MINISTRY OF EDUCATION AND TRAINING
HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION
________________________________________________
FACULTY OF INTERNATIONAL EDUCATION

GRADUATION PROJECT
STUDY ON POSITION ESTIMATION BY USING
SENSOR FUSION ALGORITHM FOR OUTDOOR
MOBILE ROBOT

Supervisor:

HÀ LÊ NHƯ NGỌC THÀNH, PhD

Student:

NGUYỄN CÔNG THÀNH

-

19146120

HUỲNH QUỐC AN

-

19146107

PHẠM ĐĂNG KHOA

-

19146136

Major: MECHATRONICS ENGINEERING TECHNOLOGY

Ho Chi Minh City, July 2024

MINISTRY OF EDUCATION AND TRAINING
HO CHI MINH CITY UNIVERSITY OF TECHNOLOGY AND EDUCATION
________________________________________________
FACULTY OF INTERNATIONAL EDUCATION

GRADUATION PROJECT
STUDY ON POSITION ESTIMATION BY USING
SENSOR FUSION ALGORITHM FOR OUTDOOR
MOBILE ROBOT

Supervisor:

HÀ LÊ NHƯ NGỌC THÀNH, PhD

Student:

NGUYỄN CÔNG THÀNH

-

19146120

HUỲNH QUỐC AN

-

19146107

PHẠM ĐĂNG KHOA

-

19146136

Major: MECHATRONICS ENGINEERING TECHNOLOGY

Ho Chi Minh City, July 2024

THE SOCIALIST REPUBLIC OF VIETNAM

Independence – Freedom– Happiness


Ho Chi Minh City, July, 2024

GRADUATION PROJECT ASSIGNMENT
Student name: Nguyễn Công Thành

Student ID: 19146120

Student name: Huỳnh Quốc An

Student ID: 19146107

Student name: Phạm Đăng Khoa

Student ID: 19146136

Major: Mechatronics Engineering Technology Class: 19146CLA
Supervisor: Hà Lê Như Ngọc Thành, PhD

Phone number: _________________

Date of assignment: _____________________ Date of submission: _____________

1. Project title: Study on position estimation by using sensor fushion algorithm for
outdoor mobile robot
2. Initial materials provided by supervisor: Pixhawk, GPS, IMU, Lab.
3. Content of the project:
- Study, design and fabricate the mobile robot
- Research and implement the algorithm to estimate the state of mobile robot (x, y, orientation)
Based on IMU and GPS
- Real implementation and test
- Write a report
4. Final product: Sensor fusion algorithm, a mobile robot
CHAIR OF THE PROGRAM

SUPERVISOR

(Sign with full name)

(Sign with full name)

i

THE SOCIALIST REPUBLIC OF VIETNAM

Independence – Freedom– Happiness
-

SUPERVISOR’S EVALUATION SHEET
Student name: Nguyễn Công Thành

Student ID: 19146120

Student name: Huỳnh Quốc An

Student ID: 19146107

Student name: Phạm Đăng Khoa

Student ID: 19146136

Major: .....................................................................................................................................
Project tit
...

...
ing and evaluation during robot assembly, ensuring the robot can
operate at high intensity.
6.1.2 Limit
- Limited resources, time and skills, limited access to technology.
GENERAL ASSESSMENT
Although they have only completed more than half of the initial tasks set, the team has
successfully applied the Sensor Fusion algorithm to control autonomous vehicles.
Although the initial investment is quite large, with the application of UGVs to explore
new environments - it can be dangerous for people or difficult to move. Using UGVs can bring
many benefits, including higher productivity, flexible design, remote control, easy control and
monitoring of operations, etc.

6.2. Development Direction
 Experimental obstacle avoidance for outdoor self-propelled vehicles.
 Add more sensors to increase the robots accuracy.
 Reinforce the self-propelled vehicles frame to make it more durable.

109

REFERENCE
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[1]
Joan Sola, Quaternion kinematics for the error-state Kalman filter
[2]
John L. Crassidis, QUATERNION IDENTITIES
[3]
Wertz, SPACECRAFT ATTITUDE DETERMINATIONAND CONTROL
[4]
readthedocs, Kalman Filter, https://ahrs.readthedocs.io/en/latest/filters/ekf.html
[5]
Jay A. Farrell, Aided GPS navigation with high-rate sensor
[6]
UNIVERSITÀ DI PISA, Attitude Estimation Using a Quaternion-Based
Kalman Filter With Adaptive and Norm based Estimation of External Acceleration
[7]
Orientation estimation using a quaternion-basedindirect Kalman filter with
adaptive estimation ofexternal acceleration
[8]
Kaiqiang, A New Quaternion-Based Kalman Filter for Real-Time Attitude
Estimation Using the Two-Step Geometrically-Intuitive Correction Algorithm
[9]
Sabatini, Sabatini, A. M. Quaternion-based extended Kalman filter for
determining
[10] Manon Kok, Jeroen D. Holy and Thomas B. Schon, Using Inertial Sensors for
Position and Orientation Estimation
[11] Intuitive Understanding of Kalman Filtering with MATLAB
[12] Timothy D. Barfoot, STATE ESTIMATION FOR ROBOTICS
[13] Jesús García, Engineering UAS Applications, chapter 4: navigation
[14] University of Toronto Coursera, state-estimation-localization-self-driving-car
[15] Error State Extended Kalman Filter Localization for Underground Mining
Environments
[16] INS/GNSS Tightly-Coupled Integration Using Quaternion-Based AUPF for USV
[17] Mingu Kim , The Design of GNSS/IMU Loosely-Coupled Integration Filter
for Wearable EPTS of Football Players

110

Appendix I

I

Appendix II

II