International Journal of Control, Automation, and Systems 2023; 21(11): 3540-3550
https://doi.org/10.1007/s12555-023-0383-x
© The International Journal of Control, Automation, and Systems
This paper presents Ex-RRT*, a modification of the rapidly-exploring random tree star (RRT*) algorithm that allows the robot to avoid obstacles with a margin. RRT* generates the shortest path to a destination while avoiding obstacles. However, if the robot’s embedded trajectory generation algorithm interpolates the waypoints generated by the RRT* to make a motion, collisions may occur with the edges or overhang of obstacles. This algorithm adds a cost function for the distance from each node to the nearest obstacle to ensure that the waypoints generated by the path planner have an appropriate margin for obstacles. It is designed to provide safer control from collisions when each robot’s embedded trajectory generation algorithm operates by interpolating waypoints derived by path planning. Through simulation, we compare the proposed Ex-RRT* and conventional RRT* with performance indices such as total distance traveled and collision avoidance norm. Experiments are conducted on the task of moving an object inside a box with a commercial robot to validate the proposed algorithm. The proposed algorithm generates paths with improved safety and can be applied to various robotic arms and mobile platforms.
Keywords Collision avoidance, path planning, rapidly-exploring random tree, robot manipulation, safe path generation.
International Journal of Control, Automation, and Systems 2023; 21(11): 3540-3550
Published online November 1, 2023 https://doi.org/10.1007/s12555-023-0383-x
Copyright © The International Journal of Control, Automation, and Systems.
Subin Lim and Sangrok Jin*
Pusan National University
This paper presents Ex-RRT*, a modification of the rapidly-exploring random tree star (RRT*) algorithm that allows the robot to avoid obstacles with a margin. RRT* generates the shortest path to a destination while avoiding obstacles. However, if the robot’s embedded trajectory generation algorithm interpolates the waypoints generated by the RRT* to make a motion, collisions may occur with the edges or overhang of obstacles. This algorithm adds a cost function for the distance from each node to the nearest obstacle to ensure that the waypoints generated by the path planner have an appropriate margin for obstacles. It is designed to provide safer control from collisions when each robot’s embedded trajectory generation algorithm operates by interpolating waypoints derived by path planning. Through simulation, we compare the proposed Ex-RRT* and conventional RRT* with performance indices such as total distance traveled and collision avoidance norm. Experiments are conducted on the task of moving an object inside a box with a commercial robot to validate the proposed algorithm. The proposed algorithm generates paths with improved safety and can be applied to various robotic arms and mobile platforms.
Keywords: Collision avoidance, path planning, rapidly-exploring random tree, robot manipulation, safe path generation.
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