Swarm Intelligence for Logistics Controlling

International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056
Volume: 04 Issue: 03 | Mar -2017 www.irjet.net p-ISSN: 2395-0072
© 2017, IRJET | Impact Factor value: 5.181 | ISO 9001:2008 Certified Journal | Page 2361
SWARM INTELLIGENCE FOR LOGISTICS CONTROLLING
Sanket Nirmal1, Amit Pathare2
1 Assistant Professor, Department of Electronics & telecommunication, PRMITR, Badnera, Maharashtra, India
2 Assistant Professor, Department of Electronics & telecommunication, PRMITR, Badnera, Maharashtra, India
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Abstract - Swarm robotics technology is inspired by
behaviour of insects how they work collaboratively to
accomplish a task. Same concept we are using here to make
the logistic management in warehouse efficient. Methodology
involved is communication between the subordinates,
Communication between the swarm bots and the master
station having a central control over each bot, task allocation
to each individual and to find best possible way to complete
the task. They organize themselves according to priority of
task and each individual of swarm can take its own decision
with respect to the current status of other members to
complete the given task. This system consists of swarm of 'n'
robots that works in a centralized way to perform an allotted
task to the swarm. Hence each robot in our system will have a
trolley based lift and place mechanism. The robot will lift item
and take it to the required destination and also can arrange it
in required manner keeping the space constrains into
consideration. As there is no human interventioninoursystem
eventually the labour effort gets minimized. The wholesystem
leads to the minimization of error and hence increases the
reliability.
Key Words: Swarm Robots, Swarm intelligence,
Cooperative control, Task allocation, Arduino
1. INTRODUCTION
Swarm robotics is currently one of the most important
application areas for swarm intelligence. Swarms provide
the possibility of enhanced task performance,highreliability
(fault tolerance), low unit complexity and decreased cost
over traditional robotic systems. They can accomplish some
tasks that would be impossible for a single robot to achieve.
Swarm robots can be applied to many fields, such as flexible
manufacturing systems, space crafts,
inspection/maintenance, construction, agriculture and
medicine work. Swarm robotics is the study of how large
number of relatively simple physically embodied agents can
be designed suchthata desiredcollective behaviouremerges
from the local interactions among agents and between the
agents and the environment. It is a novel approach to the
coordination of large numbers of robots. It is inspired from
the observation of social insects’ ants, termites, wasps and
bees which stand as fascinating examples of how a large
number of simple individuals can interact to create
collectively intelligent systems. Robustness is the ability to
cope with the loss of individuals. In social animals,
robustness is promoted by redundancy and the absence of a
leader. Scalability is the abilitytoperform well withdifferent
group sizes.
The introduction or removal of individuals doesnotresult in
a drastic change of the performance of a swarm. In social
animals, scalability is promoted by local sensing and
communication. Flexibility is the ability to copewitha broad
spectrum of different environments and tasks. In social
animals, flexibility is promoted by redundancy, simplicity of
the behaviours and mechanisms such as task allocation. To
explain how we can benefit from the properties of swarm
robotics systems that make them appealing in several
potential application domains. Swarm robotics have been
involved in many tasks such as the ones demanding
miniaturization, like distributed sensing tasks in micro-
machinery or the human body; those demanding cheap
designs, such as mining task or agricultural foraging task;
those requiring large space and timecost,andaredangerous
to the human being or the robots themselves, such as post-
disaster relief, target searching, military applications, etc.
Hence the Swarm Intelligencetechnologycanbethe eminent
change in the conventional methods of the executing tasks.
2. PROBLEM STATEMENT
Logistics & warehouse management is one of the important
process of the industrial flow control. Up till now the goods
transport was done manually. The whole process faces
problems of:
1. The accuracy of whole process is not, as required that is
the goods item may get misplaced.
2. The major issue is of time & efficiency required in the
process
3. Cost and the manpower behind process is comparatively
high.
4. Possibility of damage is greater due to human error.
5. Technical failure in process may cause setbacks.
6. The logistical concept for future operations, domestic or
international, needs to be able to
Support the modular based force concept “from factory to
foxhole”.
3. LITERATURE REVIEW
Researches in this area of swarm roboticshavedraftedthree
types object manipulation method which are namely
grasping, pushing and caging. In grasping, all robots are
arranged so that the total robots system is grasping the

object (Wang et al., 2007; Agassounon, 2004). Grasping
incorporates form closure (refer to Fig.1 (b)) and force
closure (refer to Fig.1 (a)) techniques. Force closure is a
condition that implies that the grasp can resist any external
force applied to the object. Form closure can be viewed as
the condition guaranteeing force closure, without requiring
the contacts to be frictional. In general, robots aretheagents
that induce contacts with the object, and are the only source
of grasp forces. Pushing (Miyata et al., 1997;Yamada &Saito,
2001) on the other hand doesn’t guarantee form closure or
force closure, but requires external forces to be applied to
the object such as gravity and friction. For this type of object
manipulation, conditional closure (refer to Fig.1(c)) is
introduced. Pushing behaviours gives an advantage where
any objects that can’t be graspedto be movedandtoperform
pushing to multiple objects as well.
The main difficulty on object manipulation via pushing is
that the robots cannot pull the object directly when it needs
to slow down or move back the object. Caging (Pereira et al.,
2003; Wang & Kumar, 2002; Wang et al., 2004) introduces a
bounded movable area for the object. Then, the contact
between object and robotics mechanism need not be
maintained by robot’s control. This makes motion planning
and control of each robotic mechanism become simple and
robust. This condition is called object closure (refer to Fig.1
(d)). Caging has been widely used in manipulation of swarm
robotics because this makes motion planning and control of
each robotic mechanism simple and robust.
A leader-follower type multiple robot systemwasaddressed
by Wang et al. (2007) where the proposedsystemconsistsof
a pushing leader, a robot without grasping mechanisms,and
multiple follower robots.
During the object transportation, a desired trajectory is
given to the leader robot only, and follower robots estimate
the trajectory of the leader based on force/momentfrom the
object. In Behaviour-based Multiple Robot SystemwithHost
for Object Manipulation (BeRoSH) (Wang et al., 1996), the
unit which processes all common tasks is named the host.
The host is incorporated into one of the robots, by giving the
robot the ability to organize other robots and generate
motivations/goals for the other robots. More papers
reporting leader-follower implementations can be found in
(GroB et al., 2006; Song & Kumar, 2002).
4. PRAPOSED METHODOLOGY
In the SR system the ‘n’ automatic smart robots which can
take it on decision assistingcoordinationinmulti-botsystem
to complete a task. In our system each bot work on the basis
of RPS technology with continuous feedback of eachrobot in
swarm. Based on position of each robot in its surrounding,
status, etc. It will calculate the best possible way to
accomplish the task. Again for organizationofloadinstorage
area the basic algorithm according to the arrangement will
be assigned to swarm by the monitoring system which
consist of vision based and positioning based system. Each
robot will act as a server for the monitoring system. Key
technologies used are as follows
1. Separation: Each robot needs to maintain proper spacing
between each other. Differenttypesofproximitysensors and
SONAR sensor are used to keep intact robots in its
surrounding.
2. Wireless communication system: Communication in the
system is done with the help of ZigBee module, RF module.
3. Mechanical design: The mechanical components used in
each bot is hydraulic system used for lift and place
mechanism. Other simple wheel based systemisusedforthe
movement of robot.
4. Positioning and tracking of robots: The positioning and
tracking of each individual in the swarm system can be done
by simple motion analysing method with the help of IR
sensors, attached to the wheel.
Fig. 4.1 SR SYSTEM
As shown in figure the system has a master station and the
swarm of different robots which are directly or indirectly
controlled by the station for tracking, signal for loading
unloading, etc. The master station gives the command to the
swarm bot For continuous tracking and updating the status
of each bot. The basic principle of swarming is very simple:
by having a relatively large number of agents following very
simple rules, complicated group-behaviours emerge. One of
the key features of swarming is that it may not be possible to
understand the emerging global behaviour by analysing
these simple rules. The only way to predict the behaviour of
a complicated agent system may be to simulate it. After
analysing many such simulation, it might be possible to
extract “rules” governing the aggregate behaviour of the
system. In some cases, it might even be possible to relate
these to the microscopic rules followed by the agents. In
other cases, however, the microscopic rules may be
completely counter-intuitive and seem to destroy rather
than create the desired global behaviour: “doing wrong
locally might be right globally”. Such systems havea number
of desirable features. They are robust, flexible and self-
organizing. Robust since not all individual ants needtosolve
the problem. Flexible, since they can adapt in real time to
changing conditions. The self-organizing properties of
swarming are important since they mean that there is no
central command and control post that decides what the
agents should do. This reduces the vulnerability of the

system. Swarming can be seen as one kind of self-organizing
system. To give a taste of how swarming works, consider the
following game.
Take a large number of people and randomly assign a
protector and an attacker to each person. Tell themthatthey
must move around so that their protector is between them
and their attacker. How will the crowd move? Since one
person’s attacker might be another one’s PRMIT & R 4
Protector, the motion of the crowd will be random. Consider
the difficulty faced by an observer who enters the room
while the crowd moves around and tries to discern the rules
governing it. Contrast this to the situation that arises when
the rule is changed in a very simple way: each persontries to
move so that they are in between their attacker and
protector. Now, everybody will try to move to the centre of
the crowd.
The system has two main components viz.
1. Swarm bot
2. Monitoring station
Fig. 4.2 Robot Mechanism
As shown in the figure each robot has a simplemechanismof
lift and place which is able to pick and drop the load a source
to a desired location. Each robot will be able to avoid the
clusters coming in its vicinity and take the load to the
desired destination. An infrared sensor is attached to the
wheel of each robot so that the corresponding motion of the
wheel of each robot will result in the change in the motion
from the desired direction. If the wheel goes forward the IR
sensor will count the no. of bits assigned to the motion, for
the change in direction the difference between the motions
of two wheels will result in the proper change in direction.
The robot will continuously be in connected with themaster
station so that it can update its current status on the master
station. According to the priority, the master station will
assign the proper task to each of the robot and maintain its
service. Another important factor of each bot is interfacing
the proximity sensors as it has to avoidthecollisionbetween
its subordinates. Then the role of communication between
the bots and master station comes.
5. Block Diagram & Hardware Implementation
Fig. 5.1 Block Diagram
The communication is only one directional since the bots
only arrange and perform the allotted task as per the
instructions by monitoring station.
Fig.5.2 Communication Process
Now the communicationbetweenthemonitoringstation and
the swarm bot is done through the ZigBee communication
module. There is a ZigBee Trans- receiver connected to both
bot as well as master station for theeffectivecommunication
between the bot and the monitoring station.
6. Required Hardware
6.1 SENSORS AND TRANSDUCERS USED
IR Sensors work by using a specific light sensor to detect a
select light wavelength in the Infra-Red (IR) spectrum

Fig. 6.1 IR Sensors
By using an LED which produces light at the same
wavelength as what the sensor is looking for, you canlook at
the intensity of the received light. When an object is close to
the sensor, the light from the LED bounces off the object and
into the light sensor. This results in a large jump in the
intensity, which we already know can be detected.
6.2 SONAR SENSOR
Fig .6.2 Sonar Sensor
Ultrasonic transducers are transducers that convert
ultrasound waves to electrical signals or vice versa. Those
that both transmit and receive may also be called ultrasound
transceivers; many ultrasoundsensorsbesidesbeingsensors
are indeed transceivers because they can both sense and
transmit. These devices work on a principle similar to that of
transducers used in radarand sonar systems,whichevaluate
attributes of a target by interpreting the echoesfromradioor
soundwaves,respectively.Activeultrasonicsensorsgenerate
high-frequency sound waves and evaluate the echo which is
received back by the sensor, measuring the time interval.
6.3 ARDUINO(IC Atmega32):
Arduino is an open-source platform used for building
electronics projects. Arduino consists of both a physical
programmable circuit board (often referred to as a
microcontroller) and a piece of software, or IDE (Integrated
Development Environment) that runs on your computer,
used to write and upload computer code to the physical
board. The Arduino platform has become quite popular with
people just starting out withelectronics,andforgoodreason.
Unlike most previous programmable circuit boards, the
Arduino does not need a separate piece of hardware(calleda
programmer) in order to load new codeonto the board –you
can simply use a USB cable. Additionally, the Arduino IDE
uses a simplified version of C++, making it easier to learn to
program
Finally, Arduino provides a standard form factor that breaks
out the functions of the micro-controller into a more
accessible package. Hence in this way we can implement the
swarm robotics technology in simple way to perform the
complex task
7. Applications of Swarm & Future Scope
Several potential proposals ofswarmroboticswhicharevery
suitable are described below.
1. Tasks which cover large area
2. Tasks dangerous to robot
3. Tasks which require scaling population
4. Tasks which require redundancy
5. Post-disaster relief operations
6. Target searching
7. Military application
7.1 FUTURE SCOPE
Swarms of robots performing together to carry out trades
could providenew chances for humans to connect the power
of machines. The ability tocontrol robot swarmscouldprove
tremendously beneficial in a range of contexts, from military
to medical. The robots can also group themselves together
into a single cluster after being dispersed across a room, and
shape themselves by order of priority. On a larger scale, they
could play a part in military, or search and rescueoperations,
acting together in areas where it would be too dangerous or
unrealistic for humans to go. In industry too, robot swarms
could be put to use, improving manufacturing processes and
workplace safety. The bionic aero vehicles inspired from
swarm intelligence technology will become applicable in a
few years. It can be foreseen that machine bees or
cockroaches with inspection equipment and missiles will
possibly show up in future war.
3. CONCLUSIONS
Using robots in real applications such as space exploration
and search-and-rescue is quite interesting for researchers.

These operations require high level of robustness and
adaptation. One way to increase the robustness is
constructing a distributed system, in this case using multi-
robot with distributed control. The benefit of using
distributed system is having less dependencytoa failure ofa
particular part of the whole system. Another important
feature of SAR robots is versatility. During a mission robot
would face to unpredicted situations and it should be able to
manage that situation. One approach to have versatility and
adaptation is self-reconfigurablerobots.Thisfeatureenables
the robot to change itsstructuredependontheenvironment.
Swarm robotics is a new approach for SAR. In this approach
each robot is an autonomous agent with somecapabilityand
sensors. Individual robots are capable to autonomously and
then collaborate with other robots to domorecomplex tasks
such as moving over a hole, transporting object, etc. Swarm-
Bot opens up a new research field. The system built here is
capable of performing the complex task of logistic
management in a easier way. The distribution of the task
resulted in dividing the work and finallyachievingtheresult.
REFERENCES
[1] Yogeswaran, M., Ponnambalam, S.: Swarm Robotics: An
Extensive Research Review. Advanced Knowledge
Application in Practice, Igor Fuerstner (Ed.) (2010).
[2] Applications and Prototype for System of Systems
Swarm Robotics(Matthew A.Joordens, Member IEEE,
Ted Shaneyfelt, Student member IEEE, Kranthimanoj
Nagothu, Srujana Eega, Aldo Jaimes and Mo Jamshidi,)
[3] Mamta Gupta 1, Devika, Saxena , Sugandha Kumari,
Dawinder Kaur ISSUES AND APPLICATIONSOF SWARM
ROBOTICS International Journal of Research in
Engineering, TechnologyandScience,VolumeVI,Special
Issue, July 2016
[4] G. Dudek, E. Jenkin, D. Wilkes, “A taxonomy for swarm
robots”, In Proc. 1993 IEEE International Conference
on Intelligent Robots and Systems, pp 441–447, 1993.
BIOGRAPHIES
Sanket Nirmal iscurrentlyworking
as an assistant professor at
PRMITR, Badnera and he is having
an experience of 5 years in the
field of Electronics & Telecomm.
Engg. He has done his UG from
YCCE & PG from JNTU.
Amit Pathare is currently working
as an assistant professor at
PRMITR, Badnera and he is having
an experience of 4 years in the
field of Electronics & Telecomm.
Engg. He has done his UG from
PRMITR & PG from COEP, Pune.

Swarm Intelligence for Logistics Controlling

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