• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.424-426
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• 2005

We propose an analytic trajectory planning method using a wavelet neural network (WNN) for a natural and stable locomotion of the 9-link biped robot. We design a appropriate locomotion, which have a kick-action, by means of a ballastic walking model condition. In this paper, a WNN is used to interpolate the trajectory planed by the analytic method. Finally, we show the proposed trajectories through the computer simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.833-839
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• 2004

This paper proposes a method that minimizes the consumed energy by searching the optimal locations of the mass centers of links composing of a biped robot using Real-Coded Genetic Algorithm. Generally, in order to utilize optimization algorithms, the system model and design variables must be defined. Firstly, the proposed model is a 6-DOF biped robot composed of seven links, since many of the essential characteristics of the human walking motion can be captured with a seven-link planar biped walking in the saggital plane. Next, Fourth order polynomials are used for basis functions to approximate the walking gait. The coefficients of the fourth order polynomials are defined as design variables. In order to use the method generating the optimal gait trajectory by searching the locations of mass centers of links, three variables are added to the total number of design variables. Real-Coded GA is used for optimization algorithm by reason of many advantages. Simulations and the comparison of three methods to generate gait trajectories including the GCIPM were performed. They show that the proposed method can decrease the consumed energy remarkably and be applied during the design phase of a robot actually.