Personalized Robot Assistant for Support in Dressing

Jevtić, Aleksandar; Valle, Andres Flores; Alenyà, Guillem; Chance, Greg; Caleb-Solly, Praminda; Dogramadzi, Sanja; Torras, Carme

doi:10.1109/tcds.2018.2817283

Cited by 43 publications

(23 citation statements)

References 31 publications

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“…Capacitive sensing serves as the primary way our robot reacts to the person's movements and adapts its plan, and force sensing detects potentially unsafe situations. Jevtić et al (2018) presented a system that provides assistance with putting on a slip-on shoe. The system provided interfaces with which the user could direct the robot with gestures and voice commands.…”

Section: Perceiving and Modeling The Usermentioning

confidence: 99%

Personalized collaborative plans for robot-assisted dressing via optimization and simulation

et al. 2019

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Robots could be a valuable tool for helping with dressing but determining how a robot and a person with disabilities can collaborate to complete the task is challenging. We present task optimization of robot-assisted dressing (TOORAD), a method for generating a plan that consists of actions for both the robot and the person. TOORAD uses a multilevel optimization framework with heterogeneous simulations. The simulations model the physical interactions between the garment and the person being dressed, as well as the geometry and kinematics of the robot, human, and environment. Notably, the models for the human are personalized for an individual's geometry and physical capabilities. TOORAD searches over a constrained action space that interleaves the motions of the person and the robot with the person remaining still when the robot moves and vice versa. In order to adapt to real-world variation, TOORAD incorporates a measure of robot dexterity in its optimization, and the robot senses the person's body with a capacitive sensor to adapt its planned end effector trajectories. To evaluate TOORAD and gain insight into robot-assisted dressing, we conducted a study with six participants with physical disabilities who have difficulty dressing themselves. In the first session, we created models of the participants and surveyed their needs, capabilities, and views on robot-assisted dressing. TOORAD then found personalized plans and generated instructional visualizations for four of the participants, who returned for a second session during which they successfully put on both sleeves of a hospital gown with assistance from the robot. Overall, our work demonstrates the feasibility of generating personalized plans for robot-assisted dressing via optimization and physics-based simulation.

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Section: Perceiving and Modeling The Usermentioning

confidence: 99%

Personalized collaborative plans for robot-assisted dressing via optimization and simulation

et al. 2019

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“…E.g., if both feet have been introduced into the same trousers' leg, this should be corrected asap to avoid unnecessary discomfort or even pain. It should be noted that robotic assistance in dressing is a complex HRI subject which involves a great variety of aspects, including user's pose and gesture recognition Chance et al (2017a) or resolving ambiguity of spoken deictic commands Jevtić et al (2018). Although they are undoubtly all relevant for the task, here we will concentrate on the manipulative aspects of helping a person to dress.…”

Section: Robot-assisted Dressingmentioning

confidence: 99%

Perception of cloth in assistive robotic manipulation tasks

Jiménez

Torras

2020

Nat Comput

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Assistive robots need to be able to perform a large number of tasks that imply some type of cloth manipulation. These tasks include domestic chores such as laundry handling or bed-making, among others, as well as dressing assistance to disabled users. Due to the deformable nature of fabrics, this manipulation requires a strong perceptual feedback. Common perceptual skills that enable robots to complete their cloth manipulation tasks are reviewed here, mainly relying on vision, but also resorting to touch and force. The use of such basic skills is then examined in the context of the different cloth manipulation tasks, be them garment-only applications in the line of performing domestic chores, or involving physical contact with a human as in dressing assistance. Keywords Robotic assistance • Robotic cloth manipulation • Perception of cloth 1 IntroductionRobots perform quite competently nowadays in structured environments, tackling hard tasks under tough working conditions, and even handling incidences that could be anticipated. The requirements posed by assistive settings, however, point in a quite different direction. The top concerns are no longer precision and repeatability, but rather a high degree of adaptability to varying ambient conditions, ability to learn, multimodal human-robot interaction capabilities, and integrated safety. It is obvious that robots cannot replace humans entirely in assistive environments, probably they shouldn't either. Nonetheless, it is desirable that they be able to perform a variety of tasks within domestic and service environments such as hospitals or care homes. Such tasks fall under what is commonly known as domestic chores, whose fulfillment ensures not just tidy homes, but the very proper life conditions of physically disabled people, in acceptable standards of human dignity and coverage of needs. Human companionship cannot be obviated, but the burden of associated duties without added value in personal interchange can be certainly alleviated with a robotic helper.Among these tasks, those that involve the manipulation of textile items, including of course all types of garments, but also other categories of fabric-made objects such as bed-and tablecloth, curtains, towels, kitchen rags and dishcloth, etc. have to be highlighted. The omnipresence of such items in human daily environments and the importance of handling them correctly are evident. The means of providing assistive robots with the necessary abilities to perform cloth manipulation are not so clear. Ideally one would like to replicate the human proficiency in manipulating clothes, but the robotic state-of-the-art is still far from achieving the needed perceptual skills and the required dexterity. Cloth perception and manipulation

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“…Previous work [46][47][48][49][50] has learned user preferences by constructing user models. Multi-modal data (e.g., speech communication, user speed and verbal feedback) have been used to infer user preferences in [47,48]. [49,50] aim to analyze which robot hand-over configurations users prefer most.…”

Section: User Modelingmentioning

confidence: 99%

Probabilistic Real-Time User Posture Tracking for Personalized Robot-Assisted Dressing

2019

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Robotic solutions to dressing assistance have the potential to provide tremendous support for elderly and disabled people. However, unexpected user movements may lead to dressing failures or even pose a risk to the user. Tracking such user movements with vision sensors is challenging due to severe visual occlusions created by the robot and clothes. We propose a probabilistic tracking method using Bayesian networks in latent spaces, which fuses robot end-effector positions and force information to enable camera-less and real-time estimation of the user postures during dressing. The latent spaces are created before dressing by modeling the user movements with a Gaussian Process Latent Variable Model, taking the user's movement limitations into account. We introduce a robot-assisted dressing system that combines our tracking method with hierarchical multi-task control to minimize the force between the user and the robot. The experimental results demonstrate the robustness and accuracy of our tracking method. The proposed method enables the Baxter robot to provide personalized dressing assistance in putting on a sleeveless jacket for users with (simulated) upperbody impairments.

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Personalized Robot Assistant for Support in Dressing

Cited by 43 publications

References 31 publications

Personalized collaborative plans for robot-assisted dressing via optimization and simulation

Personalized collaborative plans for robot-assisted dressing via optimization and simulation

Perception of cloth in assistive robotic manipulation tasks

Probabilistic Real-Time User Posture Tracking for Personalized Robot-Assisted Dressing

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