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Human-robot interaction based on wearable IMU sensor and laser range finder

机译:基于可穿戴IMU传感器和激光测距仪的人机交互

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摘要

Service robots are not only expected to navigate within the environment, as they also will may with people. Human tracking by mobile robots is essential for service robots and human interaction applications. In this work, the goal is to add a more natural robot-human following in front based on the normal human gait model. This approach proposes implementing and evaluating a human-robot interaction strategy, using the integration of a LRF (Laser Range Finder) tracking of human legs with wearable IMU (Inertial Measurement Unit) sensors for capturing the human movement during the gait. The work was carried out in four stages: first, the definition of the model of human-robot interaction and the control proposal were developed. Second, the parameters based on the human gait were estimated. Third, the robot and sensor integration setup are also proposed. Finally, the description of the algorithm for parameters detection is presented. In the experimental study, despite of the continuous oscillation during the walking, the parameters estimation was precise and unbiased, showing also repeatability with human linear velocities changes. The controller was evaluated with an eight-shaped curve, showing the stability of the controller even with sharp changes in the human path during real experiments.
机译:服务机器人不仅有望在环境中导航,而且还会与人一起导航。对于服务机器人和人机交互应用程序而言,移动机器人的人机跟踪至关重要。在这项工作中,目标是在正常人的步态模型的基础上,在前面增加一个更自然的机器人人追随者。该方法提出了通过将LRF(激光测距仪)跟踪人的腿与可穿戴式IMU(惯性测量单元)传感器集成在一起以实现步态捕获人的运动的方式,来实施和评估人机交互策略。这项工作分四个阶段进行:首先,开发人机交互模型的定义和控制建议。其次,基于人的步态估计参数。第三,还提出了机器人和传感器集成设置。最后,介绍了参数检测算法。在实验研究中,尽管在行走过程中连续振荡,但参数估计是精确且无偏见的,还显示了随着人类线速度变化的可重复性。控制器以八字形曲线进行了评估,显示了控制器的稳定性,即使在实际实验中人为路径发生了急剧变化也是如此。

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