Macro-walking instruction for biped humanoid robot

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This paper describes a macro-walking instruction strategy for a biped humanoid robot to memorize complex walking patterns systematically and effectively. In teaching various walking motions, auditory sensors are employed. Based on the sensory information, the motion of lower-limbs is created in online by a pattern generator. At the same time, the motion of the trunk and the waist is generated in online by a balance control method for walking stability. A complete walking pattern is hierarchically constructed on the basis of basic and advanced walking patterns. Using WABIAN-RV, many experimental tests are conducted, and the effectiveness of the teaching strategy is verified.

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