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.
- Human-robot safety
- Intention recognition
- State-based representation
ASJC Scopus subject areas
- Control and Systems Engineering
- General Mathematics
- Computer Science Applications