Difference between revisions of "PatrolDrone"
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| + | Real-time exploration and mapping of environment with low-cost drone and low-cost camera, using PTAM and special exploration heuristics taking into account both the nature of the drone and that of the fast algorithm. | ||
| + | The three views are: a view from the external camera, the view of the on-board camera, with point cloud visualization, a view of the obtained map. | ||
| − | *[http://www.youtube.com/watch?v=tbkakWK_fKA External link] | + | |
| − | *[http://www.youtube.com/watch?v=ybcBYUrTDZw External link] | + | <!--*[http://www.youtube.com/watch?v=tbkakWK_fKA External link] *[http://www.youtube.com/watch?v=ybcBYUrTDZw External link]}}--> |
Revision as of 10:23, 11 July 2013
PatrolDrone
| |
| Short Description: | The goal of the project is to develop a drone able to patrol an indoor ambient to search por intruders |
| Coordinator: | AndreaBonarini (andrea.bonarini@polimi.it) |
| Tutor: | AndreaBonarini (andrea.bonarini@polimi.it) |
| Collaborator: | |
| Students: | DanieleIasella (daniele.iasella@mail.polimi.it), StefanoFossati (stefanofossati.86@gmail.com) |
| Research Area: | Robotics |
| Research Topic: | Robot development |
| Start: | 24/10/2012 |
| Status: | Active |
| Level: | Ms |
Goal
The aim of the project is to develop an architecture for indoor autonomous exploration, including door and hole detection ability.
Motivation
Environment reconstruction and exploration with limited sensoring capacity (monocular view, altitude sensor, gyroscope) using the low cost quadrocopter AR drone 2.0
Useful readings
SLAM
- SLAM [1]
- EKF [2]
- PTAM [3]
- Indoor Navigation with Laser Scanners [4]
- Depth Camera Localization and Navigation [5]
- BIM Based Navigation [6]
- Visibility of Point Clouds and Exploratory Path Planning in Unknown environment [7]
ROS packages
Video
Real-time exploration and mapping of environment with low-cost drone and low-cost camera, using PTAM and special exploration heuristics taking into account both the nature of the drone and that of the fast algorithm. The three views are: a view from the external camera, the view of the on-board camera, with point cloud visualization, a view of the obtained map.
