Model Based System Engineering Of a Smart Collaborative Robot with Vision, Voice and IoT Capabilities

Model Based System Engineering Of a
Smart Collaborative Robot with Vision,
Voice and IoT Capabilities

Table of Contents
Introduction......................................................................................................................................2
Aim & Objectives............................................................................................................................2
Literature Review............................................................................................................................3
Methodology....................................................................................................................................4
Requirements Specification.............................................................................................................5
Design Specification........................................................................................................................7
Design Concept and Final Design...................................................................................................9
Results and Analysis......................................................................................................................11
Obstacle detection......................................................................................................................11
Path finding using A* algorithm................................................................................................14
Conclusion.....................................................................................................................................20
References......................................................................................................................................21
1

Introduction
A 1995 research mission (General Motors Foundation) was the basic foundation of the
collaborative robots. The main target of the mission was to devise a method which would enable
the robots (or equipment resembling robots) to work with the humans in their specific
environments in a highly safe manner. Crucial robotic manufacturers (in the collaborative
market) such as KUKA, FANUC, Universal Robots, Motoman and ABB are continuously
working towards the development of responsive and smart robots. Along with making certain
improvements in the functionality of the app, the collaborative robotics movement is also
lowering down the required space in respect to a robotic unit. Numerous benefits are being
offered to the production lines, business houses as well as workers by the collaborative
technology [6]. Cobots have the capability of undertaking varied roles across different industries
as well as operating in almost all work environments along with human beings. Apart from this,
these collaborative machines are also capable of performing numerous tasks like commodity
packing, assembling, palletizing and others.
Aim & Objectives
This project deals with the development of a sharp, collective palletizing robot (in respect
to the manufacturing industry) who has the potential of working along with human beings. So
“safety of humans” must be an important component of the robot’s design. For this, features such
as voice-control, vision, IoT are crucial. Below we are going to mention some activities
(project’s objectives) which are crucial to be undertaken for the achievement of the above
discussed aim.
• Undertake the primary study in respect to the collaborative robot.
• Gather crucial info in regards to collaborative robot.
• Undertake the literature review
• Performance of the design creation process
• Performance of the substitute process of examination and selection
2

• Undertaking the task of design development and duplication
Literature Review
The collective robotics app. allows the robots and human beings to work together in a
free environment in an effective and safe manner without the fear of injuries. Numerous latest
software, sensors and EOATs in the collaborative robots (cobots) aid them in quick and easy
detection of any interruptions in the work place so that they can be timely adapted to. Generally,
cobots have round type shape[5]. They come without any internal wires and motors as well as
pinch points. Also, any irregular force being applied to their joints can be easily detected by them
during motion. Apart from this, such programming can also be done to these robots which will
enable them to stop or reverse their positions whenever they face any human contact. Being
guided by hand, their programming as well as implementation is known to be made highly
simplified. This means that once the worker directs the robots of the desired paths, they can
easily and automatically repeat them[4].
Author Name Intext
citation
Year Method Performance
Lars Bretzner, Ivan
Laptev and Tony
Lindeberg
[7] 2002 Hierarchical Models,
Multi-Scale Color
Features, and Particle
Filtering
color prior: 86.5%
No color prior: 45%
Junqiu Wang and
Yasushi Yagi
[8] 2009 Adaptive Mean Shift 64.11%
Jifeng Ning [9] 2009 Mean Shift, Joint Color-
Texture Histogram , and
Local Binary Pattern
JCTH :8.22
LBP:10.78
Mean Shift:2.83
Kaihua Zhang et al [10] 2013 Active Feature Selection 83%
Lokesh Selvaraj and
Balakrishnan
[11] 2014 IP-HMM 97.14%
3

Ganesan
Jiangyang Zhang,
Shangwen Li, and C.-
C. Jay Kuo
[12] 2014 Video retargeting system
and Compressed-domain
94.81%
Methodology
Model based systems engineering is a systems engineering technique which tends to
utilize visual modeling as the initial source of info exchange. When compared with the old info
exchange, MBSE promises to remove the exchange of any unimportant info. This is because it
depends on the abstract models which store only crucial data. This way, it gets simple for the
engineering teams to discuss the design intent, get aware of the influence of the changes in
design as well as examine the design of the system before they start to build it.
The first cycle begins with the Concept-of-Operation stages, setting up the cases,
essentials and plans. Either a SysML modeling tool, a requirements management tool or some
amalgamation of both might be used to undertake it. This is the essence of the primary effort at
the system architecture, by choice in the SysML tool in place of MS Office (or Vizio).
After multiple starting cycles, the development process is known to achieve expansion in
regards to people and tools. Huge levels of efforts are put in the right-hand quadrant by the
domain engineers utilizing CAD or programming environments along with the accompanying
PLM/ALM repositories. However, the SysML model may stay as a very necessary part of the
TSM. The distribution of the system design data across multiple varying tools turns the Synthesis
process highly difficult. Creating such a graph of connection among the tools which would offer
help in recollection of the discrete engineering efforts is the first job of an MBE platform like
Syndeia.
Next job of the MBE platform is the development of a model which is transformed to
special examination as well as duplication tools which offer regularity with the present
4

synthesized TSM. The last job of the MBE platform is to bring the simulation and examination
outcomes inside the V&V quadrant so as to give a picture of the system development’s ongoing
position.
With the advancement of the system development, extra tools and people are added up in
the process. More comprehensive designs and thoroughly authenticate interpretations are made.
This is followed up by the execution of the non-digital activities related to building,
incorporation and testing. At this point, the MBE Wheel takes the image of an onion consisting
of multiple layers. This leads to a rise in the expectations on the MBE platform. In place of
creating new analysis models, consideration should be given to the fact that the framework is
capable of comparing the current models and improving them as needed. The growth of
connections is posing a huge challenge in regards to efficient tracking of links across the TSM.
Requirements Specification
The palletizer robot which has been presented here is known to move a particular box
from A to B place during which it navigates and prevents crashes. For goal achievement, the
below mentioned tasks have been faced:
 Usage of contact and sonar sensors for environment perception.
 Path planning strategy on the basis of A* algorithm.
 Performance of the path of robot and interaction of the robot with the changing obstacles.
The force and velocity needed for acquiring and moving an object from one location to
another (the servomotors not to be forced), was taken as the base for gearbox designing. Total 8
gears i.e. 1 of 36 teeth, 3 of 16 teeth and 4 having 24 teeth were utilized by the gearbox.
5