Obstacle avoidance algorithm for swarm of quadrotor unmanned aerial vehicle (UAV)
Unmanned aerial vehicle that is moving from one place to another needs to have a real-time obstacle avoidance controller to prevent collisions in the obstacles around it. In this study, the concept of Artificial Potential Field (APF) is proposed to implement obstacle avoidance in swarm of quadrotors...
Saved in:
Main Author: | |
---|---|
Format: | text |
Language: | English |
Published: |
Animo Repository
2016
|
Online Access: | https://animorepository.dlsu.edu.ph/etd_masteral/5206 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | De La Salle University |
Language: | English |
id |
oai:animorepository.dlsu.edu.ph:etd_masteral-12044 |
---|---|
record_format |
eprints |
spelling |
oai:animorepository.dlsu.edu.ph:etd_masteral-120442024-06-13T01:13:38Z Obstacle avoidance algorithm for swarm of quadrotor unmanned aerial vehicle (UAV) Galvez, Reagan L. Unmanned aerial vehicle that is moving from one place to another needs to have a real-time obstacle avoidance controller to prevent collisions in the obstacles around it. In this study, the concept of Artificial Potential Field (APF) is proposed to implement obstacle avoidance in swarm of quadrotors. This is based on the assumptions that the target and obstacle will introduce a certain force that will direct the robot to its destination. The effectiveness of this method was tested in a computer simulation and in actual implementation using Crazyflie quadrotors. The primary goal of the quadrotor is to go from point A to point B without colliding to the obstacles around it. The experiment shows that the actual implementation were similar to simulation results. It also proved that the APF was effective in real-rime obstacle avoidance and does not require complex mathematical equations to implement. 2016-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_masteral/5206 Master's Theses English Animo Repository |
institution |
De La Salle University |
building |
De La Salle University Library |
continent |
Asia |
country |
Philippines Philippines |
content_provider |
De La Salle University Library |
collection |
DLSU Institutional Repository |
language |
English |
description |
Unmanned aerial vehicle that is moving from one place to another needs to have a real-time obstacle avoidance controller to prevent collisions in the obstacles around it. In this study, the concept of Artificial Potential Field (APF) is proposed to implement obstacle avoidance in swarm of quadrotors. This is based on the assumptions that the target and obstacle will introduce a certain force that will direct the robot to its destination. The effectiveness of this method was tested in a computer simulation and in actual implementation using Crazyflie quadrotors. The primary goal of the quadrotor is to go from point A to point B without colliding to the obstacles around it. The experiment shows that the actual implementation were similar to simulation results. It also proved that the APF was effective in real-rime obstacle avoidance and does not require complex mathematical equations to implement. |
format |
text |
author |
Galvez, Reagan L. |
spellingShingle |
Galvez, Reagan L. Obstacle avoidance algorithm for swarm of quadrotor unmanned aerial vehicle (UAV) |
author_facet |
Galvez, Reagan L. |
author_sort |
Galvez, Reagan L. |
title |
Obstacle avoidance algorithm for swarm of quadrotor unmanned aerial vehicle (UAV) |
title_short |
Obstacle avoidance algorithm for swarm of quadrotor unmanned aerial vehicle (UAV) |
title_full |
Obstacle avoidance algorithm for swarm of quadrotor unmanned aerial vehicle (UAV) |
title_fullStr |
Obstacle avoidance algorithm for swarm of quadrotor unmanned aerial vehicle (UAV) |
title_full_unstemmed |
Obstacle avoidance algorithm for swarm of quadrotor unmanned aerial vehicle (UAV) |
title_sort |
obstacle avoidance algorithm for swarm of quadrotor unmanned aerial vehicle (uav) |
publisher |
Animo Repository |
publishDate |
2016 |
url |
https://animorepository.dlsu.edu.ph/etd_masteral/5206 |
_version_ |
1802997435673346048 |