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Representation and Inference of User Intention for Internet Robot

机译:互联网机器人用户意图的表示与推断

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Teleoperated robots often have unpredictable behaviors due to uncertain time delay in data transmissions over Internet. The robot cannot accomplish commands or actions issued by the remote operator in time, which severely impairs its reliability and efficiency. This paper investigates the strategy of modeling the operator's intention online by the teleoperated robot via the commands it received. Having deduced the intention, the robot could identify and thus autonomously accomplish the corresponding task without frequent interactions with the operator. Therefore data transmissions between the operator and the robot for task realization and performance evaluation can be minimized, and the impact of uncertain transmission delays on the efficiency of the entire system can be reduced. The robot, as an efficient manipulation tool controlled over the Internet, could be endowed with specified capability to improve its performance in the distributed environment. Intention of controlling and operating the robot is first expressed in planar or spatial grids and then incrementally inferred based on Bayesian techniques. Experiments with a teleoperated office robot show the validity and feasibility of the proposed method.
机译:由于Internet上数据传输的不确定的时间延迟,因此,遥控机器人通常具有不可预测的行为。机器人无法及时完成远程操作员发出的命令或动作,这严重损害了其可靠性和效率。本文研究了遥控机器人通过其接收的命令在线模拟操作员意图的策略。推断出意图后,机器人可以识别并自动完成相应的任务,而无需与操作员频繁互动。因此,可以最小化操作员与机器人之间用于任务实现和性能评估的数据传输,并且可以减少不确定的传输延迟对整个系统效率的影响。该机器人作为一种受Internet控制的有效操纵工具,可以赋予其特定的功能以改善其在分布式环境中的性能。首先在平面或空间网格中表达控制和操作机器人的意图,然后根据贝叶斯技术逐步推断。远程办公机器人的实验表明了该方法的有效性和可行性。

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