This paper proposes a method of energy-efficient trajectory planning for bipedal walking robots. In this study, we plan hip and foot trajectories in Cartesian space using polynomial interpolation. The seven key parameters which define the hip and foot trajectories are optimized by genetic algorithm (GA). Since the hip trajectory is crucial to the stability and walking performance of bipedal robot, we introduce a way to increase hip trajectory's variation by extending the order of the interpolated polynomial and using a set of key parameters. To ensure stable walking motion, we employ the zero-moment-point (ZMP) as the stability criterion. The effectiveness of our proposed method is verified by two simulation examples (flat terrain walking and slope walking) of a humanoid robot named NUSBIP-II.

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