Executive Summary Since the invention of military Unmanned Aerial Systems (UAS), the number of different use cases has grown significantly with recent years seeing expansion into the civilian sectors. Following the advent of low-cost commercial components, UASs have seen inc
Hybrid VTOL UAV surveillance system
Executive Summary
Since the invention of military Unmanned Aerial Systems (UAS), the number of different use cases has grown significantly with recent years seeing expansion into the civilian sectors. Following the advent of low-cost commercial components, UASs have seen increased demand for use in humanitarian disaster zones to rapidly deliver small aid packages to those in need. While delivering aid, UAS may also photograph the zone to aid future relief efforts. With the need for these humanitarian UASs follows numerous challenges to be solved before a full scale deployment of system. hence the need for the Vertical Take Off UAS was a basic need of the society. The Team consists of a group of young and passionate students from DHA Suffa University, with the aim of designing and manufacturing an Unmanned Aircraft in and as their final year project. The team looks forward to accomplish the task efficiently, keeping under consideration the parameters, scope and limitation committed in the defense proposal presentation and which were proposed in concept design report. Team comprises of total four members of final year semesters of Electrical Engineering under the supervision of steamed professors as advisors.
The Project Hybrid UAV VTOL Surveillance System; this was envisioned, designed, and manufactured by students of DHA Suffa University. As the aircraft is capable of fully autonomous missions for humanitarian relief, both its technical viability and wider business applicability are demonstrated.
The UAV layout has been finalized as a high-wing, H-tail configuration. A High-Wing design places the engine thrust line through the Centre of Mass, minimizing thrust pitching moment and improving payload and release mechanism visibility, whereas the tail configuration reduces ground strike. To achieve the necessary maximum lift coefficient to land within requirements vertical rotors are implemented. The nose gear with a lighter, less vulnerable tail gear that also improves the Field of View (FOV) of the image recognition camera. As aircraft for the UAV missions are frequently damaged due to the testing rigour, ease of repair and manufacture was desired. Focus was put on achieving a low mass airframe to maximize payload capacity and enhance competitiveness. Lastly, high modularity was achieved easing transport, maintainability, and upgrade-ability.
Project Scope
The team task has to design, build, and demonstrate an aircraft which can autonomously perform a mission analogous to disaster relief in a “remote coastal area devastated by an earthquake or tsunami”. For accomplishment, two major mission is to be conducted; Payload Delivery and Reconnaissance. For the Payload Delivery mission, the aircraft is required to take off from a given Take-Off and Landing Zone before navigating through a series of waypoints towards a GPS position. At the target, the aircraft drops a single payload before completing a circuit to return to the target to release another single payload. The payload drop section is repeated until all payloads have been released after which the aircraft returns for landing. The Reconnaissance mission requires the aircraft to take-off and navigate to two search areas with each search area containing two alphanumerical targets. The aircraft must then search each area and geo-locate all targets, identify the alphanumeric, and transmit the information to a ground station. All operations in both missions including aerial navigation, payload release, and image recognition should be autonomous, requiring no operator input once each mission has commenced.
Design Derivation and Innovation
A typical fixed wing configuration takes long runway and power to get upto speed to take off, this directly reduces the overall endurance, increases take off time and requires a large open space to get UAS in the air, in order to cope up with this issue a thought process was generated towards Quadplane (also known as VTOL). The goal of this project is to design and fabricate an autonomous VTOL UAV with hybrid propulsion technology i.e. both a gasoline engine and electric motors. The system is aimed towards performing humanitarian missions such as aid delivery and also consists of AI based object recognition. The project will utilize popular open source flight core using Flight controller Pixhawk (drone core from Linux foundation) for autonomous flight and deep learning-based object recognition using GPU (Jetson Nano system on module).
| Parameters | System Requirement |
| Airframe Configuration |
|
| Propulsion |
|
| Payload |
|
| Control System |
|
| Image Recognition |
|
Parameters
Airframe Configuration
Propulsion
Payload
Control System
Image Recognition
Vertical Takeoff and Land UAV is a multi-purpose reconnaissance integrated UAV system with characteristics of low-altitude, moderate speed and long endurance.
Features
Outstanding operational capability
• Multiple flight modes, convenient for operation
• Dynamic mission planning and uploading
Flexible payload integration capability and multi-task execution, High reliability, safety and maintainability design.
Application
Technology
The third-dimension movement increases the geographic accessibility to remote and underserved areas of the country.
Moderate Speed & Range
Self-piloted flying vehicles can operate at twice the speed of the average road vehicle and extend communication geographical reach by tenfold.
Reconnaissance
Improved Artificial intelligence based Deep Learning object Recognition. Field reconnaissance, surveillance, real-time video feed. Monitoring of natural disaster for humanitarian Aid.
Environmental Footprints
Self-piloted flying vehicle with hybrid propulsion electric Rotor and Internal Combustion engine .
Project Deliverables
1.Mathematical Calculation over Airworthiness parameter
The UAV MTOW shall not exceed 8 kg including the payload(s) and GPS tracker.The UAV shall be capable of fully autonomous fight.
The UAV shall be designed to perform a payload delivery mission where the UAV carries and deliver speed arrested payloads. Payload is individually deployed over the targeted area either automatically or manually without landing.
The UAV shall be designed to perform a reconnaissance mission in order to classify the ground rover in a survey area.
The UAV shall be designed to take-off and land within a 30 m diameter circle and to fly between 20ft and 400ft.
The UAV shall incorporate a Flight Termination System and manual override capabilities.
2. Fabrication of the Airframe

3. Autonomous Mission with payload Drop Capability
The system Architecture is described to be as follows the power distribution system will power the electromechanical and the flight controller (Pixhawk) and the Image Recognition module simultaneously. The Flight controller is in communication with the electromechanical system as well as the Ground Control Station (GCS) which navigate the path.

4. Deep-learning Based Image Recognition
The image Recognition pipelining of the system is started from the data Acquiring and towards the model training section when it is talked about the training part as we enters the inference the trained model is fetch and sent into the Inference Engine along with the video stream where the classification is been executed and a report is generated.

| Elapsed time in (days or weeks or month or quarter) since start of the project | Milestone | Deliverable |
|---|---|---|
| Month 1 | Preliminary Calculation | Mathematical Calculation over Airworthiness parameter |
| Month 2 | Detailed Calculation | Mathematical Calculation over Airworthiness parameter |
| Month 3 | Solid Body Assembly | Fabrication of the Airframe |
| Month 4 | Weight Deducted Assembly | Fabrication of the Airframe |
| Month 5 | Laser Cutting, Integration Fabrication | Fabrication of the Airframe |
| Month 6 | Firmware Installation, Calibration & testing | Autonomous Mission with payload Drop Capability |
| Month 7 | Automated Flight Mission testing | Autonomous Mission with payload Drop Capability |
| Month 8 | Selection of Pattern Collection of Data | Deep-learning Based Image Recognition |
| Month 9 | Model Training &Testing | Deep-learning Based Image Recognition |
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