@article {3214,
	title = { Enhancing Adaptive Grasping Through a Simple Sensor-Based Reflex Mechanism },
	journal = {IEEE Robotics and Automation Letters},
	volume = {2},
	year = {2017},
	month = {07/2017},
	pages = {1664 - 1671},
	abstract = {<p>This paper presents an approach to achieve adaptive grasp of unknown objects whose position is only approximately known via point-cloud data. We exploit the adaptability of a soft robotic hand which can autonomously conform to the shape of a grasped object if properly approached. Once a grasp approach has been preliminarily planned based only on rough estimates of the object position, the hand is shaped to a pregrasp configuration. Before closing the hand, a sensor-based algorithm is applied that corrects the relative hand-object posture so as to enhance the probability that the object is uniformly approached by all fingers, thus avoiding undesired premature contacts. The algorithm minimizes the distance between the hand{\textquoteright}s fingerpads and the object by continuously controlling both the wrist pose and orientation and the hand closure. Experimental studies with a Kuka-LWR arm and a Pisa/IIT Softhand illustrate the benefit of the developed technique and the improvement in grasping performance with respect to open-loop execution of grasps planned on the basis of prior RGB-D cues only.</p>
},
	keywords = {Haptics, Robotics},
	doi = {10.1109/LRA.2017.2681122},
	url = {http://ieeexplore.ieee.org/document/7875417/},
	author = {Luberto, E. and Y. Wu and G. Santaera and M Gabiccini and A. Bicchi}
}
