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基于预测控制的手臂运动估计

Arm Motion Estimation Based on Predictive Control

  • 摘要: 交互信息的获取是决定分布式虚拟现实系统沉浸感和真实感好坏的关键因素,通过对交互者手臂位置的跟踪,可以提供更加直观和谐的人机交互模式.为了跟踪手臂的运动轨迹,提出一种基于模糊预测控制理论的手臂运动估计算法——FPC-AME,通过提取来自2个同步摄像机的实时图像中交互者腕部和肘部的标识环信息,对手臂位置进行预测和估计,实现形象化的六自由度手臂导航.实验结果表明,在环境光照基本稳定的条件下,文中算法可以生成稳定、精确的手臂位置信息.相关研究对虚拟环境下的沉浸式交互具有较高的理论意义和实用价值.

     

    Abstract: The interactive information capture is an important factor to enhance the immersed feeling and sense of reality caused in VR systems.By tracking the arm's location of the interactive person,more harmonious way of human-computer interaction (HCI) can be provided.To track the arm motion,the paper presents an arm motion estimation algorithm based on fuzzy predictive control theory (FPC-ARM),through which the feature rings from real-time images can be extracted and the arm's position can be predicted,to achieve arm navigation operations.The test result indicates that,under the condition with stable environment illumination,the algorithm can stably produce precise information of arm's location.The work is of significance in theory and valuable in practice to immersing VR systems.

     

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