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Motion Planning by T‐RRT with Potential Function for Vertical Articulated Robots
Author(s) -
KABUTAN RYO,
NISHIDA TAKESHI
Publication year - 2018
Publication title -
electrical engineering in japan
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.136
H-Index - 28
eISSN - 1520-6416
pISSN - 0424-7760
DOI - 10.1002/eej.23103
Subject(s) - random tree , motion planning , path (computing) , robot , sampling (signal processing) , computer science , function (biology) , tree (set theory) , motion (physics) , artificial intelligence , mathematical optimization , simulation , mathematics , computer vision , mathematical analysis , filter (signal processing) , evolutionary biology , biology , programming language
SUMMARY RRT (rapidly exploring random tree) with random sampling is an effective method for path planning, and is often used for robot manipulators. The RRT has many modified methods for applying various problems and conditions. Particularly, T‐RRT (Transition‐based RRT) one of those has advantage that it is able to adopt arbitrary evaluation function. In this paper, a novel path planning method based on the T‐RRT is proposed for ensuring “quality” of a generated path. Then, its effectiveness is evaluated via comparison with other sampling‐based methods using simulation of the industrial robot having seven DOFs.