Manipulators with a hyperredundant and large aspect ratio are becoming more commonly used to detect complex and narrow spaces. The hyperredundant feature confers advantages for such manipulator types in comparison to traditional manipulators. However, they also introduce path-planning challenges. Due to the characteristics of hyperredundancy, there are countless inverse kinematics solutions, and the path-planning method that is used for traditional manipulators cannot be directly applied to these hyperredundancy manipulators in terms of the number of calculations or adaptability of the algorithm.
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