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Modeling and robust analysis of a fuzzy based person following robot

机译:基于模糊的人跟随机器人的建模和鲁棒性分析

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Ability to follow and track a person robustly is an essential prerequisite for human-robot-interaction. Such capability has desires, which cannot be met pleasingly using conventional numerical process. Most rigorously, the robot has to stay at a certain safe distance as of the person that is being tracked and concurrently be in motion smoothly which does not seem to be scary to the person. In this research, consequently, a Fuzzy Inference System (FIS) is developed and used as a controller to provide decisions achieving smooth and safe person-following activities. Few approaches have been used to examine the performance of person following robot in smooth tracking and comparing and collating those ultimately an IR based co-ordinate system is used to obtain the tracking features for human robot interaction and the velocity of the person is detected by using ultrasonic sensor which are used to generate the Fuzzy membership function of FIS to control the robot movement. The simulation and result on this research established that even though the detection of IR is subject to minor noise and false negatives, the robot will achieve the smoothness and safety objectives while following its target. In this paper robot modelling and its real time robust analysis is demonstrated for the designed prototype.
机译:强大地追踪和跟踪人的能力是人机交互的基本前提。具有这样的能力,这是使用常规数值方法不能令人满意地满足的。最严格的是,机器人必须与被跟踪的人员保持一定的安全距离,并且要同时平稳地运动,这似乎并不会使人感到恐惧。因此,在本研究中,开发了模糊推理系统(FIS)并将其用作控制器,以提供决策,以实现顺畅且安全的人员跟踪活动。很少有方法用于检查跟随机器人的人在平滑跟踪中的性能,并比较和整理这些方法,最终使用基于IR的坐标系来获取人机交互的跟踪特征,并通过使用以下方法检测人的速度超声波传感器,用于生成FIS的模糊隶属函数以控制机器人的运动。这项研究的仿真和结果表明,即使红外的检测受到轻微噪声和假阴性的影响,机器人仍将在遵循其目标的同时达到平滑性和安全性目标。在本文中,针对设计的原型演示了机器人建模及其实时鲁棒性分析。

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