Independent mobility is fundamental to the quality of life of people with impairment. Most people with severe mobility impairments, whether congenital, e.g., from cerebral palsy, or acquired, e.g., from spinal cord injury, are prescribed a wheelchair. A small yet significant number of people are unable to use a typical powered wheelchair controlled with a joystick. Instead, some of these people require alternative interfaces such as a head- array or Sip/Puff switch to drive their powered wheelchairs. However, these alternative interfaces do not work for everyone and often cause frustration, fatigue and collisions. This thesis develops a novel technique to help improve the usability of some of these alternative interfaces, in particular, the head-array and Sip/Puff switch. Control is shared between a powered wheelchair user, using an alternative interface and a pow- ered wheelchair fitted with sensors. This shared control then produces a resulting motion that is close to what the user desires to do but a motion that is also safe. A path planning algorithm on the wheelchair is implemented using techniques in mo- bile robotics. Afterwards, the output of the path planning algorithm and the user's com- mand are both modelled as random variables. These random variables are then blended in a joint probability distribution where the final velocity to the wheelchair is the one that maximises the joint probability distribution. The performance of the probabilistic approach to blending the user's inputs with the output of a path planner, is benchmarked against the most common form of shared control called linear blending. The benchmarking consists of several experiments with end users both in a simulated world and in the real-world. The thesis concludes that probabilistic shared control provides safer motion compared with the traditional shared control for difficult tasks and hard-to-use interfaces.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:763171 |
| Date | January 2018 |
| Creators | Ezeh, Chinemelu Ejiamatu Muoma |
| Contributors | Carlson, T. ; Holloway, C. |
| Publisher | University College London (University of London) |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://discovery.ucl.ac.uk/10048965/ |
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