Research Article
A Novel Stereo based Obstacle Avoidance System for Unmanned Aerial Vehicles
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 131 - Issue 13 |
| Published: December 2015 |
| Authors: Arjun Chakraborty, Bhargav Srinivasan |
10.5120/ijca2015907550
|
Arjun Chakraborty, Bhargav Srinivasan . A Novel Stereo based Obstacle Avoidance System for Unmanned Aerial Vehicles. International Journal of Computer Applications. 131, 13 (December 2015), 39-42. DOI=10.5120/ijca2015907550
@article{ 10.5120/ijca2015907550,
author = { Arjun Chakraborty,Bhargav Srinivasan },
title = { A Novel Stereo based Obstacle Avoidance System for Unmanned Aerial Vehicles },
journal = { International Journal of Computer Applications },
year = { 2015 },
volume = { 131 },
number = { 13 },
pages = { 39-42 },
doi = { 10.5120/ijca2015907550 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2015
%A Arjun Chakraborty
%A Bhargav Srinivasan
%T A Novel Stereo based Obstacle Avoidance System for Unmanned Aerial Vehicles%T
%J International Journal of Computer Applications
%V 131
%N 13
%P 39-42
%R 10.5120/ijca2015907550
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The use of autonomous unmanned aerial vehicle (UAV) has been on the rise. They are used to replace an ever-increasing amount of labor. There is a need for unmanned aerial systems to operate safely in the environment around them. The work in this paper aims at creating an obstacle avoidance system using Stereo Vision. The work uses standard block matching algorithms. OpenCV and the KTTI Vision Benchmark suite is used. The ArduPilot SITL simulator is used for running the algorithms and displaying the results. The droneapi is an application that is used to access the UAV’s information and describe new kinds of flight behavior. The application created is known as STOBA (Stereo Based Obstacle Avoidance), which was created to run within the ArduPilot SITL, in order to provide the mentioned obstacle avoidance capability
References
- Mackay,Randy."ArdupilotBalloonFinder."2015. https://github.com/rmackay9/ardupilot-balloon-finder
- KevinHester,”DronePythonDoc”. 2015.http://python.dronekit.io/automodule.html
- CentMesh, NCSU Centennial Research Project. “Software in the loop (SITL).”2010. http://centmesh.csc.ncsu.edu/trac/MeshBed/wiki/HardWare/Drones/Autopilot
- J. Cieśluk, Z. Gosiewski, "A Stereovision System for Real Time Obstacle Avoidance by Unmanned Aerial Vehicle", Solid State Phenomena, Vol 198, pp. 159-164, Mar. 2013.
- Kostavelis, Ioannis, Lazaros Nalpantidis, and Antonios Gasteratos. "Comparative Presentation of Real Time Obstacle Avoidance Algorithms Using Solely Stereo Vision.”, IARP/EURON International Workshop on Robotics for risky intervention and Environmental Surveillance-Maintenace, Jan. 2010.
- Kostavelis, Ioannis, Lazaros Nalpantidis, and Antonios Gasteratos.”Real –Time Algorithm for Obstacle avoidance using a Stereoscopic Camera”, Thrid Panhellenic Scientific Student Conference on Informatics, 2009
- Viet CN, Marshall IW,”Vision Based obstacle avoidance for a small Low-cost Robot”, International Conference on Advanced Robotics (ICAR), 2007
- Heiko Hirschmuller,”Semi- Global Matching- Motivation,Development and Applications”, Photogrammetric week, pp. 173-184, Sep. 2011.
- Kalva, Andreas. “Collision Detection System Using Computer Vision on Low Power Devices”, LAP Lambert Academic Publishing,2014
- Greiger Andreas, Lenz Philip, Stiller Christoph and Urtasun Racquel, “Vision meets Robotics: The KTTI Dataset”, International journal of Robotics Research (IJRR), 2013
- OpenCV Documentation. 2015. http://opencv.org.
Index Terms
Keywords