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Assistive Humanoid Robot Arm Motion Generation in Dynamic Environment Based on Neural Networks

Genci Capi1, Zulkifli Mohamed1, Mitsuki Kitani1 , and Shin-ichiro Kaneko2
1.University of Toyama, Toyama, Japan
2.Toyama National College of Technology, Toyama, Japan
Abstract—Assistive humanoid robots operating in everyday life environments have to autonomously navigate and perform several tasks. In this paper we propose a neural network based humanoid robot navigation and arm trajectory generation. The robotic system, which is equipped with a visual sensor, laser range finders, navigates in the environment. The neural controllers generate the robot arm motion in dynamic environments where obstacles of different shapes and positions are present. We have implemented the proposed algorithms in the hardware of a mobile humanoid robot. The robot can navigate in the environment reach the table and pick the target object. The motion generated yield good results in both simulation and experimental environments.

Index Terms—arm motion generation, neural network, optimization, dynamic environment

Cite: Genci Capi, Zulkifli Mohamed, Mitsuki Kitani, and Shin-ichiro Kaneko, "Assistive Humanoid Robot Arm Motion Generation in Dynamic Environment Based on Neural Networks," Journal of Automation and Control Engineering, Vol. 3, No. 2, pp. 115-121, April, 2015. doi: 10.12720/joace.3.2.115-121
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