Variant Step Size RRT: An Efficient Path Planner for UAV in Complex Environments
Refereed conference paper presented and published in conference proceedings


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AbstractRapidly Exploring Random Tree (RRT) is a popular way for motion planning especially in high-dimensional environments. Efficient path planner is prerequisite for highspeed Unmanned Aerial Vehicles (UAV). In this paper, we proposed a path planning algorithm for UAV in complex environments based on RRT. Our contributions are mainly on three aspects. Firstly we proposed a novel RRT algorithm which can explore the complex environment more rapidly. It is achieved by adaptively changes the step size of the tree according to the location of obstacles. The proposed method also takes random points failed to pass the collision check process as indicators to speed up exploring. We proposed an optimizaion algorithm which can get the optimal path without time-consuming sampling. The simulation result demonstrates that our proposed can work efficiently
All Author(s) ListWang CQ, Meng MQH
Name of ConferenceIEEE International Conference on Real-time Computing and Robotics (RCAR)
Start Date of Conference06/06/2016
End Date of Conference10/06/2016
Place of ConferenceAngkor Wat, Cambodia
Country/Region of ConferenceCambodia
Proceedings TitleIEEE International Conference on Real-time Computing and Robotics (RCAR)
Title of Publication2016 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (IEEE RCAR)
Year2016
Month6
Pages555 - 560
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesComputer Science, Theory & Methods;Engineering, Electrical & Electronic;Robotics;Computer Science;Engineering;Robotics

Last updated on 2020-20-10 at 03:44