Robotics report

VISVESVARAYA TECHNOLOGICAL UNIVERSITY
BELAGAVI
A PROJECT PHASE-1
Report on
“INTERACTIVE HUMANOID ROBOT”
Submitted in partial fulfillment of the requirement for the Phase 1
Bachelor of Engineering
In
“INFORMATION SCIENCE AND ENGINEERING”
Submitted by
1. Mr. Abhay Pratap 1NC16IS004
2. Mr. Bivek Kumar Jaiswal 1NC16IS014
3. Mr. Mausam Kumar 1NC16IS026
4. Mr. Ritesh Yadav 1NC16IS040
Under the Guidance of
Prof. Ashok S Patil
Associate Professor
DEPARTMENT OF INFORMATION SCIENCE AND ENGINEERING
NAGARJUNA COLLEGE OF ENGINEERING AND TECHNOLOGY
(An Autonomous Institution under VTU, Belgavi-590014)
VENKATAGIRIKOTE, DEVANAHALLI, BENGALURU– 562164
2019-20

DEPARTMENT OF INFORMATION SCIENCE AND ENGINEERING
CERTIFICATE
This is to certify that the project work entitled “INTERACTIVE HUMANOID ROBOT”
carried out by Mr. Abhay Pratap (1NC16IS004), Mr. Bivek Kumar Jaiswal (1NC16IS014),
Mr. Mausam Kumar (1NC16IS026), Mr. Ritesh Yadav (1NC16IS040) bonafide students of
Information science and engineering of Nagarjuna College of Engineering and Technology in
partial fulfillment for Project Phase-1 of 7th semester during the year 2019-2020.
Signature of the Guide Signature of the HOD Signature of Principal
Prof. Ashok S Patil Dr. Mamatha G Dr. Srinkanta Murthy K
Assoc. Professor, ISE HOD, Dept. of ISE Principal, NCET
Internal/External Viva
Name of the Examiners Signature with date
1…………………………. …………………….
2………………………….. ………………………

ACKNOWLEDGEMENT
The satisfaction and euphoria that accompany the successful completion of any project would be incomplete
without mentioning the people who made it possible, whose constant guidance and encouragements crowned our
efforts with success. I take this opportunity to express the deepest gratitude and appreciation to all those who held
me directly or indirectly towards the successful completion of the project
We would like to convey my heartiest regard and thanks to guide Prof. Ashok S Patil, Associate Professor.
Department of ISE, for his valuable suggestion and constant encouragement that he provided at every moment we
needed it during our project phase-I.
We would like to thank our project coordinator Prof. Ashok S Patil, Associate Professor Department of ISE, for
his guidance to complete our project phase-I.
We would also like to thank Dr. Mamatha G, Professor & Head of Department ISE, for her parallel guidance
to complete our Project phase-I.
We would like to thank Dr. Srikanta Murthy K, Principal, NCET for lending his help for the completion of our
project phase-I.
Gratitude should also be conveyed to the staff of the Department of ISE, NCET for their full cooperation.
Name USN
ABHAY PRATAP (1NC16IS004)
BIVEK KUMAR JAISWAL (1NC16IS014)
MAUSAM KUMAR (1NC16IS026)
RITESH YADAV (1NC16IS040)
i

Humanoid Interactive Robot
ABSTRACT
The humanoid robot can use its control function to stimulate more number of responses to its
environment and uses a computing speed of milliseconds to anticipate and react to the movements
done by workers at the workplace. For implementing the robot control and computer vision
functions a set of applications was developed in Raspberry Pi using Open CV. The Image
processing is done by the processor Raspberry Pi and all the robot movements will be controlled
by Arduino mega. Various sensors will be embedded to fetch the data from the environment or the
user. Required information is conveyed through audio and video systems to the user. In this project,
we will demonstrate that this service framework enables the robot to serve people efficiently. This
project presents the development of a humanoid robot. Humanoid Robots are built to mimic
humans. The humanoid robot navigation problem is decomposed into a series of small multi-
objective optimization problems (MOPs) with corresponding local information. Using multi-
objective evolutionary algorithms (MOEAs), the MOPs can be successively solved while the robot
is walking. In this study, a set of solutions for reproducing the human head movement and part of
the sensorial capabilities are developed and analyzed.
ii

TABLE OF CONTENTS
ACKNOWLEDGEMENT i
ABSTRACT ii
TABLE OF CONTENTS iii
LIST OF FIGURES iv
CHAPTER NO. CHAPTER NAME PAGE NO
Chapter 1
1.1
1.2
1.3
Introduction
Classification of robots
Humanoid Robots
1
1
2
Chapter 2 Literature survey 4
Chapter 3 Methodology 7
Chapter 4 Block diagram 9
4.1 Expected Outcome 9
Chapter 5 System Requirement and Budget Estimation 10
Chapter 6 Action Plan 11
Chapter 7 Conclusion 13
Chapter 8 References 14
iii

LIST OF FIGURES
FIGURE NO. FIGURE NAME PAGE NO.
1.1 Humanoid Robot 3
3.1 Humanoid Robot Testing 8
4.1 Block Diagram of Interactive Humanoid
Robot
9
iv

CHAPTER 1
INTRODUCTION
1.1 Introduction
The modern definition of a robot can be an electro-mechanical device that follows a set of
instructions to carry out certain jobs but literally, robot means a ‘slave’. Robots find wide
application in industries and thus they are called as industrial robots, Robots are known to perform
tasks automatically without much human intervention.
1.2 Classification of Robots
Articulated – Articulated robot design features rotary joints and can range from simple two joint
structures to ten or more joints. The arm is connected to the base with a twisting joint. The links
in the arm are connected by rotary joints. Each joint is called an axis and provides an additional
degree of freedom, or range of motion. Industrial robots commonly have four or six axes.
Cartesian - These are also called rectilinear or gantry robots. Cartesian robots have three linear
joints that use the Cartesian coordinate system (X, Y, and Z). They also may have an attached wrist
to allow for rotational movement. The three prismatic joints deliver a linear motion along the axis.
Cylindrical - The robot has at least one rotary joint at the base and at least one prismatic joint to
connect the links. The rotary joint uses a rotational motion along the joint axis, while the prismatic
joint moves in a linear motion. Cylindrical robots operate within a cylindrical-shaped work
envelope.
Polar – A polar robot is also called as spherical robots, this configuration consists of arm which
is connected to the base with a twisting joint and a combination of two rotary joints and one linear
joint. The axes form a polar coordinate system and create a spherical-shaped work envelope.
SCARA – SCARA stands for Selective Compliance Assembly Robotic Arm, SCARAs are
generally faster than comparable Cartesian robot systems. There single pedestal mount requires a
small footprint and provides an easy, unhindered form of mounting.

Department of ISE, NCET Page 2
Delta – A delta robot is a type of parallel robot that consists of three arms connected to universal
joints at the base. This spider-like robots are built from jointed parallelograms connected to a
common base. These are used in the food, pharmaceutical, and electronic industries, this robot
configuration is capable of delicate, precise movement.
1.3 Humanoid Robot
A Humanoid Robot is a robot built to resemble the human body. In general, humanoid robots
have a head, two arms, and two legs, though some forms of humanoid robots may model only part
of the body, for example, from the waist up. Some humanoid robots also have heads designed to
replicate human facial features such as eyes and mouth.
Currently humanoid robots are used as research tools in several scientific areas. Researchers study
the human body structure and behavior (biomechanics) to build humanoid robots. On the other
side, the attempt to simulate the human body leads to a better understanding of it. Human cognition
is a field of study which is focused on how humans learn from sensory information in order to
acquire perceptual and motor skills. This knowledge is used to develop computational models of
human behavior and it has been improving over time.
Although the initial aim of humanoid robot is to build better orthosis and prosthesis for human
beings, knowledge has been transferred between both disciplines. A few examples are powered
leg prosthesis for neuromuscular impaired, ankle-foot orthosis, biological realistic leg prosthesis
and forearm prosthesis.
Besides the research, humanoid robots are being developed to perform human tasks like personal
assistance, through which they should be able to assist the sick and elderly, and dirty or dangerous
jobs. Humanoids are also suitable for some procedurally-based vocations, such as reception-desk
administrators and automotive manufacturing line workers. In essence, since they can use tools
and operate equipment and vehicles designed for the human form, humanoids could theoretically
perform any task a human being can, so long as they have the proper software. However, the
complexity of doing so is immense.

Fig 1.1 Humanoid robot

CHAPTER 2
LITERATURE SURVEY
Biological Approximation
Since legged robots are inspired in animals observed in nature, a frequent approach for
their design and construction is to develop a mechatronic mimic of the animal that is intended to
replicate, either in terms of its physical dimensions, or in terms of characteristics such as the gait
and the actuation of the limbs. With this objective in mind, detailed studies of the locomotion and
anatomy of the animals have been made. Works joining researchers from the robotics and the
biology areas are often presented. Several examples of robots that have been developed based
on this approximation are discussed in Silva and Machado (2007), for example, the Lobster
Robot, that intends to be a lobster mimic (Ayers, 2004), the CWRU Robot II (Espenschied, et al.,
1996) that represents a stick-insect and the CWRU Robot III (Nelson, et al., 1997; Nelson and
Quinn, 1998) that intends to mimic (17:1 scale) the Blaberus Discoidalis cockroach.
This approach is also followed in the development of biped and humanoid robots. The designers
of these systems get much of their inspiration from mankind, as proved by several machines
with characteristics similar to those of humans, namely in the number of DOF and in their
dimensions.
Among the large number of examples adopting this approach one can mention the following
robots:
 The WABIAN humanoid, whose size and joint range of motion is based on an adult
human(Yamaguchi and Takanishi,1998), as can be seen in Figure 2, left;
 The biped developed by Caldwell, et al. (1997) to test the actuation using artificial pneumatic
muscles, that presents anthropomorphic dimensions;
 The BIP robot that presents the kinematic and dynamic parameters close to the anthropomorphic
values of an human, with 1.70 m height and 90 kg mass (Espiau, et al., 1997);
 The Honda Humanoid Robot model P2 that, on an initially phase of development, presented
the dimensions, joint locations, ranges of motion and center of gravity equivalent to the human
leg (Hirai, et al., 1998). Latter, it was verified that was difficult to satisfy all the conditions, and
some simplifications were made.

Mechanical View
The approaches to the systems design discussed in the two previous sections are inspired
in the strategies found in nature. However, it is important to keep in mind that legged robots are
machines. Therefore, the first aspect to consider in their design phase should be the adequate
implementation m the mechanical and physical viewpoints. In this line of thought, Habumuremyi and
Doroftei (2001) compiled the characteristics of several structures that can be adopted for the legs
of artificial locomotion systems. Hirose and Arikawa (2000) examined several concepts to be
adopted during the design of legged vehicles. The technique of actuator gravitational decoupling
was adopted in several robots and can be implemented not only during the system design, but also
in the posture during locomotion (Hirose and Arikawa, 2000).
In some cases, for designing a robot, empirical knowledge of mechanics and physics is
supported as an adopted approach. The design of the equipment’s has the objective of minimizing
some situation penalizing the performance of the robot under consideration (Hirose, et al., 1997;
Yamaguchi and Takanishi, 1998).
Another method for the optimization of the robot structure based on biology research
(Alexander, 1990), considers legs equipped with actuators introducing joint compliance. In this
way, it is possible to store and to release the kinetic and the potential energies of the robot legs and
body, during the different phases of the locomotion cycle. Raby and Orin (1999) make use of this
approach with a passive hexapod robot.
Humanoid robot Interaction
The current section describes the robot research and how the latest generation of robots
supports these characteristics. Research into human-robot interaction, the use of robots as tools,
robots as guides and assistants, as well as the progress being made in the development of humanoid
robots.
The simplest way robots can be used is as tools to aid in the completion of physical tasks.
Although there are many examples of robots used in this manner, a few examples are given that
benefit from human-robot interaction. For example, to increase the success rate of harvesting, a
human-robot collaborative system was implemented for testing by (Bechar and Edan 2003).
Results indicated that a human operator working with a robotic system with varying levels of

autonomy resulted in improved harvesting of melons. Depending on the complexity of the
harvesting environment, varying the level of autonomy of the robotic harvester increased positive
detection rates in the amount of 4.5% – 7% from the human operator alone and as much as 20%
compared to autonomous robot detection alone.
Human-robot teams are used in Urban Search and Rescue (USAR). Robots are
teleoperated and used mainly as tools to search for survivors. Studies completed on human-robot
interaction for USAR reveal that the lack of situational awareness has a negative effect on
performance (Murphy 2004), (Yanco, Drury et al. 2004). The use of an overhead camera and
automatic mapping techniques improve situational awareness and reduce the number of
navigational errors (Scholtz 2002; Scholtz, Antonishek et al. 2005). USAR is conducted in
uncontrolled, hazardous environments with adverse ambient conditions that affect the quality of
sensor and video data. Studies show that varying the level of robot autonomy and combining data
from multiple sensors, thus using the best sensors for the given situation, increases the success rate
of identifying survivors (Nourbakhsh, Sycara et al. 2005). Ohba et al. (Ohba, Kawabata et al. 1999)
developed a system where multiple operators in different locations control the collision free
coordination of multiple robots

CHAPTER 3
METHODOLOGY
Humanoid robot will works on commands given by the user either it is voice commands or touch
commands from the application designed to send some ASCII values through the CAN protocol
and the robot is coded accordingly such that with that ASCII commands it will do certain things
like 1.Wishing 2.Guiding Visitors 3.Breifing information and we can customize the code to do any
other steps
Initially the processor is set into active receiving mode and it will wake with commands and do
the task accordingly and it sends the data to the microcontroller. In the microcontroller the received
value is compared with all the values in the task codes. If the value matches with the static value
in the code it will perform the task which was coded under that value subset
It involves in 4 steps
1. Transition of the value
2. Receiving the value by the serial communication
3. Comparing the values with the static values in the code
4. If matches, do the task accordingly
All the parallel processes are done in the processor section and internet can be accessed by this
robot using this processor.
A large body of work in the field of human-robot interaction has looked at how humans and robots
may better collaborate. The primary social cue for humans while collaborating is the shared
perception of an activity, to this end researchers have investigated anticipatory robot control
through various methods including: monitoring the behaviours of human partners using eye
tracking, making inferences about human task intent, and proactive action on the part of the robot.
The studies revealed that the anticipatory control helped users perform tasks faster than with
reactive control alone.
A common approach to program social cues into robots is to first study human-human behaviours
and then transfer the learning. For example, coordination mechanisms in human-robot
collaboration are based on work in neuroscience which examined how to enable joint action in
human-human configuration by studying perception and action in a social context rather than in

isolation. These studies have revealed that maintaining a shared representation of the task is crucial
for accomplishing tasks in groups. For example, the authors have examined the task of driving
together by separating responsibilities of acceleration and braking i.e., one person is responsible
for accelerating and the other for braking, the study revealed that pairs reached the same level of
performance as individuals only when they received feedback about the timing of each other's
actions.
Fig 3.1 Humanoid robot testing

CHAPTER 4
BLOCK DIAGRAM
Fig 4.1 Block Diagram of Interactive Humanoid Robot
4.1 EXPECTED OUTCOME
 This robot will be able to share basic information about the institution
 Welcome the visitors by gestures
 Helps visitors in navigation of the campus
 Capturing the images with the help of camera
POWER SUPPLY
ACTUATORS
MOTOR DRIVERS
MICRO
PROCESSOR UNIT
(RASPBERRY PI)
SENSORS MOTORS
DISPLAY
MICRO
CONTROLLER UNIT
CAMERA MODULE
MICROPHONE
MODULE
SPEAKER
MODULE

CHAPTER 5
SYSTEM REQUIREMENT AND BUDGET ESTIMATION
5.1 Software Requirements
 Raspbian
 Python
 Arduiono IDE
 Arduberry
SL NO COMPONENTS ESTIMATION COST
1 Raspberry Pi Microcontroller Rs.2,715
2 LCD Display Rs.3,000
3 Camera Rs.8,500
4 Microphone Rs.6000
5 Speaker Rs.7,000
6 Gyroscope Rs.2,500
7 Accelerometer Rs.500
8 Arduino Mega Rs.360
9 Drivers Rs.1,000
10 Actuators Rs.3,000
11 Android Processor Rs.12,000
12 DC Motors Rs.1,000
13 Servo Motors Rs.1,000
14 IR Sensors Rs.1,200
Total Rs.49,775

CHAPTER 6
ACTION PLAN
0
20
40
60
80
100
120
Week 2
Series1
0
10
20
30
40
50
60
70
80
90
Week 1
Series1

0
20
40
60
80
100
120
Week 3
Series1
0
20
40
60
80
100
120
To Date
Series1

CHAPTER 7
CONCLUSION
Humanoid robot can be involved in various physical dynamics by just changing its posture without
need for a different experimental platform. This promotes a unified approach to handling different
dynamics. Moreover, it motivates social interactions such as gestural communication or
cooperative tasks in the same context as the physical dynamics. This is essential for three-term
interaction, which aims at fusing physical and social interaction at fundamental levels, This whole
report gives the idea about block diagram, working, principle and budget estimation for project
design which will be implemented in phase 2.

CHAPTER 8
REFERENCES
[1] W. D. Smart, “Is a common middleware for robotics possible?” in Proceedings of the
IEEE/RSJ International Conference on Intelligent Robots and Systems Workshop on Measures
and Procedures for the Evaluation of Robot Architectures and Middleware (IROS '07), E.
Prassler, K. Nilsson, and A. Shakhimardanov, Eds., 2007.
[2] J. Kramer and M. Scheutz, “Development environments for autonomous mobile robots: a
survey,” Autonomous Robots, vol. 22, no. 2, pp. 101–132, 2007.
[3] N. Mohamed, J. Al-Jaroodi, and I. Jawhar, “Middleware for robotics: a survey,” in
Proceedings of the IEEE International Conference on Robotics, Automation and Mechatronics
(RAM '08), pp. 736–742, September 2008.
[4] N. Mohamed, J. Al-Jaroodi, and I. Jawhar, “A review of middleware for networked
robots,” International Journal of Computer Science and Network Security, vol. 9, no. 5, pp.
139–148, 2009.
[5] M. Namoshe, N. Tlale, C. Kumile, and G. Bright, “Open middleware for robotics,” in
Proceedings of the 15th International Conference on Mechatronics and Machine Vision in
Practice (M2VIP '08), pp. 189–194, Auckland, New Zealand, December 2008.
[6] D. Bakken, “Middleware,” in Encyclopedia of Distributed Computing, J. Urban and P.
Dasgupta, Eds., Kluwer Academic, Dodrecht, The Netherlands, 2001.

Robotics report

Recommended

Recommended

More Related Content

Similar to Robotics report

Similar to Robotics report (20)

Recently uploaded

Recently uploaded (20)

Robotics report