Quantifying the safety of the human body orientation is an important issue in human-robot interaction. Knowing the changing physical constraints on human motion can improve inspection of safe human motions and bring essential information about stability and normality of human body orientations with real-time risk assessment. Also, this information can be used in cooperative robots and monitoring systems to evaluate and interact in the environment more freely. Furthermore, the workspace area can be more deterministic with the known physical characteristics of safety. Based on this motivation, we propose a novel predictive safety model (PSM) that relies on the information of an inertial measurement unit on the human chest. The PSM encompasses a 3-Dofs spring-damper pendulum model that predicts human motion based on a safe motion dataset. The estimated safe orientation of humans is obtained by integrating a safety dataset and an elastic spring-damper model in a way that the proposed approach can realize complex motions at different safety levels. We did experiments in a real-world scenario to verify our novel proposed model. This novel approach can be used in different guidance/assistive robots and health monitoring systems to support and evaluate the human condition, particularly elders.
翻译:了解人体运动物理限制的变化,可以改进对安全人类运动的检查,并带来关于人体运动的稳定性和正常性的基本信息,同时进行实时风险评估;此外,这种信息可用于合作机器人和监测系统,以便更自由地在环境中评估和互动;此外,工作空间区域可以更加确定已知的安全物理特征;基于这一动机,我们提议了一个新的预测安全模型(PSM),该模型依赖于人体胸部惯性测量器的信息。PSM包含一个三维的弹簧式胸罩模型,该模型以安全运动数据集为基础预测人类运动的稳定性和正常性。估计人类安全方向是通过整合安全数据集和弹性弹簧灯模型获得的,这样拟议的方法可以在不同安全级别上实现复杂的运动。我们根据这一动机,在现实世界情景中进行了试验,以核实我们提出的新模型。这种新颖的方法可以用于不同的指导/定位机器人和人类监测系统,特别是用于支持和评估老年人状况。