Abstract
In this paper, we propose a path planning system for autonomous navigation of unmanned aerial vehicle based on a Rapidly-exploring Random Trees (RRT) combination of RRT* Goal and Limit. The system includes a point cloud obtained from the vehicle workspace with a RGB-D sensor, an identification module for interest regions and obstacles of the environment, and a collision-free path planner based on RRT for a safe and optimal navigation of vehicles in 3D spaces.
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Acknowledgement
This work is part of the projects VisualNavDrone 2016-PIC-024 and MultiNavCar 2016-PIC-025, from the Universidad de las Fuerzas Armadas ESPE, directed by Dr. Wilbert G. Aguilar.
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Aguilar, W.G., Morales, S., Ruiz, H., Abad, V. (2017). RRT* GL Based Optimal Path Planning for Real-Time Navigation of UAVs. In: Rojas, I., Joya, G., Catala, A. (eds) Advances in Computational Intelligence. IWANN 2017. Lecture Notes in Computer Science(), vol 10306. Springer, Cham. https://doi.org/10.1007/978-3-319-59147-6_50
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DOI: https://doi.org/10.1007/978-3-319-59147-6_50
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