example, to avoid self-collisions and singularities. That is the reason

why the required position and orientation data for industrial robots are acquired by on-line and/or off-line

teaching system. Thus we can safely conclude that development of CAM systems for industrial robots without

using any robot language has not yet been

developed and studied sufficiently.

A Cutter Location Data (CL data) consists of

position and orientation components. The CAM

system thus developed (explained afterwards in

the report) allows an industrial robot to move

along the CL Data.

Here for explaining purpose RV1A is

considered however this CAM system has a high

applicability in other robots whose servo system is

technically accessible to the end users. Although

the RV1A basically equips with a teaching

pendant and a robot language, it is not necessary

to use them due to the proposed robotic CAM

system.

Fig. Desktop-size industrial robot RV1A with an open architecture controller based on Ethernet.

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In this report a robotic CAM system is developed and described for controlling an industrial robot with

the help of servo controllers without using any robot language or teaching pendant. The following is the

difference between the conventional method and the method of the CAM system described here.

The following report will deal in explaining the basic design of the robotic CAM system and its

experimental results.

Keywords

Industrial robot Robot language

Teaching pendant

Robotic CAM system

CAD/CAM

Cutter location data

Robotic servo system

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Findings from the Review of Literature Normally any Industrial robot needed to perform a given task requires position and orientation data

through online teaching using a teaching pendant and/or offline teaching using currently available general

CAD/CAM systems. At the present stage, the relationship between CAD/CAM and industrial robots is not well

established compared to NC machine tools that are widely spread in manufacturing industries. However the

paper proposes the development of a robotic CAM system for an articulated industrial robot RV1A which is

implemented without using any robot language or teaching pendant. The main processor of CAD/CAM

calculates CL data according to each model’s shape and machining strategy. The paper then describes how the

developed CAM system allows an industrial robot to move along Cutter Location (CL Data) consisting of position

and orientation. Thus the CAM system calculates the CL Data and directs servo control based on CL Data thus

there is no need to use any robot language.

Applications • The concept of the proposed robotic CAM system can be used to develop a 3D carving system for

wooden materials with the help of Industrial Robot. The Robotic CAM system will serve as an important

interface between the common CAM system and the Industrial Robot. Also, it will be considered for

further flexibility and efficiency how to take the advantage of a non-aligned tool in order that the system

becomes redundant and the same task can be carried out with several postures of the robot.

• In addition, the developed CAM system has a high applicability to other industrial robots whose servo

systems are technically opened to end-users.

Methodology / Algorithm / Proposed Approach Generation of cutter location data:

The position and orientation of CL data along 3D is generated by the main processor of CAM/CAM

system. The main use of CAM system is to develop a relation between the processor of CAD/CAM system and an

industrial robot.

Acquirement of position and orientation components without teaching:

The trajectory of the tool, wr(k) is generated by using the CL data which is given by the processor.

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The desired trajectory is given by ,

wr(k) = [wxdT(k) wod

T (k)]T (1)

where,

w-work coordinate designed by 3D CAD/CAM system.

wxd(k) = [wxd(k) wyd(k) wzd(k)]T and

wod(k) = [wodx (k) wody

(k) wodz (k)]T are desired position and orientation components.

Where, wod(k) is normal vector at the position wxd(k) and k is the discrete time.

Calculation of wr(k):

The CL data are calculated with linear approximation along a given model surface generated in 3D

CAD/CAM system.

CL data for i-th step is given by a vector:

cl(i) = [px(i) py(i) pz(i) nx(i) ny(i) nz(i)]T (2)

{nx(i)}2 + { ny(i)}2 + { nz(i)}2 = 1 (3)

Where,

p(i) = [px(i) py(i) pz(i)]T

n(i) = [nx(i) ny(i) nz(i)]T are position and orientation vector from origin wO, respectively.

wr(k) is obtained by using linear equation and a tangential velocity scalar vt called feed rate.

Fig. Relation between CL data cl(i) and desired trajectory wr(k), in which wO is the origin of work coordinate

system.

A relation between cl(i) and wr(k) is shown in above figure 3.

If wr(k) € [cl(i-1), cl(i)], then wr(k) is calculated by following method.

The direction vector,

t(i) = [tx(i) ty(i) tz(i)]T is obtained from

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t(i) = p(i)-p(i-1) (4)

and the directional (x-, y- and z- directional components describe in work coordinate system as follows:

vti = vt 𝑡𝑗(𝑖)

||𝒕(i)|| (5)

considering a sampling width Δt, can calculate each component of desired position, wxd(k), as follows:

wxd(k) = wxd(k-1) + vtxΔt (6)

wyd(k) = wyd(k-1) + vtyΔt (7)

wzd(k) = wzd(k-1) + vtzΔt (8)

Fig. Enlarged illustration to explain the relation between position components p(i) in the CL data and desired

position wxd(k) in which p(i)- wxd(k) and p(i+1)- wxd(k+3) are called the fraction vectors.

Calculation of wOd(k):

Rotational vector tr(i) = n(i) – n(i-1) (9)

Where,

t(i) = [txr(i) tyr(i) tzr(i)]T

Therefore by using tr(i) we can calculate desired orientation

wOdj(k) = nj(i-1) + trju(i) {[|| wxd(k) – p(i-1)||] /[ ||t(i)]}…..(j=x,y,z) (10)

Again, CL data will give us wxd(k) and wod(k) value directly.

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Here we are using linear approximation hence our curve which is formed by CL data is continuous minute lines

such as p(i) – p(i-1) and p(i+1) – p(i) as shown in above figure.

This methodology is implementation on an articulated robot RV1A, which basically used a teaching pendant and

a robotic programming language MELFA – BASIC as standard tool. But as we are using robotic CAM system it is

not necessary to use both of them.

Fig. Block diagram of communication system by using UDP packet.

As shown in above figure the RV1A and windows PC is interfaced by using Ethernet.

The PC controller application is developed on Windows dialogue.

Fig. Communication scheme by using UDP packet between a PC controller and an industrial robot RV1A.

The above diagram shows the UDP communication scheme used in RV1A. The ‘sendto()’ function gives

us the reference vector of desired position [Xd(k) Yd(k) Zd(k)]T (mm) and orientation [Φd(k)θd(k)Ψd(k)] (rad) in

robot absolute coordinate system. Φd(k), θd(k) andΨd(k) are desired rotational angel which is called as X-Y-Z

fixed Euler angel. The UDP stores the desired position and orientation of arm tip in the Cartesian-based

coordinate system. Similarly the current location vectors of arm tip can be obtained by ‘recvform()’ function

which is used as feedback quantity of actual position and orientation.

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Software Used

Various kinds of 3D CAD/CAM systems which are commonly used in manufacturing industries like Catia,

Unigraphics, Pro/Engineer, etc. can be used.

A Windows PC is used as a controller and it is connected to RV1A with Ethernet. Also an application for

PC controller is developed based on window’s dialogue.

Observations

An experiment of trajectory following control was conducted using the suggested technique. The

following figures show the desired trajectory generated using the main processor of 3D CAD/CAM and the actual

control results of experiment conducted using industrial robot RV1A respectively.

Fig. CL data cl(i) = [pT(i)nT(i)]T consisting of position

and orientation components, which is used for

desired trajectory of arm tip. This figure is

disintegrated into Figs. 10–14.

Fig. 3D view illustrated in robot absolute coordinate

system, in which actual controlled results X(k), Y(k)

and Z(k) are plotted.

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The experiment aimed to control the arm tip so as to follow a desired sets of positions and orientations.

The following observations were made and the x-component, y-component and z-component was plotted

across time for the first 200 seconds. The observations are illustrated in the figures a, b and c.

Fig. Initial range of the x-component

Xd(k) of desired trajectory described

in robot’s absolute coordinate

system.

Fig. Control result of x-

directional position X(k).

Fig. Initial range of the y-

component Yd(k) of desired

trajectory described in robot’s

absolute coordinate system.

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Fig. Control result of y-directional

position Y(k).

Fig. Initial range of the z-

component Zd(k) of desired

trajectory described in robot’s

absolute coordinate system.

Fig. Control result of z-directional

position Z(k).

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The following figures show the initial ranges of the roll angle and the pitch angle for the required trajectory.

Fig. Initial range of the desired roll

angle ɸd(k) calculated from the

desired trajectory shown in

previous fig.

Fig. Control result of roll angle ɸ(k).

Fig. Initial range of the desired

pitch angle ϴd(k) calculated from

the desired trajectory shown in

previous fig.

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Fig. Control result of pitch angle ϴd

(k).

Result It was confirmed from the experiment that desirable control results of position and orientation could be

obtained. The arm tip could gradually move up from the bottom center along the spiral path desired. In this

case, the orientation of the arm tip was simultaneously controlled along the normal direction to the surface. It

was successfully demon-strated that the proposed CAM system without using any robot language allows the tip

of the robot arm to desirably follow the desired trajectory given by multi-axis CL data without any complicated

teaching tasks.

Conclusion

From the experimental results, it can be said that based on the technical capabilities of the developed

robotic servo control based CAM system, the industrial robot can be controlled in cooperation with a common

3D CAD/CAM system without the use of any robot language and teaching process.

The required CAM system for an industrial robot was realized as an integrated system mainly between

the conventional main-processor of a CAD/CAM system, the robotic servo control system and the kinematics of

the robot, so that the post-process and the teaching process to generate robot languages could be rationalized.

Critical Comment on the Work

Using the position and orientation data obtained from the CL Data the desired position and orientation

for a servo robotic system can be found out. Thus there is no need to use the teaching pendent to obtain the

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position and orientation information for the arm tip. Also the CL Data obtained can be directly used to direct the

servo motors thus the tedious job of generating each robot language can be avoided. This is great help for the

developers of Industrial Robots as this applicability was only known for NC machines which resulted in its

tremendous popularity.

But there can be a discrepancy in this algorithm. If the trajectory intersects itself at any point, the arm

tip after reaching such a point may not follow the desired trajectory but may choose an alternative path which

might make the arm tip to repeat the earlier followed path.