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Abstract

Samuel Rodriguez, Xinyu Tang, Jyh-Ming Lien, Nancy M. Amato, "An Obstacle-Based Rapidly-Exploring Random Tree," Technical Report, TR05-009, Parasol Laboratory, Department of Computer Science, Texas A&M University, Sep 2005.
Technical Report(ps, pdf, abstract)

Tree-based path planners have been shown to be well suited to solve various high dimensional motion planning problems. Here we present modifications that can be made to the Rapidly-Exploring Random Tree (RRT) path planning algorithm that allows it to explore narrow passages or difficult areas more effectively. We show that both workspace obstacle information and C-space information can be used when deciding which direction to grow. The method includes many ways to grow the tree, some taking into account the obstacles in the environment. This planner works best in difficult areas when planning for free flying rigid or articulated robots. Where as the standard RRT can have problems planning in a narrow passage, the tree based planner presented here works best in these narrow or difficult areas.