SRRT* - a probabilistic optimal trajectory planner for problematic area structures

作     者：Hess, Robin Jerg, Roland Lindeholz, Tobias Eck, Daniel Schilling, Klaus 

作者机构：Zentrum fur Telematik e.V. Magdalene-Schoch-Straße 5 Würzburg97074 Germany CS VII Universty of Würzburg Am Hubland Würzburg97074 Germany 

出 版 物：《IFAC-PapersOnLine》 

年 卷 期：2016年第49卷第30期

页      面：331-336页

核心收录：

主　　题：Motion planning Image segmentation Robot programming Trajectories Trees (mathematics) Autonomous Mobile Robot Critical environment Environmental structure Optimal trajectories Rapidly exploring random trees Segmentation methods Water shed algorithm Watershed segmentation 

摘      要：This paper extends the well known efficient RRT* algorithm to handle special environmental structures, such as narrow passages. By applying the watershed algorithm, inspired by image processing, a segmentation component is added to solve the given problem. Therefore the traditional watershed segmentation competes against the newly developed center marker watershed algorithm and the results of different experiments, combining both segmentation methods with the Rapidly Exploring Random Tree* (RRT*) algorithm to the Segmented Rapidly Exploring Random Tree* (SRRT*), are compared for several critical environments. It is shown, the whole trajectory planning process benefits from the segmentation and the SRRT*, using the new center marker watershed, outer performs the traditional RRT* method. © 2016