STM32 Based Quadcopter For Obstacle Avoidance
Using Ultrasonic Sensor
Prof. Priya Gupta
Electronics & Telecommunication
Department
K J Somaiya Institute of Technology
Mumbai, India
priya.ag@somaiya.edu
Muiz Tanki
Fredrick Ambrose
Electronics & Telecommunication
Department
K J Somaiya Institute of Technology
Mumbai, India
fredrick.a@somaiya.edu
Aarti Kumbhar
Sahil Naik
Electronics & Telecommunication
Department
K J Somaiya Institute of Technology
Mumbai, India
sahil.naik1@somaiya.edu
Jainam Shah
Electronics & Telecommunication
Department
K J Somaiya Institute of Technology
Mumbai, India
muiz.tanki@somaiya.edu
Electronics & Telecommunication
Department
K J Somaiya Institute of Technology
Mumbai, India
aarti.k@somaiya.edu
Electronics & Telecommunication
Department
K J Somaiya Institute of Technology
Mumbai, India
jas@somaiya.edu
Abstract—This research paper presents the development of
a drone system that is based on a quadcopter and utilizes an
ultrasonic sensor for evaluating obstacles and measuring
altitude. The project employs an STM32 microcontroller and
Arduino programming to establish a quadcopter platform that
is both affordable and educational. The system encompasses
various functionalities such as auto-leveling and altitude
maintenance. The hardware components and calibration
procedures are extensively elucidated to ensure a flight that is
safe and dependable. The paper highlights the importance of
calibrating the sensor, balancing the motors and propellers,
and effectively implementing obstacle avoidance and altitude
measurement capabilities. In conclusion, this project offers a
comprehensive resolution for self-sufficient drone navigation
and control.
Keywords—Obstacle avoidance,
Ultrasonic Sensor, STM32
I.
Quadcopter,
Drone,
INTRODUCTION
Over the past few years, the rise in unmanned aerial vehicles
(UAVs), commonly referred to as drones, has sparked a
surge of interest in self-governing flight systems. Drones are
used in a variety of fields, such as monitoring, farming, and
delivering packages, where they must navigate intricate
environments with accuracy and safety. The success of
self-governing drone systems depends on their ability to
detect and avoid obstacles in real-time, ensuring secure
operation. This research article presents a comprehensive
examination of integrating ultrasonic sensors for obstacle
avoidance and altitude measurement in a quadcopter-based
drone system. In our quest to develop an effective and
economical solution, we leverage the power of
STM32F103C8T6 microcontrollers, combined with Arduino
programming, to establish a versatile and informative
platform.
The core objectives of this study are to achieve a
minimalistic yet robust codebase and to minimize overall
project costs while ensuring effective obstacle detection and
altitude control. Our system relies on strategically placing
four to six ultrasonic sensors, allowing the drone to perceive
its surroundings and respond to obstacles instantaneously.
We delve into the complexities of selecting appropriate
hardware, calibration methods, and sensor fusion algorithms
to create a reliable and adaptable obstacle avoidance system.
XXX-X-XXXX-XXXX-X/XX/$XX.00 ©20XX IEEE
Additionally, accurate altitude measurement plays a vital
role in achieving stable flight, particularly in challenging
terrain or during independent missions. Throughout this
study, we emphasize the importance of sensor calibration,
motor-propeller equilibrium, and precise control algorithms
to optimize the system's efficiency. We investigate the
difficulty of integrating sensors, assembling hardware, and
developing software to offer a comprehensive approach to
quadcopter-based drone autonomy. As the UAV industry
continues to progress, the discoveries from this investigation
contribute to the advancement of safer and more capable
drone systems, with various applications ranging from
independent monitoring to search and rescue operations. The
successful implementation of ultrasonic sensors for obstacle
avoidance
and
altitude
measurement
in
our
quadcopter-based drone system represents a significant
stride towards enhancing the capabilities and safety of
self-governing UAVs.
II.
DRONE DESIGN
A. To create a quadcopter-based drone system with a focus
on educational and hobbyist applications. Here's an
overview of the key elements of this drone design:
B. Flight Controller: The heart of the design is the STM32
quadcopter flight controller, which is programmed using the
Arduino IDE. This flight controller serves as the central
processing unit for stabilizing the drone, managing sensor
data, and executing flight control algorithms.
C. Cost Efficiency: An essential aspect of the design
philosophy is to keep costs to a minimum, making it
accessible to a wide range of enthusiasts and students. The
goal is to create a complete drone system for under Rs
15,000, including essential components like the battery,
charger, remote control, and telemetry system.
D. Hardware Selection: The drone design specifies a list of
hardware components, including the STM32F103C8T6
microcontroller, MPU-6050 gyro/accelerometer, Flysky
FS-T6 6-CH TX Transmitter with IA6B Receiver, resistors,
LEDs, and more. These components are chosen for their
compatibility and cost-effectiveness.
E. Balancing and Calibration: Proper motor and propeller
balancing, along with sensor calibration, are critical steps in
ensuring stable and safe flight. The design provides
guidance on balancing props and calibrating sensors to
optimize performance.
F. Software Development: The software of the drone is
crucial to flight stability and control. To provide
transparency and user-friendliness, the flight controller code
is extensively documented and commented on. This enables
code explorers to go into the code, tweak it, and adapt it to
their unique needs.
TX Transmitter & for receiver we use Flysky FS-iA6B
Receiver. On the schematic, only the ground and signal
wires of ESC 2, 3, and 4 are connected, which is the correct
configuration. The +5V (BEC) from ESC 1 is also
connected, supplying power to the flight controller. If your
ESC lacks a built-in BEC/+5V, you must supply power
using a 5V step-down regulator connected to the flight
battery. You will need a 1 x Mini DC 7~28V to DC 5V
step-down converter for this purpose.
L. FTDI Adapter: The FTDI adapter is used for
programming and communicating with the STM32
microcontroller. It provides a USB-to-serial interface,
allowing you to upload code and debug the microcontroller
using a computer. The FTDI adapter is connected to the
UART (Universal Asynchronous Receiver-Transmitter) pins
of the STM32 to establish communication.
M.
LiPo Battery: The LiPo battery is the power source
for the drone's electronics, including the STM32
microcontroller. By connecting the LiPo battery to the
STM32, you provide it with the necessary power to operate.
The battery is typically regulated to a suitable voltage for the
microcontroller's power supply.
Figure 1. Block Diagram of Connections between components of drone
G. Flight Controller: Choose a flight controller board with
sufficient processing power and sensor inputs. Ensure it
supports sensor integration, such as accelerometers and
gyroscopes for stability control. Implement flight control
algorithms to stabilize the drone using sensor data.
H. Control and Navigation Algorithms: Implement control
and navigation algorithms that take the obstacle detection
data into account and adjust the drone's flight path to avoid
collisions.
I. Testing and Validation: Conduct rigorous testing and
validation of our obstacle avoidance system. This may
involve simulated testing, controlled indoor flights, and
outdoor field tests. Collect data to evaluate the system's
performance. If you look at Fig. 1 in this schematic diagram,
you'll notice that we're using our main component, the
STM32F103C8T6, connected to the voltage divider R3 and
R4. These resistors divide the flight battery voltage by 11,
allowing us to monitor the battery voltage during flight.
J. The LED will illuminate when the battery voltage drops
too low, and the motor RPM will automatically increase to
compensate for the decreasing battery voltage during flight.
It's crucial to install the 1kΩ and 10kΩ resistors; otherwise,
the quadcopter will not fly perfectly, and the battery
warning system will not function. Mounting the gyro in the
incorrect orientation can lead to an immediate upside-down
flip of the quadcopter. Ensure you use thin double-sided
tape for mounting, avoiding foam tape or any other
damping material, as these can reduce performance.
K. Ensure that the transmitter has adjustable endpoints and
subtrims by referring to its manual for these specific
functions. The transmitter we use is the Flysky FS-T6 6-CH
N.
Overall, the FTDI adapter enables programming
and communication with the STM32, while the LiPo battery
supplies power to the microcontroller and other drone
components. In summary, this drone design provides an
accessible and cost-effective platform for building a
quadcopter-based drone system. implementing obstacle
avoidance in a drone is a complex task that requires a deep
understanding of drone hardware, software development,
control systems, and sensor integration.
III.
SYSTEM DESIGN
A. The system design of the obstacle avoidance drone
involves integrating an ultrasonic sensor with existing
components such as the frame, motors, microcontroller, and
gyro/accelerometer. The sensor sends ultrasonic waves and
measures the time taken for the waves to bounce back, allowing
for distance calculation. The STM32F103C8T6 microcontroller
processes the sensor data and controls the drone's movements.
The implementation includes connecting the sensor to the
microcontroller, programming the microcontroller to interpret
the sensor data, and adjusting the drone's movements based on
the obstacle detection. Further testing and refinement are
needed for optimal performance.
B. Frame: We are using a 450 size frame with an integrated
power distribution board. This frame provides the structure
and support for the rest of the components.
C. Motors and Props: The drone is equipped with four
1000kV motors and 10x4.5 props. These motors generate
the necessary thrust to lift and maneuver the drone.
D. ESCs: We have a motor/ESC combo, which means the
Electronic Speed Controllers (ESCs) are integrated with the
motors. ESCs regulate the speed and direction of the motors.
E. Flight Controller: We are using an STM32F103C8T6
microcontroller as the flight controller. This microcontroller
handles the processing and control of the drone's flight.
F. Sensors: The MPU-6050 gyro/accelerometer is used for
stability and orientation control.
It provides data on the drone's attitude and motion.
G. Transmitter & Receiver: The Flysky FS-T6 6-CH TX
Transmitter is used for controlling the drone remotely. It
sends signals to the receiver on the drone to control its
movements. The FS-iA6B Receiver is a component used in
the drone system to establish communication between the
transmitter and the flight controller. It operates on a specific
frequency and receives signals transmitted from the
transmitter.
H. Power: The drone is powered by a 3S/2200mAh/30C lipo
battery, which is connected through a XT60 connector.
I. Charging: You have a 2S/3S lipo battery charger
for charging the drone's battery.
J. LEDs: The drone is equipped with 3mm LEDs in
red, yellow, and green for visual indicators.
IV. LITERATURE SURVEY
The research paper introduces a quadcopter-based drone
system incorporating ultrasonic sensors for obstacle
avoidance and altitude measurement using an STM32
microcontroller. Drones, vital in various industries, demand
precise navigation through complex terrains for safety. This
study focuses on integrating ultrasonic sensors into the
drone platform, utilizing STM32 microcontrollers with
Arduino programming for cost-effectiveness. It emphasizes
achieving robust obstacle detection and accurate altitude
control while minimizing project costs. Detailed hardware
descriptions, calibration methods, and sensor fusion
algorithms are discussed. The successful integration of
ultrasonic sensors enhances drone safety and autonomy,
marking a significant step forward in UAV technology.
●
●
●
●
B. Overall, integrating the ultrasonic sensor and obstacle
avoidance feature with the YMFC-32 quadcopter project
adds an additional layer of intelligence and autonomy to the
drone's capabilities, making it more versatile and efficient in
its operations.
●
●
●
Connect the motors to the ESCs and mount them
securely on the frame.
Connect the ESCs to the flight controller
(STM32F103C8T6) according to the pinout
diagram.
Connect the MPU-6050 gyro/accelerometer to
the flight controller.
Connect the Flysky FS-T6 transmitter to the flight
controller.
Mount the glass fiber prototyping PCB and
solder the components according to the
schematic.
Connect the ultrasonic sensors to the
flight controller for obstacle avoidance.
VI. CONCLUSION
In conclusion, our project contributes to the field of drone
technology by providing a practical and reliable obstacle
avoidance solution using ultrasonic sensors. This research
opens doors for safer and more autonomous drone operations in
real-world environments. The successful integration of
ultrasonic sensors and the development of a robust algorithm
represent important contributions to the field. As technology
continues to evolve, there is ample opportunity for further
refinement and expansion of our system to address emerging
challenges and applications in the drone industry.
REFERENCES
1.
2.
3.
V. IMPLEMENTATION
A. To implement obstacle detection and avoidance, the
ultrasonic sensor can continuously measure the distance to
obstacles in the quadcopter's flight path. If an obstacle is
detected within a certain range, the flight controller can send
commands to the quadcopter's motors to adjust its flight path
and avoid the obstacle. This can be achieved by
programming the flight controller to interpret the sensor data
and make appropriate adjustments to the quadcopter's flight
parameters. With the obstacle avoidance feature, the
quadcopter will be able to autonomously navigate its
surroundings and avoid collisions with obstacles. This
enhances the safety and maneuverability of the drone,
making it suitable for various applications such as aerial
photography, surveillance, or even delivery services.
Connect the XT60 connector to the power
distribution board and connect the battery.
4.
5.
Suherman, Rizky Ananda Putra and Maksum Pinem “Ultrasonic
Sensor Assessment for Obstacle Avoidance in Quadcopter-based
Drone System” in 2020 3rd International Conference on Mechanical,
Electronics, Computer, and Industrial Technology (MECnIT) p50-53,
IEEE 2020
M. Guanglei, P. Haibing, “The application of ultrasonic sensor in the
obstacle avoidance of quad-rotor UAV,” in 2016 IEEE Chinese
Guidance, Navigation and Control Conference (CGNCC) p 976-981,
IEEE, 2016.
H. Anis, AH, Fadhillah, S. Darma, S. Soekirno, “Automatic
Quadcopter Control Avoiding Obstacle Using Camera with Integrated
Ultrasonic Sensor”, in Journal of Physics: Conference Series vol.
1011, no. 1, p 012046, IOP Publishing, 2018.
Masatoshi Hamanaka, and Fujio Nakano “Surface-Condition Detection
System of Drone-Landing Space using Ultrasonic Waves and Deep
Learning” 2020 International Conference on Unmanned Aircraft
Systems (ICUAS) Athens, Greece. September 1-4, 2020 p1452-1459,
IEEE 2020.
MC De Simone, Z. B., Rivera, D. Guida, “Obstacle avoidance system
for unmanned ground vehicles by using ultrasonic sensors”,
Machines, vol.6, no. 2, p18, 2018.