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2013
Schlenoff, Craig; Pietromartire, Anthony; Kootbally, Zeid; Balakirsky, Stephen; Foufou, Sebti (2013): Ontology-based state representations for intention recognition in human–robot collaborative environments. In: Robotics and Autonomous Systems 61 (11), S. 1224-1234. DOI: 10.1016/j.robot.2013.04.004

DOI: https://doi.org/10.1016/j.robot.2013.04.004

Abstract: In this paper, we describe a novel approach for representing state information for the purpose of intention recognition in cooperative human–robot environments. States are represented by a combination of spatial relationships in a Cartesian frame along with cardinal direction information. This approach is applied to a manufacturing kitting operation, where humans and robots are working together to develop kits. Based upon a set of predefined high-level state relationships that must be true for future actions to occur, a robot can use the detailed state information described in this paper to infer the probability of subsequent actions occurring. This would allow the robot to better help the human with the task or, at a minimum, better stay out of his or her way. (PsycINFO Database Record (c) 2016 APA, all rights reserved)

Keywords: Bedienung & Handhabung, Environmental Effects, Human Machine Systems, human robot environments, Intention, intention recognition, Intentional Learning, Knowledge representation, Ontology (Philosophy), ontology based state representations, Recognition (Learning), Robotics, Spatial Learning, spatial relationships

2013

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