ST-FMT: A Fast Optimal Global Motion Planning for Mobile Robot

This article introduces a secure tunnel fast marching tree motion planning algorithm (ST-FMT*) to provide a secure and optimal path quickly for a mobile robot. The proposed ST-FMT* consists of preprocessing and exploring procedures, which are responsible for establishing a secure tunnel and optimizi...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) Vol. 69; no. 4; pp. 3854 - 3864
Main Authors: Wu, Zheng, Chen, Yanjie, Liang, Jinglin, He, Bingwei, Wang, Yaonan
Format: Journal Article
Language:English
Published: New York IEEE 01.04.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Collision avoidance
Convergence
Convergence performance
fast marching tree algorithm (FMT)
Heuristic algorithms
Mobile robots
Motion planning
Optimization
Planning
Preprocessing
Robot dynamics
Robots
Sampling
secure tunnel
Space exploration
Trajectory
Transportation
Tunnels
Voronoi graphs
ISSN:0278-0046, 1557-9948
Online Access:Get full text
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Summary:This article introduces a secure tunnel fast marching tree motion planning algorithm (ST-FMT*) to provide a secure and optimal path quickly for a mobile robot. The proposed ST-FMT* consists of preprocessing and exploring procedures, which are responsible for establishing a secure tunnel and optimizing the path, respectively. In the preprocessing process, the generalized Voronoi graph is adopted to build an equidistant roadmap and generates an initial collision-free solution rapidly. Then, a secure tunnel is established via the minimum distance from the obstacles to the initial solution to facilitate the concentration of sampling. In the exploration process, the FMT* with uniform sampling within the secure tunnel is utilized to find the optimal solution with high computational efficiency. The theoretical analyses of the ST-FMT* are provided. In a series of scenarios evaluation, the ST-FMT* exhibits fast convergence to the optimal solution in different environments. Besides, the effectiveness of the ST-FMT* is verified in a transportation experiment using a Turtlebot2 mobile robot.
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ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2021.3075852