Optimization-based motion retargeting integrating spatial and dynamic constraints for humanoid
Optimization-based motion retargeting integrating spatial and dynamic constraints for humanoid
复制标题
基于优化的运动重定向集成了人形机器人的空间和动态约束
DOI：
10.1109/isr.2013.6695715
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
吉田英一、中岡慎一郎
中科院分区：
文献类型：
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作者：
Thomas Moulard;吉田英一、中岡慎一郎
在这篇文章中，我们提出了一种基于优化的重定目标方法，用于精确复制仿人机器人捕捉到的人类运动。我们同时考虑了重定目标的两个重要方面：空间关系和机器人动力学模型。前者基于交互网格处理身体各部分之间的空间关系，以自然的方式跟随人体运动，而后者则以满足扭矩限制或动平衡等动态约束的方式来适应所产生的运动。我们将交互网格和动力学约束集成在一个统一的优化框架中，与以往单独执行这些过程相比，这有利于人形机器人产生自然运动。我们通过将采集到的人类数据转换成类人机器人的一系列姿势验证了该方法的基本有效性。
In this paper, we present an optimizationbased retargeting method for precise reproduction of captured human motions by a humanoid robot. We take into account two important aspects of retargeting simultaneously: spatial relationship and robot dynamics model. The former takes care of the spatial relationship between the body parts based on “interaction mesh” to follow the human motion in a natural manner, whereas the latter adapts the resulting motion in such a way that the dynamic constraints such as torque limit or dynamic balance are being satisfied. We have integrated the interaction mesh and the dynamic constraints in a unified optimization framework, which is advantageous for generation of natural motions by a humanoid robot compared to previous work that performs those processes separately. We have validated the basic effectiveness of the proposed method with a sequence of postures converted from captured human data to a humanoid robot.