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Intention modeling of Web user for networked mobile robot with Bayesian inference

机译:贝叶斯推理的网络移动机器人网络用户意图建模

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Teleoperated networked robot often has unpredictable behaviors due to uncertain time delay in data transmission over Internet. This paper investigates a novel approach to compensate the uncertain time delay with the autonomy of mobile robot. The user's intention to operate and control the networked robot is incrementally inferred based on Bayesian techniques so that task of the robot defined by the user's intention can be recognized. Consequently, the robot can autonomously execute this task without frequent interaction with the user, which decreases data transmission to a great extent. So long the robot has a correct inference on task, the efficiency of the whole system can be improved to a remarkable extent. Experimental results show the validity and feasibility of the proposed method.
机译:由于Internet上的数据传输存在不确定的时间延迟,因此远程操作的网络机器人通常具有不可预测的行为。本文研究了一种利用移动机器人的自主性来补偿不确定的时延的新方法。基于贝叶斯技术逐渐推断出用户操作和控制联网机器人的意图,从而可以识别出由用户意图定义的机器人任务。因此,机器人可以自主执行该任务,而无需与用户频繁互动,这在很大程度上减少了数据传输。只要机器人对任务有正确的推断,整个系统的效率就可以得到显着提高。实验结果证明了该方法的有效性和可行性。

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