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An Approach to Optimize the Path of Humanoids using Adaptive Ant Colony Optimization

摘要In the emerging area of humanoid robotics,path planning and autonomous navigation have evolved as one of the most promising area of research.This paper deals with the design and development of a novel navigational controller to guide humanoids in cluttered environments.The basic parameters of the ant colony optimization technique have been modified to have enhanced control as Adaptive Ant Colony Optimization (AACO).The controller that has been implemented in the humanoids receives sensory information about obstacle distances as inputs and provides required turning angle as output to reach the specified target position.The proposed controller has been tested in both simulated and experimental environments created under laboratory conditions,and a good agreement has been observed between the simulation and experiment results.Here,both static and dynamic path planning have been attempted.Finally,the proposed controller has also been tested against other existing techniques to validate the efficiency of the AACO in path planning problems.

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作者单位 Robotics Laboratory, Mechanical Engineering Department, National Institute of Technology, Rourkelao769008, Odisha, India [1]
DOI 10.1007/s42235-018-0051-7
发布时间 2018-08-27(万方平台首次上网日期,不代表论文的发表时间)
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仿生工程学报(英文版)

仿生工程学报(英文版)

2018年15卷4期

623-635页

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