Autonomous Device for Obstacles Detection
Robotics is a part of today?s communication which will make human life simpler in day today aspect. So we are supporting this cause. This is the Smart city project that will be based on Artificial Intelligence, Image Processing and some touch of Hardware (Robotics). We make autonomous device that mo
Project Title
Autonomous Device for Obstacles Detection
Project Area of Specialization
Project Summary
Robotics is a part of today’s communication which will make human life simpler in day today aspect. So we are supporting this cause. This is the Smart city project that will be based on Artificial Intelligence, Image Processing and some touch of Hardware (Robotics). We make autonomous device that moving and taking decision on its own intelligence. The device should be able to detect the obstacles for smooth and efficient working in order to avoid accident and collision. It should also be able to calculate the distance of the obstacle from the device and making the corresponding decisions. The Device can be Trackable by sending the location continuously to the mobile device through IOT using Gps and Wi-Fi Module. The device just not only detect the obstacles but it can also recognize it by using the Machine Learning Techniques. Furthermore, device is also be control with the voice using Bluetooth.
Project Objectives
Our fundamental goal is to facilitate the people so for this purpose our project objectives is to make a device autonomous and this autonomous device has an ability to taking decisions on its own and also an ability to detect the obstacles on its way. By making the device autonomous is itself a big achievement but if we can detect and recognize the obstacles then we can achieve many goals like real world settings in different fields such as military, medical field, space exploration and everyday housekeeping etc.
Our main objectives are following:
Autonomous Device: Moving and turning by taking decision on its own intelligence.
Obstacle Detection: Detection of the obstacles is possible while device moving or static.
Beneficial thing for the people: Less human responsibilities, Machine Control, so that there are less chances of human errors.
Rational Decision: Able to take more rational decisions by reducing the computational time.
Obstacle Recognition: Able to recognize specific type of obstacles.
Trackable Device: Able to track the device anywhere in the world.
Voice based Movement: Able to Control the device on the basis of voice.
Project Implementation Method
To explain the Implementation, we are explaining the Use case Diagram, Methodology, Architecture and the Swift lane Diagram of our Project "Autonomous Device for Obstacle Detection".
Use Case Diagram
Figure1: Use Case Diagram
Methodology
Figure2: Methodology
Architecture and working
Autonomous Device for Obstacle Detection is based on Three-Tier Architecture.
- Data Layer
- Business Layer
- Presentation Layer
Data Layer is composed of Environment modeling and Localization. They rely on camera, Gps, Bluetooth, Ultrasonic, infrared sensors etc. Next, Business Layer consists of Arduino and Raspberry Pi which taking Decisions, detect and recognize Obstacles voice control and Gps based Decision on the basis of the information delivered by the Data Layer. Finally, the Presentation Layer having Controller which is dedicated to follow the Decisions that has been taken by the Business layer by commanding the vehicle’s actuators.
Figure3: Architecture
Data comes from Analyzing and Perceiving the environment effectively is mandatory for an autonomous device. Because it gives information to extract the locations of static/dynamic objects as well as the type of the obstacle that device will face.
On the given previous information device can take different decisions on different scenarios that are defined by the business layer in the form of logics.
In the last Device can move and perform on the basis of the logical decision that are made by the previous layer.
Swift Lane Diagram
Figure4: Swift Lane Diagram
Benefits of the Project
- Device will be autonomous device which can be used in almost all mobile robot navigation systems.
- This device can never be lost we can track it easily using Google maps.
- Blind people also use this device on the basis of voice-based movement.
- Device Will be able to navigate through obstacles from one place to another by detecting.
- Taking More Rational Decisions by reducing the Computational time.
- More towards Autonomous Vehicle.
- Device Will be able to Recognize the different obstacles.
Technical Details of Final Deliverable
Hardware Technologies
| Tools | Rationale |
| Arduino Uno | In our Project Arduino will be a core because we use to control different sensors, and motors through this microcontroller. |
| Raspberry Pi 4 | In our Project we need computer vision properties for image recognition. |
| DC Motor | To run the wheel. |
| Chargeable Battery | To give the Vcc to the device |
| Ultrasonic Sensor (HC-SR04) | To calculate the distance from the obstacles |
| IR Sensor (LM 393) | To calculate the distance between the ground and the device for better movement |
| Pi Cam Model V2 | To display the live stream and show the obstacles being recognized. |
| Wheels | To move the device |
| Charger | To Charge the battery |
| Bluetooth (HC-05) | To communicate between the mobile and the device specially for the voice-based movement. |
| Gps Module (Ublox Neo-6m) | To get the current location of the device |
| ESP88266 12-E Wi-Fi Module | To communicate between the mobile and the device for Gps purpose |
| L293d Motor Driver | To control the motors. |
| Servo motor SG90 | To move the sensors for the purpose of detecting obstacles |
| Male, Female Wires | For Connectivity Purpose |
Software Environment
| Environment | Rationale |
| Pycharm | In our Project for Python we are using PyCharm Environment. This is Because we are familiar with this and is easy for us to do new things on it. It is also very efficient and easy to use. |
| Arduino Ide | It’s an environment that is used to program the Arduino. C++ is a basic language of it. You can write different logics read and write different sensors values and take the decisions accordingly. |
| LXDE | Raspberry Pi OS uses a modified LXDE as its desktop environment |
Software Libraries
| Libraries | Rationale |
| Open CV | For object Recognition purpose to attain the Computer vision properties |
| Adafruit (Motor.h) | For controlling the DC motors by Arduino |
| &l |
Tools
Arduino Uno
Raspberry Pi 4
DC Motor
Chargeable Battery
Ultrasonic Sensor (HC-SR04)
IR Sensor (LM 393)
Pi Cam Model V2
Wheels
Charger
Bluetooth (HC-05)
Gps Module (Ublox Neo-6m)
ESP88266 12-E Wi-Fi Module
L293d Motor Driver
Servo motor SG90
Male, Female Wires
Environment
Pycharm
Arduino Ide
LXDE
Libraries
Open CV
Adafruit (Motor.h)
&l
Final Deliverable of the Project
Core Industry
Other Industries
Core Technology
Other Technologies
Sustainable Development Goals
Required Resources
| Environment | Rationale |
| Pycharm | In our Project for Python we are using PyCharm Environment. This is Because we are familiar with this and is easy for us to do new things on it. It is also very efficient and easy to use. |
| Arduino Ide | It’s an environment that is used to program the Arduino. C++ is a basic language of it. You can write different logics read and write different sensors values and take the decisions accordingly. |
| LXDE | Raspberry Pi OS uses a modified LXDE as its desktop environment |
If you need this project, please contact me on contact@adikhanofficial.com
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