3D environment mapping using the Kinect V2 and path planning based on RRT algorithms
This paper describes a 3D path planning system that is able to provide a solution trajectory for the automatic control of a robot. The proposed system uses a point cloud obtained from the robot workspace, with a Kinect V2 sensor to identify the interest regions and the obstacles of the environment....
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/103909 |
| Acceso en línea: | https://hdl.handle.net/2117/103909 https://dx.doi.org/10.3390/electronics5040070 |
| Access Level: | acceso abierto |
| Palabra clave: | Mobile robots--Automatic control path planning RRT RRT* point cloud registration 3D modeling mobile robotics RGB-D segmentation computational geometry Robots mòbils -- Control automàtic Àrees temàtiques de la UPC::Informàtica::Robòtica |
| Sumario: | This paper describes a 3D path planning system that is able to provide a solution trajectory for the automatic control of a robot. The proposed system uses a point cloud obtained from the robot workspace, with a Kinect V2 sensor to identify the interest regions and the obstacles of the environment. Our proposal includes a collision-free path planner based on the Rapidly-exploring Random Trees variant (RRT*), for a safe and optimal navigation of robots in 3D spaces. Results on RGB-D segmentation and recognition, point cloud processing, and comparisons between different RRT* algorithms, are presented. |
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