RoboCup: The Robot World Cup Initiative
AGENTS '97 Proceedings of the first international conference on Autonomous agents
Using Orientation Information for Qualitative Spatial Reasoning
Proceedings of the International Conference GIS - From Space to Territory: Theories and Methods of Spatio-Temporal Reasoning on Theories and Methods of Spatio-Temporal Reasoning in Geographic Space
Automated Planning: Theory & Practice
Automated Planning: Theory & Practice
Inferring Activities from Interactions with Objects
IEEE Pervasive Computing
Understanding human intentions via hidden markov models in autonomous mobile robots
Proceedings of the 3rd ACM/IEEE international conference on Human robot interaction
Ontology-Based User Intention Recognition for Proactive Planning of Intelligent Robot Behavior
MUE '08 Proceedings of the 2008 International Conference on Multimedia and Ubiquitous Engineering
Qualitative spatial representation and reasoning in the SparQ-toolbox
SC'06 Proceedings of the 2006 international conference on Spatial Cognition V: reasoning, action, interaction
Intention recognition in the situation calculus and probability theory frameworks
CLIMA'05 Proceedings of the 6th international conference on Computational Logic in Multi-Agent Systems
Proceedings of the 2012 ACM Conference on Ubiquitous Computing
Knowledge driven robotics for kitting applications
Robotics and Autonomous Systems
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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.