Autonomous Drone for Indoor Environment
Unmanned Ariel Vehicles are the most active area in the field of robotics. There are a lot of types of UAVs being developed by the robotics industry i.e. Fixed Wings (Quad Copter, Hex Copter) UAV and Variable wings UAVs (Helicopter). In the category of fixed wings, the quadcopter is most popular one
2025-06-28 16:30:31 - Adil Khan
Autonomous Drone for Indoor Environment
Project Area of Specialization RoboticsProject SummaryUnmanned Ariel Vehicles are the most active area in the field of robotics. There are a lot of types of UAVs being developed by the robotics industry i.e. Fixed Wings (Quad Copter, Hex Copter) UAV and Variable wings UAVs (Helicopter). In the category of fixed wings, the quadcopter is most popular one because of its simplicity and easy controllability.
In the quadcopter industry mostly, drones were developed for outdoor and they have GPS for the navigation of location. They have a RC controller for the drone motion controlling and monitoring the camera motion, but our purposed drone project is neither containing the GPS nor a RC for controlling the motion of the quadcopter. Rather proposed project (titled as Autonomous Drone for Indoor motion is based on a quad copter) can move in a dynamic indoor environment without pilot commands and get a survey of the environment.
The main objective of the project is to design and to build autonomous drone that can move without human intervention in any unknown and indoor environment by getting the visual information using the vision and depth sensors.
The proposed drone system will use the vision and depth sensor for getting the environmental data. An important part of the purpose system is that It can transmit visual data over a long distance using the internet technology (IoT). The proposed system will be able to collect the data of dynamic environment (survey) using the quadcopter where human cannot go, or it is dangerous to go there for humans.
Project ObjectivesProposed project titled as Autonomous Drone for indoor motion is being designed to solve the problem of drone for indoor motion. The quadcopter (drone) can fly autonomously and get the details (visual data/video) from environment and transmit it over the long distance using the technology of the internet. Proposed drone system is using a very cost-effective technique for the environment perception using a vision sensor (camera) and go to the dedicated location.
Autonomous drone for indoor motion can be used for various purposes in many domains of the engineering and security. In the domain of security, it could be used for the indoor inspection where generous to go for the humans. For engineering purpose, it is used to get the real-world data which can be used for getting the 3D model of the indoor environment (building).
Purpose of designing the drone is to automate the process of fight and get the visual information over a long-distance using internet technology and sending it to the specified location inside of the building using the vison-based technique.
The objective of the project is to design a drone that can move without the human intervention and we can define a navigation point and it reaches to the navigated point using the vision sensor for getting the visual information of the dynamic environment for avoiding the obstacles as well as finding the desired location and transmitting the visual data to the desired server over a global internet technology.
METHODOLOGY
- Hardware design of Drone (quadcopter)
- Stability (balancing) of Drone
- Developing a drone vision system using Monocular SLAM method (based on monocular camera)
- Designing of Communication system for drone using IOT
Autonomous drone for indoor motion is being implemented for the indoor motion, navigation and visual data transformation using internet technology. There are 4 major milestones of this project. These are as follows
- Designing a drone (hardware)
- Controller designing for drone stability and balancing
- Vision system designing for avoiding the obstacles
- Communication system for transmitting the video streaming
Designing a drone
Designing the drone (hardware) is based on the drone weight/mass. Because drone has to carry its weight for the flying in the air so we have to calculate the weight to trust ratio and then according to the weight to trust ratio we have selected the drone components like motor (we have selected the brushless DC motor due to its efficiency and low weight) and propeller and the battery that will power the drone and a processing board (Raspberry Pi) that will process the video for the vision system. After selecting the components, we have assembled the drone hardware.
Controller designing
The most important milestone of the project is to design a controller that will make a stable flight for the drone (drone stability and drone balancing) so that it can bear the effect of the wind and air for the smooth flight. We are implementing Proportional Derivative and Integration controller (PID) using a machine learning approach called Neural Networks for drone balancing and stabilization. Although we have many other options like Sliding Mode controller, Feed Back linearization backstepping but we are using PID controller using the Neural Network approach due to its simplicity and better performance.
Vision system
We are designing a vision system for the drone so that it can avoid the obstacles and fly smoothly in dynamic environment and get the visual information and go to the desired position inside the building using vision sensor called camera. For achieving this milestone, we are using an algorithm called Monocular SLAM. SLAM stands for the Simultaneous Localization and Mapping. It gets the visual data form the environment using camera and estimates its position and consider the landmarks and construct a map.
Communication system
We are designing the drone communication system based on the IoT (Internet of Thing), so that it can transmit the visual data (video/map) using internet (Global Network).
Benefits of the ProjectBenefits of the project are as follows: -
- Proposed drone system is autonomous, so need of any human pilot is eliminated.
- Proposed drone system is based on vision. It is very accurate to navigate the location and avoiding the obstacles.
- It is based on Internet technology so that I can send data to server anywhere in the world.
- The proposed drone system is built for indoor environment so I can investigate the places that are dangerous for human to go.
- Its (android and desktop) application is very simple and friendly so that everyone can operate it easily.
- Proposed drone system is containing a system that if its battery power is less then up to a specific value, it will land itself automatically.
- Propose drone system is contains the vision system on front as well as back so that it can move in both the directions.
- Proposed drone system is containing a very powerful balancing system so that in the heavy wind pressure it can stabilize itself.
Final deliverable of the proposed drone system are as follows: -
- Drone (Quadcopter) can fly smoothly in air, means that its stability controller (PID using Neural Network) is working efficiently.
- It is avoiding the obstacles of the dynamic and indoor environment using proposed vision systems based on the Monocular SLAM.
- It is transmitting visual data using internet (IoT)
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 42628 | |||
| Q450 Quad 450 V3 Quadcopter Frame Kit 450Mm | Equipment | 1 | 1800 | 1800 |
| A2212 1000KV Brushless Outrunner Motor | Equipment | 4 | 1350 | 5400 |
| RC BRUSHLESS ELECTRONIC SPEED CONTROLLER (HLW XXD-30A) | Equipment | 4 | 1350 | 5400 |
| Raspberry Pi Starter Kit Raspberry Pi 3 B+ starter kit | Equipment | 1 | 9500 | 9500 |
| 11.1V 30C 3S 5000mah Lipo Rechargeable Lithium Polymer Battery | Equipment | 1 | 5300 | 5300 |
| IMAX B6 80W LIPO RC BATTERY BALANCE CHARGER | Equipment | 1 | 2400 | 2400 |
| propellers | Equipment | 4 | 250 | 1000 |
| Mini Video Recorder FPV Drones Quadcopter Fly Helicopter Lens IR Night | Equipment | 2 | 5664 | 11328 |
| MPU-6050 Gyro + Accelerometer Sensor | Equipment | 1 | 300 | 300 |
| Ultrasonic Sensor HC-SR04 | Equipment | 1 | 200 | 200 |