\section{Overview}\label{overview}

In a shared control framework, both the human and the machine play an important role in the performance of the wheelchair. The degree of control imparted to the human driver should be decided based on his or her abilities. This may relate to physical or cognitive disabilities or temporal changes in skills due to stress, fatigue, type of environment etc. Hence the shared control system has to make three decisions on-line for continuously adapting to the user's needs - who is in control, when is assistance required by the user and what is the extent of assistance required. Vanhooydonck et al (2010) have identified a list of requirements for a personalised shared control strategy. These include useful navigational manoeuvres, user safety, independence from environment, good understanding between human and robot through adequate communication, predictable behaviour, respect for user autonomy, ability to predict user intention and adaptable to various disabilities of users. Most smart wheelchair developers focus on one or more of these requirements while designing their shared control system. However, it has proved to be difficult to satisfy all the requirements.

Some of the assisting behaviours provided by smart wheelchairs include obstacle avoidance, collision avoidance, wall following, docking, door passage, navigation through cluttered or crowded areas etc. The assistance may be provided in indoor or/and outdoor environments. Switching between these modes may be done explicitly by the user or implicitly by algorithms as in NavChair (Simpson et al, 1998) and Sharioto (Vanhooydonck et al, 2010).

Simpson's (2005) review of smart wheelchairs provides a helpful guide to understanding the various features provided by shared control approaches and their limitations. Most wheelchairs provide obstacle avoidance or collision avoidance assistance. Wheelchairs providing only these functionalities include Luoson III, TinMan, IntellWheels intelligent wheelchair (Petry et al, 2010), biometrically modulated wheelchair developed by Uridales et al (2010) etc. The CWA (Collaborative Wheelchair Assistant) however, depends on the user to detect obstacles, while the shared control module provides only path-following assistance (Zeng et al, 2006). The wheelchairs providing additional task-specific functionalities such as wall following, door passage, target tracking etc. include Hephaestus, Intelligent Wheelchair System of Osaka University, MisterEd, NavChair, OMNI, RobChair, SENARIO, Sharioto (Nuttin et al, 2002), VAHM, Wheelesley etc. These wheelchairs are capable of providing a wider range of daily manoeuvres required by people with disabilities or elderly people. However, the issue of mode switching must be handled explicitly or implicitly. The wheelchair developed in the MAid project was based on a different methodology for providing navigational assistance, as will be described in \hyperref[exampletechniques]{Section 2.2}.

Various control algorithms have been adopted for implementing shared control. \hyperref[exampletechniques]{Section 2.2} provides detailed examples of a few interesting methodologies to illustrate the differences and similarities in shared control techniques. These include intelligent wheelchairs using Vector Field Histogram and Potential Field Methods for obstacle avoidance, implementation of BCI operated shared control, a biometrically modulated smart wheelchair, approaches where the environment has been modified for providing navigation assistance etc.
