Vision Augmented Robot Feeding

Candeias, Alexandre; Rhodes, Travers; Marques, Manuel; Costeira, João Paulo; Veloso, Manuela

doi:10.1007/978-3-030-11024-6_4

Cited by 18 publications

(10 citation statements)

References 16 publications

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“…While specialized feeding devices for people with disabilities have been introduced on the market [1-5, 7, 9, 10, 13], they lack widespread acceptance. Numerous researchers have also developed robot-assisted feeding systems, either as table-mounted robotic arms [24,36,39,40,44,49,52,53,55,57,59,60,62,63,65,67,68], general purpose mobile manipulators [20,50,54], or wheelchairmounted robotic arms [16,21,28,30,32,37,45]. A comprehensive review of meal assistance robots is given in [22,42,47,61].…”

Section: Related Workmentioning

confidence: 99%

Is More Autonomy Always Better?

Bhattacharjee

Gordon

Scalise

et al. 2020

Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction

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A robot-assisted feeding system can potentially help a user with upper-body mobility impairments eat independently. However, autonomous assistance in the real world is challenging because of varying user preferences, impairment constraints, and possibility of errors in uncertain and unstructured environments. An autonomous robot-assisted feeding system needs to decide the appropriate strategy to acquire a bite of hard-to-model deformable food items, the right time to bring the bite close to the mouth, and the appropriate strategy to transfer the bite easily. Our key insight is that a system should be designed based on a user's preference about these various challenging aspects of the task. In this work, we explore user preferences for different modes of autonomy given perceived error risks and also analyze the effect of input modalities on technology acceptance. We found that more autonomy is not always better, as participants did not have a preference to use a robot with partial autonomy over a robot with low autonomy. In addition, participants' user interface preference changes from voice control during individual dining to web-based during social dining. Finally, we found differences on average ratings when grouping the participants based on their mobility limitations (lower vs. higher) that suggests that ratings from participants with lower mobility limitations are correlated with higher expectations of robot performance. CCS CONCEPTS• Human-centered computing → Empirical studies in accessibility; • Social and professional topics → People with disabilities; Assistive technologies; • Computer systems organization → Robotic autonomy.

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Section: Related Workmentioning

confidence: 99%

Is More Autonomy Always Better?

Bhattacharjee

Gordon

Scalise

et al. 2020

Proceedings of the 2020 ACM/IEEE International Conference on Human-Robot Interaction

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“…The primary was to enable people, with severe and complex disabilities, to live independently (Bühler et al, 1995;Kim et al, 2012;Chen et al, 2013;Hawkins et al, 2014;Schröer et al, 2015;Chance et al, 2016;Tan et al, 2016;Candeias et al, 2018;Jevtić et al, 2018;Canal, Alenyà andTorras, 2019, Ajani andAssal, 2020). Indeed, everyday tasks were considered by a number of papers: Hawkins et al (2014) focused on shaving; Schröer et al (2015) considered drinking; Candeias et al (2018) developed robotic feeding assistants; and Ajani and Assal (2020) focused on tooth brushing. One set of tasks which was considered by a number of papers was that of assisted dressing (Chance et al 2016, Canal, Alenyà and Torras.…”

Section: Disability and Autonomous Systems Researchmentioning

confidence: 99%

Trustworthy Autonomous Systems and Disabled Young People: A Critical Literature Review

White¹,

Picardi²,

Paterson³

et al. 2023

Preprint

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Autonomous robotic and AI assistive systems are becoming increasingly prevalent in public and private spheres—often heralded as having the potential to revolutionise the everyday lives of disabled people. The reality could not be more different: disabled young people are routinely excluded from such spheres and, significantly, from the recent efforts to ensure that autonomous systems are trustworthy. Our critical literature review explores how trustworthy autonomous systems (TAS) can be framed within a critical disability studies perspective. We introduce the field of TAS and explore the interdisciplinary field of critical disability studies. This brings us to a key question: how is disability conceptualised, methodologically explored and represented in the TAS literature? We address this question by considering the ways in which disability and TAS have hitherto connected in the literature. We conclude with suggestions for future research and innovation that place disabled young people at the core of research and innovation in TAS.

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“…In previous inquiries, there is the lake of technological work and limitations of selected food items [8].The user's facial expressions method is used to determine the user's demand and desire for those people who are paralyzed. The base-line algorithm is working properly in the face detection method which is currently using most the researchers in commercially available robots [9].The amazing factor is the multiple uses of sensors, which are creating a smooth behavior with nature. This method is enhancing to create a wide functional behavior in a globally accepted systems [10].In our process; Assistive capabilities are included for tangible progress.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on the Application of Machine Learning Algorithm and Fuzzy Logic in Eating Assistive Robot

Nawaz¹,

Li²,

Latif³

et al. 2021

IJRTE

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More than 110 million people in this world are facing some kind of disability, for which they experience difficulty while eating food. Eating Assistive Robots could meet the needs of the elderly and people with upper limb disabilities or dysfunctions in gaining independence in eating. We are researching making a robot, which can assist the disabled in eating their meals. Our Eating Assistive Robot will detect the face of the disabled and process it for whether his/her mouth is opened or closed. Our robot will put a pre-prepared replaceable spoon of food in his/her mouth iteratively until the food lasts in the food container. The methodology we used for it i.e. firstly there is a live camera feed through which we are detecting human faces, after this, a library of Affectiva calculates how much mouth is open. We have set a certain threshold after which the program starts the stepper motor which brings the pre-filled spoon of food into the mouth of the disabled.

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Vision Augmented Robot Feeding

Cited by 18 publications

References 16 publications

Is More Autonomy Always Better?

Is More Autonomy Always Better?

Trustworthy Autonomous Systems and Disabled Young People: A Critical Literature Review

Research on the Application of Machine Learning Algorithm and Fuzzy Logic in Eating Assistive Robot

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