Predictive and Robust Robot Assistance for Sequential Manipulation
Theodoros Stouraitis, Michael Gienger
Abstract
This letter presents a novel concept to support physically impaired humans in daily object manipulation tasks with a robot. Given a user's manipulation sequence, we propose a predictive model that uniquely casts the user's sequential behavior as well as a robot support intervention into a hierarchical multi-objective optimization problem. A major contribution is the prediction formulation, which allows to consider several different future paths concurrently. The second contribution is the encoding of a general notion of constancy constraints, which allows to consider dependencies between consecutive or far apart keyframes (in time or space) of a sequential task. We perform numerical studies, simulations and robot experiments to analyse and evaluate the proposed method in several table top tasks where a robot supports impaired users by predicting their posture and proactively re-arranging objects.
BibTeX
@inproceedings{ral2023_predictiveandrob,
title = {Predictive and Robust Robot Assistance for Sequential Manipulation},
author = {Theodoros Stouraitis and Michael Gienger},
booktitle = {RA-L 2023},
year = {2023}
}