SmartWheeler

SmartWheeler: A robotic wheelchair test-bed for investigating new models of human-robot interaction
J. Pineau & A. Atrash for the SmartWheeler team
Abstract: The goal of the SmartWheeler project is to increase the autonomy and safety of individuals with severe mobility impairments by developing a robotic wheelchair that is adapted to their needs. The project tackles a range of challenging issues, focusing in particular on tasks pertaining to human-robot interaction, and on robust control of the intelligent wheelchair. The platform we have built also serves as a test-bed for validating novel concepts and algorithms for automated decisionmaking onboard socially assistive robots. This paper introduces the wheelchair platform, and outlines technique contributions in four ongoing research areas: adaptive planning in large-scale environments, learning and control under model uncertainty, large-scale dialogue management, and communication protocols for the tactile interface.
Citation: J. Pineau & A. Atrash for the SmartWheeler team. "SmartWheeler: A robotic wheelchair test-bed for investigating new models of human-robot interaction." AAAI Spring Symposium on Multidisciplinary Collaboration for Socially Assistive Robotics. 2007.
Efficient planning and tracking in POMDPs with large observation spaces
A. Atrash & J. Pineau
Abstract: Planning in partially observable MDPs is computationally limited by the size of the state, action and observation spaces. While many techniques have been proposed to deal with large state and action spaces, the question of automatically finding good low-dimensional observation spaces has not been explored as thoroughly. We show that two different reduction algorithms, one based on clustering and the other on a modified principal component analysis, can be applied directly to the observation probabilities to create a reduced feature observation matrix. We apply these techniques to a real-world dialogue management problem, and show that fast and accurate tracking and planning can be achieved using the reduced observation spaces.
Citation: A. Atrash & J. Pineau "Efficient Planning and Tracking in POMDPs with Large Observation Spaces". AAAI-06 Workshop on Empirical and Statistical Approaches for Spoken Dialogue Systems. 2006.