Vision based quadrotor navigation
Quadrotors have been a subject of interest for military for surveillance and warfare purpose since 19th century. However recently they are becoming increasingly popular amongst RC hobby enthusiasts and researcher alike due to their agility, maneuverability and Vertical Takeoff and Landing capability...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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2013
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| Online Access: | http://hdl.handle.net/10356/55083 |
| _version_ | 1811683117392461824 |
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| author | Gaurav Gupta. |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Gaurav Gupta. |
| author_sort | Gaurav Gupta. |
| collection | NTU |
| description | Quadrotors have been a subject of interest for military for surveillance and warfare purpose since 19th century. However recently they are becoming increasingly popular amongst RC hobby enthusiasts and researcher alike due to their agility, maneuverability and Vertical Takeoff and Landing capability. The rapid innovation and research in this area motivates us to explore the integration of computer vision with quadrotors to make a fully autonomous system in GPS enabled as well as GPS denied environments.
For the first phase of the project we used a commercial off the shelf AR. Drone quadrotor to integrate with ROS (Robot operating system) in order to chase a target tag. The AR. Drone is a ready to fly system, which uses Wi Fi to connect to a remote computer running ROS node to communicate with AR. Drone. The remote computer node takes the navigation data input from AR. Drone, does position estimation relative to tag and returns a command back to AR. Drone to maintain its position over the tag. The system performed well. The AR. Drone flew for 40 seconds and maintained its position over a tag moving in arbitrary fashion.
The second phase of the project concerns with developing a more powerful modular quadrotor with higher payload capacity and longer battery life. This phase was not the original objective of the project but was included later on considering the limitations of AR. Drone. A DJI Flamewheel quadrotor kit, Ardupilot Mega Autopilot and 3DR telemetry system was chosen to implement and improve the functionality of AR. Drone. The quadrotor was assembled and tested successfully, however the integration of camera and implementation of image processing over ROS still remains to be done. |
| first_indexed | 2024-10-01T04:07:38Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/55083 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:07:38Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/550832023-03-03T20:33:05Z Vision based quadrotor navigation Gaurav Gupta. School of Computer Engineering Suresh Sundaram DRNTU::Engineering::Computer science and engineering Quadrotors have been a subject of interest for military for surveillance and warfare purpose since 19th century. However recently they are becoming increasingly popular amongst RC hobby enthusiasts and researcher alike due to their agility, maneuverability and Vertical Takeoff and Landing capability. The rapid innovation and research in this area motivates us to explore the integration of computer vision with quadrotors to make a fully autonomous system in GPS enabled as well as GPS denied environments. For the first phase of the project we used a commercial off the shelf AR. Drone quadrotor to integrate with ROS (Robot operating system) in order to chase a target tag. The AR. Drone is a ready to fly system, which uses Wi Fi to connect to a remote computer running ROS node to communicate with AR. Drone. The remote computer node takes the navigation data input from AR. Drone, does position estimation relative to tag and returns a command back to AR. Drone to maintain its position over the tag. The system performed well. The AR. Drone flew for 40 seconds and maintained its position over a tag moving in arbitrary fashion. The second phase of the project concerns with developing a more powerful modular quadrotor with higher payload capacity and longer battery life. This phase was not the original objective of the project but was included later on considering the limitations of AR. Drone. A DJI Flamewheel quadrotor kit, Ardupilot Mega Autopilot and 3DR telemetry system was chosen to implement and improve the functionality of AR. Drone. The quadrotor was assembled and tested successfully, however the integration of camera and implementation of image processing over ROS still remains to be done. Bachelor of Engineering (Computer Engineering) 2013-12-12T04:37:26Z 2013-12-12T04:37:26Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/55083 en Nanyang Technological University 88 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Gaurav Gupta. Vision based quadrotor navigation |
| title | Vision based quadrotor navigation |
| title_full | Vision based quadrotor navigation |
| title_fullStr | Vision based quadrotor navigation |
| title_full_unstemmed | Vision based quadrotor navigation |
| title_short | Vision based quadrotor navigation |
| title_sort | vision based quadrotor navigation |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | http://hdl.handle.net/10356/55083 |
| work_keys_str_mv | AT gauravgupta visionbasedquadrotornavigation |