For many people suffering from chronic mobility impairments, such as spinal cord injuries or multiple sclerosis, using a powered wheelchair to move around their environment can be difficult. According to a survey, 40% of patients found daily steering and maneuvering tasks to be difficult or impossible, and clinicians believe that between 61% and 91% of all wheelchairs users would benefit from a smart wheelchairs. Such numbers suggest that the deployment of intelligent wheelchairs catering to those patients need could have a deep social impact.
Robotics technology has made progress on a number of important issues pertaining to mobility over the last decade. Many of these developments can be transferred to the design of the intelligent wheelchairs. Yet many challenges remain, both practical and technical, when it comes to the development of human robot interaction components. The present survey of the literature on smart wheelchairs suggest that while voice control has often been used to control smart wheelchairs, it remains difficult to implement successfully.
The work addresses two main challenges pertaining to the development of voiced controlled assistive robots. Firstly, it tackles the problem of robust processing of speech commands. It propose to complete architecture for handling speech signals, which include not only signal processing, also semantic and synthetic processing, as well as probabilistic decision making for response production.
Secondly, it tackles the issue of developing standards and tools for the formal testing of assistive robots. The use of standard testing has been common currency in some sub-tasks pertaining to human robot interaction, most notably speech recognition. However few tools are available for the standardized and rigorous testing of fully integrated system.
It proposes a novel environment and methodology for the standardized testing of smart wheelchairs. The procedure is inspired from one commonly used in the evaluation of conventional or non-intelligent wheelchairs.
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