Dissemin is shutting down on January 1st, 2025

Published in

2006 IEEE/RSJ International Conference on Intelligent Robots and Systems

DOI: 10.1109/iros.2006.282386

Links

Tools

Export citation

Search in Google Scholar

Bayesian Estimation of Wheelchair Driver Intents: Modeling Intents as Geometric Paths Tracked by the Driver

This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Many elderly and disabled people today experience difficulties when manoeuvring an electric wheelchair. In order to help these people, several robotic assistance platforms have been devised in the past. In most cases, these platforms consist of separate assistance modes, and heuristic rules are used to automatically decide which assistance mode should be selected in each time step. As these decision rules are often hard-coded and do not take uncertainty regarding the user's intent into account, assistive actions may lead to confusion or even irritation if the user's actual plans do not correspond to the assistive system's behavior. In contrast to previous approaches, this paper presents a more user-centered approach for recognizing the intent of wheelchair drivers, which explicitly estimates the uncertainty on the user's intent. The paper shows the benefit of estimating this uncertainty using experimental results with our wheelchair platform Sharioto