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A migrant-inspired path planning algorithm for obstacle run usingparticle swarm optimization, potential field navigation, and fuzzy logiccontroller

Published online by Cambridge University Press:  09 September 2016

Ping-Huan Kuo ,
Tzuu-Hseng S. Li ,
Guan-Yu Chen ,
Ya-Fang Ho  and
Chih-Jui Lin
Ping-Huan Kuo
Affiliation:
aiRobots Lab, Department of Electrical and Electronic Engineering, National Cheng Kung University, Tainan 70101, Taiwan, ROC e-mail: coll22000@hotmail.com, thsli@mail.ncku.edu.tw, hank2579@hotmail.com, makinosakuya@hotmail.com, lirere0225@hotmail.com
Tzuu-Hseng S. Li
Affiliation:
aiRobots Lab, Department of Electrical and Electronic Engineering, National Cheng Kung University, Tainan 70101, Taiwan, ROC e-mail: coll22000@hotmail.com, thsli@mail.ncku.edu.tw, hank2579@hotmail.com, makinosakuya@hotmail.com, lirere0225@hotmail.com
Guan-Yu Chen
Affiliation:
aiRobots Lab, Department of Electrical and Electronic Engineering, National Cheng Kung University, Tainan 70101, Taiwan, ROC e-mail: coll22000@hotmail.com, thsli@mail.ncku.edu.tw, hank2579@hotmail.com, makinosakuya@hotmail.com, lirere0225@hotmail.com
Ya-Fang Ho
Affiliation:
aiRobots Lab, Department of Electrical and Electronic Engineering, National Cheng Kung University, Tainan 70101, Taiwan, ROC e-mail: coll22000@hotmail.com, thsli@mail.ncku.edu.tw, hank2579@hotmail.com, makinosakuya@hotmail.com, lirere0225@hotmail.com
Chih-Jui Lin
Affiliation:
aiRobots Lab, Department of Electrical and Electronic Engineering, National Cheng Kung University, Tainan 70101, Taiwan, ROC e-mail: coll22000@hotmail.com, thsli@mail.ncku.edu.tw, hank2579@hotmail.com, makinosakuya@hotmail.com, lirere0225@hotmail.com
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Abstract

Obstacle avoidance is an important issue in robotics. In this paper, the particleswarm optimization (PSO) algorithm, which is inspired by the collectivebehaviors of birds, has been designed for solving the obstacle avoidanceproblem. Some animals that travel to the different places at a specific time ofthe year are called migrants. The migrants also represent the particles of PSOfor defining the walking paths in this work. Migrants consider not only thecollective behaviors, but also geomagnetic fields during their migration innature. Therefore, in order to improve the performance and the convergence speedof the PSO algorithm, concepts from the migrant navigation method have beenadopted for use in the proposed hybrid particle swarm optimization (H-PSO)algorithm. Moreover, the potential field navigation method and the designedfuzzy logic controller have been combined in H-PSO, which provided a goodperformance in the simulation and the experimental results. Finally, theFederation of International Robot-soccer Association (FIRA) HuroCup Obstacle RunEvent has been chosen for validating the feasibility and the practicability ofthe proposed method in real time. The designed adult-sized humanoid robot alsoperformed well in the 2015 FIRA HuroCup Obstacle Run Event through utilizing theproposed H-PSO.

Information

Type
Review Article
Information
The Knowledge Engineering Review , Volume 32 , 2017 , e5
Copyright
© Cambridge University Press, 2017 

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