Assistive Trajectories for Human-in-the-Loop Mobile Robotic Platforms

Gillham, Michael; Howells, Gareth; Kelly, Stephen W.

doi:10.1109/est.2015.19

Cited by 4 publications

(1 citation statement)

References 22 publications

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“…According to our research and experience, whilst developing and testing our driving assistance technology [14][15][16] , providing simple collision avoidance or navigational assistance would not be sufficient to allow unmonitored use of the PWC, due to safety risks. There needs to be a synergetic assistance which adapts the assistance to the needs and requirements of the individual as they change over time, and most importantly keeps the user in full control of the PWC motion at all times.…”

Section: Introductionmentioning

confidence: 99%

Feature determination from powered wheelchair user joystick input characteristics for adapting driving assistance

Gillham¹,

Pepper²,

Kelly³

et al. 2017

Wellcome Open Res

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Many powered wheelchair users find their medical condition and Background their ability to drive the wheelchair will change over time. In order to maintain their independent mobility, the powered chair will require adjustment over time to suit the user's needs, thus regular input from healthcare professionals is required. These limited resources can result in the user having to wait weeks for appointments, resulting in the user losing independent mobility, consequently affecting their quality of life and that of their family and carers. In order to provide an adaptive assistive driving system, a range of features need to be identified which are suitable for initial system setup and can automatically provide data for re-calibration over the long term.: A questionnaire was designed to collect information from powered Methods wheelchair users with regard to their symptoms and how they changed over time. Another group of volunteer participants were asked to drive a test platform and complete a course which represented manoeuvring in a very confined space as quickly as possible. Two of those participants were also monitored over a longer period in their normal home daily environment. Features, thought to be suitable, were examined using pattern recognition classifiers to determine their suitability for identifying the changing user input over time.: The results are not designed to provide absolute insight into the Results individual user behaviour, as no ground truth of their ability has been determined, they do nevertheless demonstrate the utility of the measured features to provide evidence of the users' changing ability over time whilst driving a powered wheelchair.: Determining the driving features and adjustable elements Conclusions provides the initial step towards developing an adaptable assistive technology for the user when the ground truths of the individual and their machine have been learned by a smart pattern recognition system.

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Section: Introductionmentioning

confidence: 99%

Feature determination from powered wheelchair user joystick input characteristics for adapting driving assistance

Gillham¹,

Pepper²,

Kelly³

et al. 2017

Wellcome Open Res

Self Cite

View full text Add to dashboard Cite

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A Human-Vehicle Collaborative Driving Framework for Driver Assistance

Tran

Sheng

et al. 2019

IEEE Trans. Intell. Transport. Syst.

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Feature determination from powered wheelchair user joystick input characteristics for adapting driving assistance

Gillham¹,

Pepper²,

Kelly³

et al. 2017

Wellcome Open Res

View full text Add to dashboard Cite

Background: Many powered wheelchair users find their medical condition and their ability to drive the wheelchair will change over time. In order to maintain their independent mobility, the powered chair will require adjustment over time to suit the user's needs, thus regular input from healthcare professionals is required. These limited resources can result in the user having to wait weeks for appointments, resulting in the user losing independent mobility, consequently affecting their quality of life and that of their family and carers. In order to provide an adaptive assistive driving system, a range of features need to be identified which are suitable for initial system setup and can automatically provide data for re-calibration over the long term. Methods: A questionnaire was designed to collect information from powered wheelchair users with regard to their symptoms and how they changed over time. Another group of volunteer participants were asked to drive a test platform and complete a course which represented manoeuvring in a very confined space as quickly as possible. Two of those participants were also monitored over a longer period in their normal home daily environment. Features, thought to be suitable, were examined using pattern recognition classifiers to determine their suitability for identifying the changing user input over time. Results: The results are not designed to provide absolute insight into the individual user behaviour, as no ground truth of their ability has been determined, they do nevertheless demonstrate the utility of the measured features to provide evidence of the users’ changing ability over time whilst driving a powered wheelchair. Conclusions: Determining the driving features and adjustable elements provides the initial step towards developing an adaptable assistive technology for the user when the ground truths of the individual and their machine have been learned by a smart pattern recognition system.

show abstract

Assistive Trajectories for Human-in-the-Loop Mobile Robotic Platforms

Cited by 4 publications

References 22 publications

Feature determination from powered wheelchair user joystick input characteristics for adapting driving assistance

Feature determination from powered wheelchair user joystick input characteristics for adapting driving assistance

A Human-Vehicle Collaborative Driving Framework for Driver Assistance

Feature determination from powered wheelchair user joystick input characteristics for adapting driving assistance

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