fyp presentation of group 43011 final.pptx

INSTITUTE OF INDUSTRIAL ELECTRONICS
ENGINEERING
FINAL YEAR PROJECT PRESENTATION
Muhammad Hammad khan (18021)
Syed Mazhar Hussain Rizvi (18043)
Syed Murtaza Hussain (18045)
Arsal Abbasi (17008)
1
PROJECT NAME
Localization and 3D Mapping for Indoor Environment
PROJECT SUPERVISOR
Engr Asif Ahmed Memon
PROJECT CO-SUPERVISOR
Engr Agha Mohammad Shakir

Presentation Overview
 Introduction
 Problem Statement
 Possible Solutions
 Proposed Solution
 Objectives
 Literature Review
 Methodology
 1. System Model
 2. Detail of the Hardware and Software
 3. System Analysis and Specifications
 Results and Discussion
 1. Simulation Results
 2. Experimental Results
 3. Comparison between Simulation and Experimental Results
 Conclusion and Recommendations
 References 2

Introduction
 The importance of robotics is rapidly increasing as reflected by the number of available
robotic systems present in industrial, commercial, educational and research facilities.
 During the last 50 years, robotics research has been aimed at finding solutions to the
technical issues raised in multiple domains of human society. The evolution of
sophisticated robotic solutions has been witnessed all around the global communities.
3
Robot in Industry
[www.azorobotics.com]
Robot in warehouse
[www.ehstoday.com]
Robot in Healthcare
[www.nobel-project.eu/]
Robot in Education
[www.slashgear.com]

Introduction
 The earlier developments of robotic systems have been solely emerged for
industrial robotic solutions.
 A research article “A Brief History of Industrial Robotics in the 20th Century”,
published in August 2019 states that the word robot would be assigned to a
system that performs physical tasks automatically with some intelligence.
 The article described three generations of industrial robots till the year 1999
when this field got saturated.
 The First Generation of Industrial Robots (1950-1967).
 The Second Generation of Industrial Robots (1968-1977).
 The Third Generation of Industrial Robots (1978-1999).
4

Introduction to Surveying and Mapping
Robots
 Exploring unknown environment and to build its 3D representation is one of the
most focused multi-disciplinary research field which has been evolved through
the usage of Simultaneous Localization and Mapping (SLAM) technique.
 Surveying and mapping the environment is one of the recent topic for the
robotic researchers and started to evolve since last decade.
 There are different varieties of mapping robots available which can do the
surveying job in indoor and outdoor environments.
 An indoor surveying robot may be developed by using a laser scanner and
odometry setup supported by a single board computer.
 But on the other hand, an outdoor surveying robot becomes a complex setup of
sensors supported by a high-speed computer.
5

Surveying and Mapping Robots
6

Problem Statement
 In recent years researchers developed several solutions for simultaneous
localization and mapping (SLAM), however, 3D real-time map development
and scanning of a large area is still a big challenge and requires autonomy of
the system by involving multiple robotic units.
 Increasing the number of robotic units for large area mapping creates several
challenges, like the power consumption, data transfer and the determination
of the exact lidars transformation and exact joint together them for real-time
3D mapping.
 Therefore over all system exceeds the acceptable cost with high power
consumption solution for 3D surveying and real-time mapping.
7

POSSIBLE SOLUTIONS
 We can 3d laser scanners like velodyne .Velodyne is approx 2,200$.
 We can also use SICK-TIM510 but the issue is they are very high cost.
SICK-TIM510 is approx. 1,800$.
 The other one solution is the usage of 2D RP-Lidar A1 for low cost 3D
mapping.
8

POSSIBLE SOLUTIONS
10
 The one another solution is to make the servo motor stand which
rotates the 2D lidar on x-y and z axis through this we can capture 3D
map of the whole environment.

PROPOSED SOLUTION
 Our proposed solution is meant to design a “SLAM BASED 3D MAP BUILDING
USING 2 LOW COST 2D LASER SCANNERS (RPLIDAR A1)”and perform motion in
real-time from the initial position to the final destination (surveyed region).
 Main theme of “SLAM BASED 3D MAP BUILDING USING 2 LOW COST 2D LASER
SCANNERS (RPLIDAR A1)” is an orthogonal combination of two RP-Lidar 2D
laser scanners which we will used on slam’s vehicle to build real-time 3D point
cloud map of the explored region.
 The interfacing of scanners, transformation joints, zero degree transformation
and the processing of simultaneous localization and mapping (SLAM)
technique will achieve using Robot Operating System (ROS).
11

PROPOSED SOLUTION
 The developed 3D point cloud map will further utilize to establish
Building Information Model (BIM) to found validity for the surveyed
region.
12
Simulated model Real model

Objectives
 The main objective is to make the real-time 3D Map development of the
corridor using ROS.
 The existing solution are costly and not economically feasible to the
local market of the country.
 Therefore, the main motivation of our project is to develop an
economical autonomous mapping solution acceptable to the local
market.
13

Objectives
 To accomplish the desired project goals the overall work has been
divided into multiple objectives as follows:
 Fabrication of small mapping rover.
 Characterizing and selection of 2D scanners.
 Simulated and Real robot transformation Lidar’s joints, plugin and it’s
transformations on real-time bases.
 Real-Time Map development of the environment by rover.
14

A Rover Team Based 3D Map Building Using Low Cost
2D Laser Scanners
 This paper presents a solution to develop 3D map of indoor place using
a team of rovers equipped with low cost 2D laser scanners. They used
uwb 1000 for sensing 2nd rover another thing they used identity marks
on both rover and read them of 1st rover to 2nd and 2nd rover to 1st . Both
rovers make the map and stop at meeting point by reading identity
mark. Researchers get the lidars data of both rovers wirelessly.
 Then the researchers process data offline in MATLAB for 3d map
merging using some equations. The rover equipped with the on board
computer(raspberry pi) ,2 lidars, uwb1000.
 The results of research is given in below slide.
15

A Rover Team Based 3D Map Building Using Low Cost
2D Laser Scanners
16

Ground Robot Mapping Infrastructure
 Ground Robot Mapping Infrastructure GRoMI is
composed of two major parts, a hybrid laser scanning
system and an autonomous mobile robot platform
 The upper laser scanning system part, which is for
collecting 3D mapping information, consists of
 Five SICK 2D laser scanners
 A built-in digital single-lens reﬂex (DSLR) camera
 The lower mobile robot part, which is for collecting
localization data, has
 four wheels with encoders,
 object avoidance sensors,
 an Inertial Measurement Unit (IMU),
 and a navigation camera
17

(a) raw scan data from
LiDAR
(b) incrementally-built 2D
map of the environment
(c) final recovered trajectory with
position and orientation of robot
18

• Once the robot ﬁnds the best static scan position,
• it calculates the coordinate transformation from the previous static scan position to the current
position using SLAM localization data
• and then moves to a next static scan position.
• Once the scanning process is completed at the last scan position,
• the ﬁnal registered point cloud is simultaneously generated.
• Figure shows the registered RGB-mapped point clouds for the test environment
19

Methodology
 Designing and Development of Rover Based 3D Scanning System.
 Simulated and Real robot transformation Lidar’s joints, plugin and it’s
transformations on real-time bases.
 Check visualization in Rviz (the debugging tool of ROS).
 Check tf-tree broadcasting to check data is publishing and subscribing
correctly.
 Lidar zero-degree transformation.
 Implementation of customize real-time 3d map development package on
ROS. Its name is IRA laser tools.
 Rover Instrumentation and control.
 Real-Time 3D Map Development using Rover.
20

System Model
Designing and Development of Rover Based 3D Scanning System:
 The motive of our project is to scan the environment using two 2D scanners and develop
a 3D model of the scanned vicinity. The experimental setup is consisting of
 A rover, equipped with an appropriate control system and instrumentations as discussed later
 A communication system.
 Computer.
 We are using a vehicle its fabrication as discussed later.
 This vehicle were installed with a control system and sensors with support of additional
mechanical attachments.
 The communication system we are using is simple a Wifi network between our rover and
pc.
 Our pc which is a laptop is installed with Robot Operation System (ROS), and some
packages we required for data accusation and control.
21

The CAD model
 The CAD model of the experimental setup is
shown in Figure. The model is developed on
Autodesk Fusion 360, an online CAD model
development software. The model developed
was further used for simulation in the ROS
environment. The model is indicating the
desired connections of two orthogonal
RPLIDARs .
Rover model of Sim & Exp setup
22

Selection of Rover
 The rover we selected is
customize 4WD mobile platform
model.
 There are two sections where we
can mount our additional
hardware. These sections may
be called as lower section and
upper section
23

Modifications in Rover
 Additionally, for the support
of LIDARs, an acrylic stand
in orthogonal shape has
been designed and
fabricated. Two surfaces
have been developed on the
stand
Rover with support for RPLIDARs
24

Modifications in Rover
 We use the 1000 Rpm encoder motors to get the feedback from
encoder for correct odometry of the rover in the environment.
1000 Rpm 12V Dc gear
motor with encoder.
Odometry from encoders 25

Real Rover
Real Rover with using acrylic sheet
26

Software Details and Control
Simulated and Real Rover Transformation:
 To visualize the movement of the robot in Rviz we must have to do the robot
parts transformation for broadcasting and make joints for visualize the
movement of the rover.
27

TF-Tree and Topics Publishing by Frames:
 To check the transformation that broadcasting of the frames is perfect or not we make TF-
Tree of our rover.
28

Worlds Modeling Models for Indoors Environments:
 Occupancy Grid-based Map
 Feature Based Maps
 Topological Maps
 Point-Features Based Map
29

Occupancy Grid-based Map:
 In 1980, Moravec and Elfes introduced this type of map. They used a
sonar sensor for data collection from the environment, with a measuring
range of 0.9 to 35 feet
 The advantage of occupancy grid maps lies in the fact that they do not
rely on any predeﬁned features
 One of the major drawbacks of the occupancy grid map is the
consumption of memory
30

Two-dimensional Occupancy Grid used: (a) 2D laser scanner for mapping. (b) Fused sensor
data for mapping.
31

Implementation of IRA Laser
Tools (The Real Time) Package:
 IRA Laser Tools is a customize
package which we use here to
merge both (vertical and
horizontal) Lidar readings and
publish into a single point
cloud.
 It is used to hold the real
sample or reading which comes
from both Lidars to make 3D
Real time map of the whole
environment.
32

The working of Ira-laser tools is that is merge the both lidar (vertical and horizontal)
and produce single point cloud another is important think is that its transformation use
to update the the pose of lidar w.r.t odometry. Map to odom transformation is used to
update the map using odometry. If we don’t do this issue in visualization in Rviz.
33
Lidar’s Pose Update:

Hardware Details and Control
34
Rover Instrumentation and control:

Hardware Details and Control
35
Rover Connectivity and control:

SYSTEM ANALYSIS AND SPECIFICATIONS
Lidar Zero-Degree Transformation:
 The objective of lidar’s zero degree transformation is to reduce length
of lidar’s frame (reduction in the lidar’s frame, compact in size).
 Another objective is to increase the flexibility in lidar.
36

SYSTEM ANALYSIS AND SPECIFICATIONS
Performance Evaluation and Selection of 2D laser scanners:
 There are various 2D laser scanners available that have been designed to operate in
numerous environments and provide the benefit of non-contact sensing of the
surveyed region.
 Based on general features of scanners such as
 compactness
 interfacing
 cost
 Following three 2D laser scanners specifications are as follows:
 Hokuyo URG-04LX
 Hokuyo UTM-30LX
 RPLidar A1
37

Parameter URG-04LX RPLIDAR A1 UTM-30LX
Maximum measurement
range (m)
4 6 30
Measurement error
(mm)
±10mm up to 1m range;
1% of measurement
value for 1-4m range
±50 mm ±30mm for 0.1 to 10m
range, ±50mm for 10 to
30m range
Scanning angle (deg) 240 360 270
Angular resolution (deg) 0.36 ≤ 1 0.25
Scanning time
(ms/cycle)
100 180 25
SPECIFICATION OF 2D LASER SCANNERS
38

Results
Rover Based Localization and Mapping:
 we are using two RPLIDARs.
 One is for horizontal scanning
 and the other is for vertical scanning
 One LIDAR scanning horizontally is being used for 2D SLAM
 The 2D map has been developed using hector SLAM.
 There is no requirement for odometer data from wheels in Hector SLAM
 The package matches the current scan data with previous data and
estimates the value for u
 As a result, an occupancy grid map of the environment is generated, along
with the related pose of the rover
39

Results
Real-Time Point Cloud Generation:
 For taking the data and generation of
real-time point cloud an experiment
has been performed with a rover at the
3rd-floor corridor in the IIEE.
 It is clear that the environment has
different pillars and walls, and the path
is E-shape. The rover was controlled
through a wifi network using teleop
twist keyboard package.
40

Simulated Results
Simulated Map Generation:
 In Ros there are 2 tools which are widely use.
 Gazebo (a simulation plateform).
 Rviz (the debugging tool).
41

Simulated Results
2D Grid Map Generation:
 The data of both scanners,
were also transmitted using the
same network. The SLAM
package used a Horizontally
mounted scanner and
estimated the 2D map and
pose in the simulated corridor.
The result of these two values
is shown in Figure
 Red arrows shows the
odometry of the simulated
rover at every movement.
42

Simulated Results
Real-Time 3D PointCloud Generation:
 Real-Time point cloud generation of simulated corridor as shown in given video.
43

Simulated Results
44

Hardware Results
2D Grid Map Generation:
 Similarly in hardware data of both
scanners, were also transmitted
using the same network. The
SLAM package used a
Horizontally mounted scanner and
estimated the 2D map and pose in
the real corridor.
 In the given 2D grid map of the
corridor the is little bar of extra
scan shows that the room is open.
 Green line shows the trajectory of
the real rover which comes from
odometry.
45

Hardware Results
 Real-Time point cloud generation of real corridor as shown in given figures.
46

Hardware Results
47

Hardware Results
Comparison Between Simulation an Hardware Results:
48
Simulation :
 The total volume of the simulated
corridor developed by the rover is
27.7 x 2 x 3.2 in meters.
 in simulated 2D map there is no
bad scanning present.
 Simulated rover weight is about 1.5
KG so the linear and angular
motion of the motors are perfect
due to less load.
 The total operation completed by
the simulated rover is about 5 min.
Experimental:
 The total volume of the real corridor
developed by the rover is 27.37 x
1.92 x 3.04 in meters.
 in real 2D map there is some bad
scanning present at one place.
 Real rover weight is about 4.5 KG
so the linear and angular motion of
the motors are good but not perfect
due to enough load.
 The total operation completed by
the simulated rover is about 10
min.

Conclusion
 This project has presented the efficient working of a scanning and
mapping system comprising of a low cost rover.
 The working of the system provides ease of operation at affordable
rates.
 The successful Real-Time map development technique has been
utilized to show the use of rover for the surveying application of
comparatively large vicinities.
49

References
 Asif Memon, Syed Riaz un Nabi Jafri, Syed Muhammad Usman Ali,” A Rover Team
based 3D Map Building using Low Cost 2D Laser Scanners”.
https://www.researchgate.net/publication/357363038_A_Rover_Team_based_3D_Ma
p_Building_using_Low_Cost_2D_Laser_Scanners
 PileunKim,JingdaoChen ,Yong K.Cho,“SLAM-driven robotic mapping and registration
of 3D point clouds”.
https://www.sciencedirect.com/science/article/abs/pii/S0926580517303990
 Zheng Fang , Shibo Zhao, Shiguang Wen, and Yu Zhang, “A Real-Time 3D
Perception and Reconstruction System Based on a 2D Laser Scanner”.
https://www.hindawi.com/journals/js/2018/2937694/
 David M. Cole and Paul M. Newman,“Using Laser Range Data for 3D SLAM in
Outdoor Environments”.
https://www.robots.ox.ac.uk/~mobile/Papers/3DScanMacthingCole_ICRA2006.pdf
50

Refrences
 P. Lepej, M. Lakota and J. Rakun,”Robotic real-time 3D object reconstruction
using multiple laser range finders”.
https://www.cambridge.org/core/journals/advances-in-animal-
biosciences/article/abs/robotic-realtime-3d-object-reconstruction-using-
multiple-laser-range-finders/B7168728D5D093B9492BCEBA4F49C038
 Kyeong-Hwan Lee, Reza Ehsani,“Comparison of two 2D laser scanners for
sensing object distances, shapes, and surface patterns”.
https://www.sciencedirect.com/science/article/abs/pii/S0168169907001834
 Jan Weingarten and Roland Siegwart,“EKF-based 3D SLAM for structured
environment reconstruction”. https://ieeexplore.ieee.org/document/1545285
 Peter Zhang, Evangelous Millos & Jason Gu,“General Concept of 3D
SLAM”.
https://www.researchgate.net/publication/221786534_General_Concept_of_3
D_SLAM#:~:text=Simultaneous%20localization%20and%20mapping%20(SL
AM,map%20that%20includes%20feature%20locations.
51

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