University Institute of Engineering
Mechatronics Engineering
Automated Guided Vehicle
project part 2 (20MTR-689)
Under the Guidance of
Dr. Gurmeet Singh
(Associate Professor)
DISCOVER . LEARN .
EMPOWER
Contents
Introduction
Application
Literature Review
Research objective
Methodology
Conclusion
References
Introduction
Automated Guided Vehicle (AGV)- AGVs are
self driven/controlled/propelled vehicles.
Introduced by U.S.A in early 1945 (Barrett
electronic corporation, Illinios).
Europe is largest market (revolution).
In early time, parcel company has to deliver at
desired time (efficient way).
AGV
Reasons to implement
•
•
•
•
•
•
Cheap in terms of cost.
Reduce accident (safety).
Time saving (efficient).
Eliminate human error (precise and accurate).
Centrally controlled
Robust in use
Applications
•
•
•
•
•
•
•
Material handling system (30-80% costs).
AGVs personal vehicles.
Robots in homes and many places.
In medical sectors (covid pandemic).
Assembly systems
Pick and place
AS/RS (automated storage and retrieval
system)
Literature Review
Sl.no
Author
Name
(year)
Title of
paper
Objective Methodol Conclusio
ogy
n
1
Matthias
De Ryck
2020
Automate
d Guided
Vehicle
Systems,
State-OfThe-Art
Control
Algorithms
and
Technique
s
To study
Automate
d Guided
Vehicle
and
paradigm
to shift of
industry 4.
Data
collection,
path
control
study,
taxonomy
study, etc
Industry 4
paradigm
will push
AGV
manufactu
rer to
think
about
decentraliz
ation.
Literature Review
Sl.no
Author
Name
(year)
Title of
paper
Objective Methodol Conclusio
ogy
n
2
Zhixiong
Ning1
2020
Vehicle
pose
estimation
algorithm
for parking
automated
guided
vehicle
To study
the
efficient
use of
AGVs in
automatic
parking
Research
on cell
based
method,
ground
segmentati
on, pose
estimation
on wheel
symmetry,
etc
vehicle
pose
estimation
method
is feasible
and it has
a high
precision
results.
Literature Review
Sl.no
Author
Name
(year)
Title of
paper
Objective Methodol Conclusio
ogy
n
3
HeeWoon
Cheong
(2018)
Concept
design of
AGV based
on image
detection
and
positioning
To focus
on
automated
driving
(AGV)
based on
image
detection
and
positioning
real time
image
capturing
camera
(L.C), deep
learning
algorithm
with small
image, etc.
Image
sensing
based
AGV with
positioning
is
successivel
y
developed
and
implement
ed, but
high
infrastruct
ure cost.
Objectives
• To study Automated Guided Vehicle (AGVs).
• To implement on Indian industries.
• To focus on India to be ready for Industry 4.0.
Statistical research data
Industrial robot installation report
• 2019 [ China (1st) 140000, Japan (2nd)
49900,….India (10th) 4300
Countries with robot densities [per 10000
employees]
• South Korea (1st) 631, Singapore (2nd) 488,….
India (15th) 3.
Statistical research data
Indian industries
• In 2019, $121.1 million and estimated $364.3
million by 2027.
• Projected growth rate of 14.4% from 2020 to
2027.
• Flipkart (350 AI-powered bots AGV), 4500
shipment per hour at twice speed accuracy.
Statistical estimated data
India position
 According to Indian Brand Equity Foundation
(IBEF), to contribute manufacturing output to
25% of GDP in 5 years, currently 16 %.
 Iot, India to capture 20 % share in next five
years.
Methodology
Path selection methods/modes
• Guidance path system
• Behavior navigation system (unstructured)
• Vision based system (latest)
Central processing system controlled
Industry 4.0- (Germany)- Artificial intelligence
(AI), Internet of things (Iot), machine-tomachine communication, quick smart decision
Parts of AGVs
Task allocation for
AGVs
•Traction motor (move-as
per requirement)
•Task allocation
•Batteries
•Navigation
•Industrial PC
•Path planning
•Sensor
•Motion planning
•Payload interface (fork,
conveyor, etc)
•Vehicle management
Methodology
India position
 According to Indian Brand Equity Foundation
(IBEF), to contribute manufacturing output to
25% of GDP, currently 16 % .
 Iot, India to capture 20 % share in next five
years.
Methodology
Task allocation for AGVs
• Task allocation
• Navigation
• Path planning
• Motion planning
• Vehicle management
Advantage and Disadvantage
 Cheap in operation if
implemented in mass.
 Reduced labor cost,
ensures safety.
 Results in high
productivity with
accuracy.
 Overall low cost leads
us to stand in
competitive world.
 Very High initial
investment and
maintenance cost.
 Cannot work without
power, Leads to
unemployment as seen.
 Not suitable for nonrepeated tasks.
 Less flexibility of
operations.
Conclusion
• AGVs are the most common tools now in
industries due to its inherent capabilities.
• Indian industries are in growing stage, little or
few AGVs are working, if in mass introduction
of it, then machines will be smart.
• AGVs save costs and increase efficiency.
• It can be implemented in almost everywhere
with few small challenges.
• To be ready for Industry 4.0, AGVs will help to
overcome and compete with others.
References
1.
2.
3.
4.
5.
De Ryck, M., Versteyhe, M. and Debrouwere, F., 2020. Automated guided
vehicle systems, state-of-the-art control algorithms and
techniques. Journal of Manufacturing Systems, 54, pp.152-173.
Fransen, K.J.C., van Eekelen, J.A.W.M., Pogromsky, A., Boon, M.A.A. and
Adan, I.J.B.F., 2020. A dynamic path planning approach for dense, large,
grid-based automated guided vehicle systems. Computers & Operations
Research, 123, p.105046.
Ning, Z., Wang, X., Wang, J. and Wen, H., 2020. Vehicle pose estimation
algorithm for parking automated guided vehicle. International Journal of
Advanced Robotic Systems, 17(1), p.1729881419891335.
Nagarathinam, D., Current Status about Automated Guided Vehicle and
Their Advantages and Application.
Velmurugan, S., 2020. Guided Vehicle Navigation for Warehouse
Applications.
6.
7.
8.
Das, S.K. and Pasan, M.K., 2016. Design and methodology of
automated guided vehicle-a review. IOSR Journal of Mechanical
and Civil Engineering (IOSR-JMCE), pp.29-35.
Cheong, H.W. and Lee, H., 2018. Concept design of AGV
(automated guided vehicle) based on image detection and
positioning. Procedia computer science, 139, pp.104-107.
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Thank you