Heuristic approach to robot path planning based on task requirements using a genetic algorithm

Chi Haur Sheu*, Kuu-Young Young

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


In order to enhance integration between CAD and robots, we propose a scheme to plan kinematically feasible paths in the presence of obstacles based on task requirements. Thus, the feasibility of a planned path from a CAD system is assured before the path is sent for execution. The proposed scheme uses a heuristic approach to deal with a rather complex search space, involving high-dimensional C-space obstacles and task requirements specified in Cartesian space. When the robot is trapped by the local minimum in the potential field related to the heuristic, a genetic algorithm is then used to find a proper intermediate location that will guide it to escape out of the local minimum. For demonstration, simulations based on using a PUMA-typed robot manipulator to perform different tasks in the presence of obstacles were conducted. The proposed scheme can also be used for mobile robot planning.

Original languageEnglish
Pages (from-to)65-88
Number of pages24
JournalJournal of Intelligent and Robotic Systems: Theory and Applications
Issue number1
StatePublished - 1 May 1996

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