Robot-driven Trajectory Improvement for Feeding Tasks

Rhodes, Travers; Veloso, Manuela

doi:10.1109/iros.2018.8593525

Cited by 14 publications

(5 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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

View full text Add to dashboard Cite

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.

show abstract

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

View full text Add to dashboard Cite

show abstract

“…We leverage such visual input to detect anomalies as well as the user's mouth. In addition, researchers have adapted feeding task movements to users' preferences by incrementally updating movement primitives [58,59].…”

Section: Meal-assistance Devicesmentioning

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

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.

show abstract

“…For example, researchers have demonstrated how tablemounted robotic arms can provide drinking assistance to people using a force sensing smart cup [4] and a brain-machine interface for shared-autonomy [5]. Similarly, robots have shown promising results for providing feeding assistance [6], [7], [8], [9], [10], [11]. Prior research has also investigated robotic assistance for bed bathing [12], [13], which can be especially valuable for people who are confined to a bed due to disabilities or injuries.…”

Section: A Physically Assistive Roboticsmentioning

confidence: 99%

Assistive VR Gym: Interactions with Real People to Improve Virtual Assistive Robots

Erickson

Kemp

2020

2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)

View full text Add to dashboard Cite

Versatile robotic caregivers could benefit millions of people worldwide, including older adults and people with disabilities. Recent work has explored how robotic caregivers can learn to interact with people through physics simulations, yet transferring what has been learned to real robots remains challenging. Virtual reality (VR) has the potential to help bridge the gap between simulations and the real world. We present Assistive VR Gym (AVR Gym), which enables real people to interact with virtual assistive robots. We also provide evidence that AVR Gym can help researchers improve the performance of simulation-trained assistive robots with real people. Prior to AVR Gym, we trained robot control policies (Original Policies) solely in simulation for four robotic caregiving tasks (robotassisted feeding, drinking, itch scratching, and bed bathing) with two simulated robots (PR2 from Willow Garage and Jaco from Kinova). With AVR Gym, we developed Revised Policies based on insights gained from testing the Original policies with real people. Through a formal study with eight participants in AVR Gym, we found that the Original policies performed poorly, the Revised policies performed significantly better, and that improvements to the biomechanical models used to train the Revised policies resulted in simulated people that better match real participants. Notably, participants significantly disagreed that the Original policies were successful at assistance, but significantly agreed that the Revised policies were successful at assistance. Overall, our results suggest that VR can be used to improve the performance of simulation-trained control policies with real people without putting people at risk, thereby serving as a valuable stepping stone to real robotic assistance.

show abstract

Robot-driven Trajectory Improvement for Feeding Tasks

Cited by 14 publications

References 11 publications

Is More Autonomy Always Better?

Is More Autonomy Always Better?

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

Assistive VR Gym: Interactions with Real People to Improve Virtual Assistive Robots

Contact Info

Product

Resources

About