An autonomous robotic assistant for drinking

Schröer, Sebastian; Killmann, Ingo; Frank, Barbara; Volker, Martin A.; Fiederer, Lukas Dominique Josef; Ball, Tonio; Burgard, Wolfram

doi:10.1109/icra.2015.7140110

Cited by 54 publications

(36 citation statements)

References 21 publications

(23 reference statements)

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“…Takahashi and Suzukawa, on the other hand, introduced an interface enabling a user with quadriplegia to manually adjust delivery locations [57]. Similar to our work, Schroer et al proposed an adaptive drinking assistance robot that finds the user's mouth location with an external vision system [22]. Recently, Candeias et al introduced a visually-guided feeding system that also finds the user's mouth as well as checks food acquisition success using cameras [27].…”

Section: Meal-assistance Devicesmentioning

confidence: 76%

“…For meal assistance, Maheu et al showed that people with disabilities can feed themselves using a manually controlled JACO arm mounted on a wheelchair [37]. Schroer et al showed drinking assistance using a 7-DoF KUKA arm [22]. For object fetching, Kim et al introduced the UCF-MANUS robot, consisting of a wheelchair-mounted manipulator and interface [38].…”

Section: Assistive Manipulatorsmentioning

confidence: 99%

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Active robot-assisted feeding with a general-purpose mobile manipulator: Design, evaluation, and lessons learned

Park

Hoshi

Mahajan

et al. 2020

Robotics and Autonomous Systems

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Eating is an essential activity of daily living (ADL) for staying healthy and living at home independently. Although numerous assistive devices have been introduced, many people with disabilities are still restricted from independent eating due to the devices' physical or perceptual limitations. In this work, we present a new meal-assistance system and evaluations of this system with people with motor impairments. We also discuss learned lessons and design insights based on the evaluations. The meal-assistance system uses a general-purpose mobile manipulator, a Willow Garage PR2, which has the potential to serve as a versatile form of assistive technology. Our active feeding framework enables the robot to autonomously deliver food to the user's mouth, reducing the need for head movement by the user. The user interface, visually-guided behaviors, and safety tools allow people with severe motor impairments to successfully use the system. We evaluated our system with a total of 10 able-bodied participants and 9 participants with motor impairments. Both groups of participants successfully ate various foods using the system and reported high rates of success for the system's autonomous behaviors. In general, participants who operated the system reported that it was comfortable, safe, and easy-to-use.

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Section: Meal-assistance Devicesmentioning

confidence: 76%

Section: Assistive Manipulatorsmentioning

confidence: 99%

Active robot-assisted feeding with a general-purpose mobile manipulator: Design, evaluation, and lessons learned

Park

Hoshi

Mahajan

et al. 2020

Robotics and Autonomous Systems

View full text Add to dashboard Cite

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“…In [15] the robot delivers water in a cup. The user sends commands via a Brain Computer Interface (BCI) to the robot, whereas the robot calculates necessary trajectories.…”

Section: Related Workmentioning

confidence: 99%

“…Direct contact with the face is avoided by drinking from a straw. A more natural way of assistive drinking is achieved in [15] by tilting the cup stepwise while in direct contact with the user's mouth.…”

Section: Introductionmentioning

confidence: 99%

Towards robotic drinking assistance

Koller

Kyrarini

Gräser

2019

Proceedings of the 12th ACM International Conference on PErvasive Technologies Related to Assistive Environments

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Assistive robotic manipulators have the potential to support individuals with severe motor impairments at performing activities of daily life. With the help of robotic manipulators, the individuals may eat and drink independently of caregivers. The presented research work focuses on interactive drinking with a cup without a straw. The interaction exposes the user to potential harm due to the direct contact with the robot. In the presented work, a multi-sensor system is outlined, which ensures harmless contact forces between robot and human during an interactive drinking task. Tests on a healthy subject are performed and indicate pain-free interaction with the system. The sensor system is designed to allow the user an intuitive control of the task. The lip pressure is measured at the contact points and will be used in future work to control the tilting angle of the cup, which is grasped by the robot. CCS CONCEPTS • Human-centered computing → Collaborative interaction.

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“…More relevant, Schröer et al . [5] propose a robotic system which receives a BCI command from a user and autonomously assists the user in drinking from a cup. However, this approach only considers a single object and a fixed-base manipulator.…”

Section: Related Workmentioning

confidence: 99%

Deep Learning Based BCI Control of a Robotic Service Assistant Using Intelligent Goal Formulation

Kuhner

Fiederer

Aldinger

et al. 2018

Preprint

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As autonomous service robots become more affordable and thus available for the general public, there is a growing need for user-friendly interfaces to control these systems. Control interfaces typically get more complicated with increasing complexity of the robotic tasks and the environment. Traditional control modalities as touch, speech or gesture commands are not necessarily suited for all users. While non-expert users can make the effort to familiarize themselves with a robotic system, paralyzed users may not be capable of controlling such systems even though they need robotic assistance most. In this paper, we present a novel framework, that allows these users to interact with a robotic service assistant in a closed-loop fashion, using only thoughts. The system is composed of several interacting components: non-invasive neuronal signal recording and co-adaptive deep learning which form the brain-computer interface (BCI), high-level task planning based on referring expressions, navigation and manipulation planning as well as environmental perception. We extensively evaluate the BCI in various tasks, determine the performance of the goal formulation user interface and investigate its intuitiveness in a user study. Furthermore, we demonstrate the applicability and robustness of the system in real world scenarios, considering fetch-and-carry tasks and tasks involving human-robot interaction. As our results show, the system is capable of adapting to frequent changes in the environment and reliably accomplishes given tasks within a reasonable amount of time. Combined with high-level planning using referring expressions and autonomous robotic systems, interesting new perspectives open up for non-invasive BCI-based human-robot interactions.

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An autonomous robotic assistant for drinking

Cited by 54 publications

References 21 publications

Active robot-assisted feeding with a general-purpose mobile manipulator: Design, evaluation, and lessons learned

Active robot-assisted feeding with a general-purpose mobile manipulator: Design, evaluation, and lessons learned

Towards robotic drinking assistance

Deep Learning Based BCI Control of a Robotic Service Assistant Using Intelligent Goal Formulation

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