0000000000082980
AUTHOR
Anthony Pietromartire
Ontology-based state representations for intention recognition in human–robot collaborative environments
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 …
Intention recognition in manufacturing applications
In this article, we present a novel approach to intention recognition, based on the recognition and representation of state information in a cooperative human-robot environment. States are represented by a combination of spatial relations along with cardinal direction information. The output of the Intention Recognition Algorithms will allow a robot to help a human perform a perceived operation or, minimally, not cause an unsafe situation to occur. We compare the results of the Intention Recognition Algorithms to those of an experiment involving human subjects attempting to recognize the same intentions in a manufacturing kitting domain. In almost every case, results show that the Intention…
Ontology-based state representation for intention recognition in cooperative human-robot environments
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 states relationships that must be true for future actions to occur, a robot can use the detailed state information presented in this paper to infer the probability of subsequent actions occurring. This would enable the robot to better help th…