Human-Robot Interaction in an Unknown Human Intention scenario

被引:23
作者
Awais, Muhammad [1 ]
Henrich, Dominik [2 ]
机构
[1] Govt Coll Univ Faisalabad, Coll Comp Sci & Informat Studies, Faisalabad, Pakistan
[2] Univ Bayreuth, Lehrstuhl Angew Informat Robot & Eingebettete Sys, D-95440 Bayreuth, Germany
来源
2013 11TH INTERNATIONAL CONFERENCE ON FRONTIERS OF INFORMATION TECHNOLOGY (FIT) | 2013年
关键词
D O I
10.1109/FIT.2013.24
中图分类号
TP39 [计算机的应用];
学科分类号
080201 [机械制造及其自动化];
摘要
In this paper an approach is introduced to human-robot interaction in a known scenario with unknown human intentions. Initially, the robot reacts by copying the human action. As the human-robot interaction proceeds, the level of human-robot interaction improves. Before each reaction, the robot hypothesizes its potential actions and selects one that is found most suitable. The robot may also use the human-robot interaction history. Along with the history, the robot also considers the action randomness and heuristic based action predictions. As solution, a general Reinforcement Learning (RL) based algorithm is proposed that suggests learning of human-robot interaction in an unknown human intention scenario. A Particle Filter (PF) based algorithm is proposed to support the probabilistic action selection for human-robot interaction. The experiments for human-robot interaction are performed by a robotic arm involving the arrangement of known objects with unknown human intention. The task of the robot is to interact with the human according to the estimated human intention.
引用
收藏
页码:89 / 94
页数:6
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