Projects:2018s1-145 Simplified Indoor UAV Operations

From Projects
Revision as of 12:27, 21 August 2018 by A1669931 (Talk | contribs)

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

UAVs have been mainly used for defence since 200??, however since entering the commercial market UAV development for personal use has taken the forefront of UAV development. Due to the increasing functionality available on commercial UAVs many sectors have begun exploring the possible applications of drones.

Many papers published on UAV development Potential for student courses

Our project focuses on implementing obstacle evasion within a defined space using an Optitrack System. This wiki shall firstly discuss the background motivations behind this study as well as the research that has already been conducted within this field. The project shall then be broken into sections...

Project Team

Elizabeth Hodgins

Matthew Preece

Samuel Thomas

Supervisors

Dr Hong Gunn Chew

Dr Braden Phillips

With assistance from Ryan Choi


Definitions

UAV - Unmanned Aerial Vehicle

Background and Previous Studies

Potential Fields

In the 2015 study at Universitas Gadjah Mada in Indonesia, by Budiyanto, et. al [2], attractive and repulsive potential fields around the controlled UAV, its destination and its surroundings were used to avoid collisions and reach a set destination. In the potential field method, a controlled vehicle is likened to a charged particle which is attracted to its destination and repelled from any objects in its path [24]. The group used a combination of these two forces to determine the linear acceleration of the UAV along its path to a destination. However, limited its motion to remaining at the same altitude for the duration of the path. The repulsive constant affects the limit distance of how close the UAV will approach a repulsive object and was varied throughout the experiments to determine the best value. These values were tested using a Parrot AR Drone 2.0 in simulation using the Gazebo simulator package through the Robot Operating System (ROS). Three test cases were used - a single UAV with static obstacles along its path, three UAVs in one area, with only one UAV with a destination and five UAVs with destinations within one area manueovering static objects and the other UAVS around them. In each test case, accuracy, time to complete and path length were compared. In the conclusion of the study, it was determined that the optimal repulsive constant value was 7.8 for dynamic performance. Whilst the potential field algorithm in this study is applied in path planning to a specified location, our research will analyse the effectiveness of potential fields when applied to manual flight control


Equipment

OptiTrack Motion Capture System


Parrot Mambo Drone


System Design

System Diagram

The system has been broken into four main high-level components, and then further broken down into individual tasks within them.

Testing

Results

Conclusions

References

[1] Commercial drones are the fastest-growing part of the market https://www.economist.com/news/technology-quarterly/21723003-most-drones-today-are-either-cheap-toys-or-expensive-weapons-interesting [2] A. Budiyanto, A. Cahyadi, T. B. Adji and O. Wahyunggoro, ``UAV obstacle avoidance using potential field under dynamic environment, In Proc. 2015 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC), Bandung, (2015), pp. 187-192. Available: IEEE Explore, {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7337041&isnumber=7337022}. [Accessed: May 29, 2018].