Abstract-Some people with severe mobility impairments are unable to operate powered wheelchairs reliably and effectively, using commercially available interfaces. This has sparked a body of research into "smart wheelchairs", which assist users to drive safely and create opportunities for them to use alternative interfaces. Various "shared control" techniques have been proposed to provide an appropriate level of assistance that is satisfactory and acceptable to the user. Most shared control techniques employ a traditional strategy called linear blending (LB), where the user's commands and wheelchair's autonomous commands are combined in some proportion. In this paper, however, we implement a more generalised form of shared control called probabilistic shared control (PSC). This probabilistic formulation improves the accuracy of modelling the interaction between the user and the wheelchair by taking into account uncertainty in the interaction. In this paper, we demonstrate the practical success of PSC over LB in terms of safety, particularly for novice users.

It is important to assess the suitability of mobility aids before prescribing them to patients. This assessment is often subjectively completed by a therapist and it often includes a variety of basic practical tests. An objective assessment of a patient's capability, which captures not only speed of task completion and success, but also accuracy and risk of manoeuvres, would be both a fairer and safer approach. Yet until now such an assessment would have been cost-prohibitive, especially in low resource settings. We pave the way towards this end goal, by describing, validating and demonstrating a low-cost computer vision based system called MoRe-T2 (mobility research trajectory tracker). The open-source MoRe-T2 system uses low-cost off-the-shelf webcams to track the pose of fiducial markers, which are simply printed onto regular office paper. In this article, we build upon previous work and benchmark the accuracy of MoRe-T2 against an industry standard motion capture system. In particular, we show that MoRe-T2 achieves accuracy comparable to CODA motion tracking system. We go on to demonstrate a use case of MoRe-T2 in assessing wheelchair manoeuvrability over a relatively large area. The results show that MoRe-T2 is scalable at a much lower cost than typical industry-standard motion trackers. Therefore, MoRe-T2 can be used to develop more objective and reliable assessments of mobility aids, especially in low-resource settings.

Abstract-Independent mobility is important for the selfesteem and well-being of people with mobility impairments. For people with severe disabilities, there is a body of research investigating how best to share control of motion between a person with disabilities and a "smart wheelchair". Traditionally in "shared control", the control law is a linear combination of the human's intended velocity and the path planner's velocity. However, this formulation of sharing control between a human and a machine does not guarantee safety on a theoretical level. To guarantee safety in formulating the blending of the human's input velocity and planner's velocity, we implement a practical form of probabilistic shared control formulated by Trautman. We tested this shared control by conducting experiments in a simulation where participants drive a wheelchair. The results of the experiment suggest probabilistic shared control has similar performance to linear blending in terms of significant reduction in number of collisions. However, probabilistic shared control reduced more collisions on average than linear blending did for the sip-puff switch, which is a difficult control interface to drive a wheelchair with.