A Path Planning Method Based on Adaptive Genetic Algorithm for a Shape-shifting Robot | Zendy

Mengxin Li | Zendy; XingHua Xia | Zendy; Ying Zhang | Zendy; Jinguo Liu | Zendy

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A Path Planning Method Based on Adaptive Genetic Algorithm for a Shape-shifting Robot

Author(s) -

Mengxin Li,

XingHua Xia,

Ying Zhang,

Jinguo Liu

Publication year - 2010

Publication title -

computer and information science

Language(s) - English

Resource type - Journals

eISSN - 1913-8997

pISSN - 1913-8989

DOI - 10.5539/cis.v3n4p208

Subject(s) - computer science , motion planning , robot , path (computing) , genetic algorithm , potential field , field (mathematics) , any angle path planning , variation (astronomy) , algorithm , artificial intelligence , simulation , machine learning , mathematics , physics , geophysics , pure mathematics , astrophysics , programming language , geology

A shape-shifting robot with changeable configurations can accomplish search and rescue tasks which could not be achieved by manpower sometimes. The accessibility of this robot to uneven environment was efficiently enlarged by changing its configuration. In this paper, a path planning method is presented that integrates the reconfigurable ability of the robot with the potential field law. An adaptive genetic algorithm is applied to solve effectively the local minimum problem. The experiments show that the robot’s configurations can be changed to perform the path planning with the environmental variation. Moreover, the path has been shortened effectively.

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