State of the art review
To go back to the mainpage: PRE2017 3 Groep6.
This page is not finished yet
summaries:
[1] This article is about navigating for people with mobility problems. They explore a combination of accessibility maps and route planning for people with mobility problems. When in an elderly scooter accessibility of a place of rout is important. As an pedestrian you can take the stairs but when you are in an elderly scooter this is not possible.
[2] This article presents routing methods suitable for wheelchair users by taking into account obstacles. they calculate scores for sideways segment and use those scores to toe determine the best route between tow addresses in a network.
[3] This is an old article about a robotic wheel chair. But is about using a robotic wheel chair during rush hours in a train station. This is similar to one of the problems we were thinking about namely using a elderly scooter in a supermarket when there are a lot of other people. In this article they are already talking about standard skills like following a wall or corridor or passing a doorway. This are all skill we can also use. the wheelchair in this article is already able to move collision free through a busy train station.
[4] This article is not really about the current state of the art but more about the problem. This article investigate the characteristic of the users, how they got a device and what the benefits and challenges of use are. In the survey is concluded that 1 out of 5 responders had an accident with their powered wheel chair or scooter in the last year.
[5] this article describes the current state of the art in 2017. So it will probably by close to the current state of the art. It describe popular input methods. At the moment there is already a method Brain-computer interface that can detect that the user is frustrated with the system. It also describes promising methods of obstacle detection like low-tech inexpensive optical USB camera and sophisticated machine vision software. The articles also describe different operation mode like machine learning, Following, localization and mapping and, navigational assistance. The article also considers human factor in smart wheelchairs.
[6] this article explains how IR and ultrasonic devices could be implemented on a mobility scooter and shows tests with an implemented system, how well the system responds to far, medium and short distance to obstacles.
[7] this article explores the safety of mobility scooters by a series of collision tests.
[8] this is a study done to find out the current number of incidents between 2011 and 2012. This could help us to see if our autonomous modifications will actually help solve some incidents
[9] This article explores the best way to notify drivers of a semi-autonomous vehicle to take over control when the autonomous system fails. This article shows results with abstract cues, such as audio and cues delivered from the tablet can help notify the driver.
sources:
[1] Holone H., Misund G. (2008) People Helping Computers Helping People: Navigation for People with Mobility Problems by Sharing Accessibility Annotations. In: Miesenberger K., Klaus J., Zagler W., Karshmer A. (eds) Computers Helping People with Special Needs. ICCHP 2008. Lecture Notes in Computer Science, vol 5105. Springer, Berlin, Heidelberg
[2] piyawan kasemsuppakorn & Hassan A. Karimi (2008) Personalised routing for wheelchair navigation
[3] e.prassle, j. scholz P. Fiorini (1999) Navigating a Robotic Wheelchair in a Railway Station during Rush Hour
[4] Kara Edwards 7 Annie Mccluskey (2010) A survey of adult power wheelchair and scooter users
[5] Jesse Leaman & Hung Manh LA (2017) a comprehensive review of smart wheelchairs: past, present and future
[6] Adrian Bingham, Xavier Hadoux &Dinesh Kant Kumar (2014) Implementation of a safety system using ir and ultrasonic devices for mobility scooter obstacle collision avoidance
[7] Hongyu Li & E.C. Chirwa (2014) Development of a mobility scooter finite element model
[8] Nancy M. Gell, Robert B. Wallace MD,Andrea Z. LaCroix ,Tracy M. Mroz, Kushang V. Patel Mobility Device Use in Older Adults and Incidence of Falls and Worry About Falling: Findings from the 2011–2012 National Health and Aging Trends Study
[9] Politis, I., Brewster, S. & Pollick, F. (2017) Using multimodal displays to signify critical handovers of control to distracted autonomous car drivers.