International Journal of Robotics Research
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Handling multiple objectives with particle swarm optimization
IEEE Transactions on Evolutionary Computation
A review of gait optimization based on evolutionary computation
Applied Computational Intelligence and Soft Computing - Special issue on theory and applications of evolutionary computation
On the use of human instruction for improving the behavior of RoboCup soccer agents
Artificial Life and Robotics
Application of the "Alliance algorithm" to energy constrained gait optimization
Robot Soccer World Cup XV
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Controlling a biped robot with a high degree of freedom to achieve stable and straight movement patterns is a complex problem. With growing computational power of computer hardware, high resolution real time simulation of such robot models has become more and more applicable. This paper presents a novel approach to generate bipedal gait for humanoid locomotion. This approach is based on modified Truncated Fourier Series (TFS) for generating angular trajectories. It is also the first time that Particle Swarm Optimization (PSO) is used to find the best angular trajectory and optimize TFS. This method has been implemented on Simulated NAO robot in Robocup 3D soccer simulation environment (rcssserver3d). To overcome inherent noise of the simulator we applied a Resampling algorithm which could lead the robustness in nondeterministic environments. Experimental results show that PSO optimizes TFS faster and better than GA to generate straighter and faster humanoid locomotion.