Development of a Bayesian recursive algorithm to find free-spaces for an intelligent wheelchair

This paper introduces a new shared control strategy for an intelligent wheelchair using a Bayesian recursive algorithm. Using the local environment information gathered by a laser range finder sensor and commands acquired through a user interface, a Bayesian recursive algorithm has been developed to find the most appropriate free-space, which corresponds to the highest posterior probability value. Then, an autonomous navigation algorithm will assist to manoeuvre the wheelchair in the chosen free-space. Experiment results demonstrate that the new method provides excellent performance with great flexibility and fast response. © 2011 IEEE

Development of an assistive patient mobile system for hospital environments

This paper presents an assistive patient mobile system for hospital environments, which focuses on transferring the patient without nursing help. The system is a combination of an advanced hospital bed and an autonomous navigating robot. This intelligent bed can track the robot and routinely navigates and communicates with the bed. The work centralizes in building a structure, hardware design and robot detection and tracking algorithms by using laser range finder. The assistive patient mobile system has been tested and the real experiments are shown with a high performance of reliability and practicality. The accuracy of the method proposed in this paper is 91% for the targeted testing object with the error rate of classification by 6%. Additionally, a comparison between our method and a related one is also described including the comparison of results. © 2013 IEEE

The advancement of an obstacle avoidance bayesian neural network for an intelligent wheelchair

In this paper, an advanced obstacle avoidance system is developed for an intelligent wheelchair designed to support people with mobility impairments who also have visual, upper limb, or cognitive impairment. To avoid obstacles, immediate environment information is continuously updated with range data sampled by an on-board laser range finder URG-04LX. Then, the data is transformed to find the relevant information to the navigating process before being presented to a trained obstacle avoidance neural network which is optimized under the supervision of a Bayesian framework to find its structure and weight values. The experiment results showed that this method allows the wheelchair to avoid collisions while simultaneously navigating through an unknown environment in real-time. More importantly, this new approach significantly enhances the performance of the system to pass narrow openings such as door passing. © 2013 IEEE

Shared control strategies for human - Machine interface in an intelligent wheelchair

In this paper, we introduce a shared control mechanism for an intelligent wheelchair designed to support people with mobility impairments, who also have visual, upper limb, or cognitive impairment. The method is designed to allow users to be involved in the movement as much as possible, while still providing the assistance needed to achieve the goal safely. The data collected through URG-04LX and user interface are analyzed to determine whether the desired action is safe to perform. The system then decides to provide assistance or to allow the user input to control the wheelchair. The experiment results indicate that the method performs effectively with high satisfaction. © 2013 IEEE