Hybrid Navigation Decision Control Mechanism for Intelligent Wheel-Chair

Authors:
Open Access
Publisher website
Google Scholar
Abstract
The continuous rising of the elderly/disabled population has created a requirement for assistive robotics devices to counter the lack of trustworthy servants. Intelligent Wheelchairs are developed for that particular purpose. Intelligent Wheelchairs differ depending on the interactive modality and most commonly found modalities are speech-controlled. Since these are assistive devices that need to act as human companions, it is necessary to have a dialogue between the device and the user. Even though the wheelchair is fully automated, the user should have control over it at some point. However, this exchange of control should be intelligent and transitions need to be executed in order to safeguard the user. Therefore the purpose of this paper is to propose an intelligent system that would navigate an intelligent voice-controlled wheelchair facilitating the intelligent exchange of control between the user and the wheelchair. This control is not simultaneous and one can override the other only when navigation could lead to collisions. In the proposed method, users can control the wheelchair using fixed vocal commands, and execution of those commands will be performed using the spatial and control parameters. Control of the wheelchair will be exchanged between the user and the wheelchair itself considering specific parameters such as obstacle distance, collision time, the velocity of the wheelchair among others. User control mode has 5 definite vocal commands with classifiers to identify any navigation command into the command model and considers uncertain terms such as ‘little’ and ‘hard’ for ‘Turn’ commands. Command classification had produced a Cohen’s Kappa value of 0.9462 and the classifier for the uncertain terms had produced a Cohen’s Kappa value of 0.7325. Both were acceptable values for those particular classifications. As per the experiment results, the proposed system reduced the vocal command frequency and risk of collisions through proper control of the velocity levels and intelligent exchange of control at given locations.
Funding Information
  • University of Moratuwa under Senate Research Committee (SRC/CAP/2018/03)
  • Center for Advanced Robotics

This publication has 44 references indexed in Scilit: