Alle Publikationen
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2019
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(2019): An affordance and distance minimization based method for computing object orientations for robot human handovers. In: International Journal of Social Robotics, S. 143-162. DOI: 10.1007/s12369-019-00546-7
DOI: https://doi.org/10.1007/s12369-019-00546-7 Abstract: The ability to hand over objects to humans is an important skill for service robots. However, determining the proper object pose for handover is a challenging task. Our approach, based on observations of a set of natural human handovers, addresses three related challenges in teaching robots how to hand over objects: (1) how to compute mathematically an appropriate ‘standard’ or ‘mean’ handover orientation, (2) how to ascertain whether an observed set is of good or poor quality, and (3) using (1) and (2), how to compute an appropriate handover orientation from a set, in a manner that is robust to the quality of the set. We first compare three methods for computing mean orientations and show that our proposed distance minimization based method yields the best results. Next, we show that using the concept of affordance axes, we can evaluate the quality of a set of observed orientations. Finally, using affordance axes together with random sample consensus, we devise a method for computing an appropriate handover orientation from a set of observed natural handover orientations. User study data verified that our methods are successful in identifying both good and poor quality sets of handover orientations and in computing appropriate handover orientations from observed natural handover orientations. These results enable robots to automatically learn proper handover orientations for various objects. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
2014
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(2014): An affordance sensitive system for robot to human object handover. In: International Journal of Social Robotics 6 (4), S. 653-666. DOI: 10.1007/s12369-014-0241-3
DOI: https://doi.org/10.1007/s12369-014-0241-3 Abstract: One of the most important characteristics that needs to be taken into account while designing advanced human-robot interaction systems is the ability of the robot to behave in a socially acceptable way that is comfortable for humans. This paper presents a novel system for robot to human object handover that maximizes user’s convenience while receiving the object. The object is delivered to the receiving partner such that the most appropriate part is oriented towards him/her. The system has been developed supporting all the necessary phases of the handover task, including object recognition, people detection, robot motion planning, and automatic detection of user’s grasp. Moreover, voice recognition and text-to-speech have been integrated to enable natural object selection in environments that include multiple objects. The experimental setup consists of a six degree of freedom robot arm equipped with a two-finger gripper and an eye-in-hand laser scanner for object recognition, as well as a fixed range sensor for people and grasp detection. A user study has been conducted to assess the usability of the system and verify whether novice users can successfully accomplish a handover task with the system. The user study has confirmed that the proposed solution allows a more comfortable handover than a system disregarding object orientation. (PsycINFO Database Record (c) 2019 APA, all rights reserved)
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