An Obstacle-based Rapidly-exploring Random Tree

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

Authors

• Samuel Rodríguez
• Xinyu Tang 0002
• Jyh-Ming Lien
• Nancy M. Amato

Keywords

• Motion planning
• Robots
• Space exploration
• Path planning
• Joining processes
• Orbital robotics
• Surgery
• US Department of Energy
• Shape
• Rapidly-exploring Random Tree
• Difficult Areas
• Triangular
• Degrees Of Freedom
• Standard Algorithm
• Step Length
• Area Of Space
• Probabilistic Method
• Random Orientation
• Configuration Space
• Growth Method
• Planning Methods
• Narrow Area
• Random Configuration
• Greedy Approach
• Robot Movement
• Types Of Robots
• Robot Configuration
• Medial Axis
• Target Configuration
• Source Configuration
• Fewer Calls