Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Ontology-Based State Representations for Intention Recognition in Human-Robot Collaborative Environments



Craig I. Schlenoff, Anthony Pietromartire, Zeid Kootbally, Stephen B. Balakirsky, Sebti Foufou


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 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.
Robotics and Autonomous Systems Journal


intention recognition, human-robot interaction and safety, state representation, ontology, template matching, RCC8


Schlenoff, C. , Pietromartire, A. , Kootbally, Z. , Balakirsky, S. and Foufou, S. (2013), Ontology-Based State Representations for Intention Recognition in Human-Robot Collaborative Environments, Robotics and Autonomous Systems Journal, [online], (Accessed May 25, 2024)


If you have any questions about this publication or are having problems accessing it, please contact

Created May 23, 2013, Updated April 7, 2017