Quick-RRT*: Triangular inequality-based implementation of RRT* with improved initial solution and convergence rate

作者：

Highlights：

• Sampling-based algorithms are commonly used in motion planning problems.

• The RRT* algorithm incrementally builds a tree of motion to find a solution.

• Taking a shortcut to the ancestry increases the convergence rate to the optimal.

• Combination with sampling strategies further improves the performance.

摘要

•Sampling-based algorithms are commonly used in motion planning problems.•The RRT* algorithm incrementally builds a tree of motion to find a solution.•Taking a shortcut to the ancestry increases the convergence rate to the optimal.•Combination with sampling strategies further improves the performance.

论文关键词：RRT,Sampling-based algorithms,Navigation,Motion planning,Optimal path planning

论文评审过程：Received 11 September 2018, Revised 21 December 2018, Accepted 9 January 2019, Available online 9 January 2019, Version of Record 15 January 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.01.032