The Community for Technology Leaders
Frontiers of Information Technology (2013)
Islamabad, Pakistan Pakistan
Dec. 16, 2013 to Dec. 18, 2013
pp: 89-94
ABSTRACT
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.
INDEX TERMS
Human-robot interaction, History, Probabilistic logic, Trajectory, Robot kinematics, Service robots,intention estimation, Human-Robot interaction
CITATION
Muhammad Awais, Dominik Henrich, "Human-Robot Interaction in an Unknown Human Intention Scenario", Frontiers of Information Technology, vol. 00, no. , pp. 89-94, 2013, doi:10.1109/FIT.2013.24
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