Title
Minimising computational complexity of the RRT algorithm a practical approach
Abstract
Sampling based techniques for robot motion planning have become more widespread during the last decade. The algorithms however, still struggle with for example narrow passages in the configuration space and suffer from high number of necessary samples, especially in higher dimensions. A widely used method is Rapidly-exploring Random Trees (RRT's). One problem with this method is the nearest neighbour search time, which grows significantly when adding a large number of vertices. We propose an algorithm which decreases the computation time, such that more vertices can be added in the same amount of time to generate better trajectories. The algorithm is based on subdividing the configuration space into boxes, where only specific boxes needs to be searched to find the nearest neighbour. It is shown that the computational complexity is lowered from a theoretical point of view. The result is an algorithm that can provide better trajectories within a given time period, or alternatively compute trajectories faster. In simulation the algorithm is verified for a simple RRT implementation and in a more specific case where a robot has to plan a path through a human inhabited environment.
Year
DOI
Venue
2011
10.1109/ICRA.2011.5979540
Robotics and Automation
Keywords
Field
DocType
computational complexity,minimisation,mobile robots,path planning,random processes,sampling methods,search problems,trees (mathematics),RRT algorithm,computational complexity,nearest neighbour search time,path planning,rapidly exploring random trees,robot motion planning
Motion planning,Mathematical optimization,Algorithm design,Stochastic process,Algorithm,Mathematics,Trajectory,Mobile robot,Configuration space,Computation,Computational complexity theory
Conference
Volume
Issue
ISSN
2011
1
1050-4729
ISBN
Citations 
PageRank 
978-1-61284-386-5
4
0.53
References 
Authors
11
3
Name
Order
Citations
PageRank
Mikael Svenstrup1806.11
Thomas Bak2838.31
Hans Jørgen Andersen316719.41