One of the issues that have garnered little attention, but that is nevertheless important for developing practical robots, is optimal walking conditions like power consumption during walking. The main contribution of this research is to prepare a correct walking pattern for humans who have a problem with their walking and also study the effect of average motion speed on optimal power consumption. In this study, we firstly optimize the stability and minimize the power consumption of the robot during the single support phase using parameter optimization. Our approach is based on the well-known Zero Moment Point method to calculate the stability of the proposed biped robot. Secondly, we performed experiments on healthy male, age 29 years, to analyze human walking by placing 28 markers, attached to anatomical positions and two power plates for a distance of more than one gait cycle at an average speed of 1.23 ± 0.1 m s−1 validate our results for motion analysis of correct walking ability. Our model was continuously validated by comparing the results of our empirical evaluation against the prediction of our model. The errors between experimental test and our prediction were about 4%–11% for the joint trajectories and about 0.2%–0.5% for the ground reaction forces which is acceptable for our prediction. Due to the presented model and optimized issue and predicted path, the robot can move like a person in a way that has maximum stability along with the minimum power consumption. Finally, the robot was able to walk like a specific person that we considered. This study is a case study and also can be generalized to all samples and can perform these procedures to another person’s with different features.

中文翻译：

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双足机器人的平均运动速度和最佳功耗

很少受到关注但对于开发实用机器人仍然很重要的问题之一是最佳步行条件，例如步行期间的功耗。这项研究的主要贡献是为行走有问题的人类准备正确的行走模式，并研究平均运动速度对最佳功耗的影响。在这项研究中，我们首先通过参数优化优化了机器人在单支撑阶段的稳定性并最小化了机器人的功耗。我们的方法基于众所周知的零矩点方法来计算所提出的双足机器人的稳定性。其次，我们对 29 岁的健康男性进行了实验，通过放置 28 个标记来分析人类行走，-1验证我们对正确行走能力的运动分析的结果。通过将我们的经验评估结果与我们模型的预测进行比较，我们的模型得到了不断的验证。实验测试与我们的预测之间的误差对于关节轨迹约为 4%–11%，对于地面反作用力约为 0.2%–0.5%，这对于我们的预测是可以接受的。由于提出的模型和优化的问题和预测的路径，机器人可以像人一样以具有最大稳定性和最小功耗的方式移动。最后，机器人能够像我们认为的特定人一样行走。这项研究是一个案例研究，也可以推广到所有样本，并且可以对具有不同特征的另一个人执行这些程序。