An obstacle-based rapidly-exploring random tree
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Tree-based path planners have been shown to be well suited to solve various high dimensional motion planning problems. Here we present a variant of the Rapidly-Exploring Random Tree (RRT) path planning algorithm that is able 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. Indeed, whereas the standard RRT can face difficulties planning in a narrow passage, the tree based planner presented here works best in these areas. 2006 IEEE.
name of conference
Proceedings. 2006 Conference on International Robotics and Automation
Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006.
author list (cited authors)
Rodriguez, .., Xinyu Tang, .., Jyh-Ming Lien, .., & Amato, N. M.
complete list of authors