A POMDP framework for modelling human interaction with assistive robots

This paper presents a framework for modelling the interaction between a human operator and a robotic device, that enables the robot to collaborate with the human to jointly accomplish tasks. States of the system are captured in a model based on a partially observable Markov decision process (POMDP). States representing the human operator are motivated by behaviours from the psychology of the human action cycle. Hierarchical nature of these states allows the exploitation of data structures based on algebraic decision diagrams (ADD) to efficiently solve the resulting POMDP. The proposed framework is illustrated using two examples from assistive robotics; a robotic wheel chair and an intelligent walking device. Experimental results from trials conducted in an office environment with the wheelchair is used to demonstrate the proposed technique.