@article {
	title = {Active View Point Control for Detection of Dynamic Targets in Human-Robot Interaction},
	author = {Luan, Wentao., John S. Baras, Fermuller, Cornelia., Mao, Ren.},
	year = {2017},
	month = {06/2017},
	abstract = {Object detection is a fundamental task for robots, and is particularly challenging in the dynamic setting of humanrobot interaction because of the user{\textquoteright}s movements. In this work, we put forward a practical viewpoint control mechanism for object detection in human-robot interaction. We not only consider constraints from vision but also incorporate the low level robot kinematics to guarantee reachability of the desired viewpoint. Using a linear time cost score function, our system selects very fast the viewpoints, which in turn leads to a smooth user interaction experience. We also provide a method to learn from human demonstration the score function weights to fit the task{\textquoteright}s preference.
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	journal = {IEEE Robotics and Automation Letters (RA-L)}
}
