Assistive Robotic Platform Research Articles

A Comparison of Myoelectric Control Modes for an Assistive Robotic Virtual Platform.

In this paper, we propose a daily living situation where objects in a kitchen can be grasped and stored in specific containers using a virtual robot arm operated by different myoelectric control modes. The main goal of this study is to prove the feasibility of providing virtual environments controlled through surface electromyography that can be used for the future training of people using prosthetics or with upper limb motor impairments. We propose that simple control algorithms can be a more natural and robust way to interact with prostheses and assistive robotics in general than complex multipurpose machine learning approaches. Additionally, we discuss the advantages and disadvantages of adding intelligence to the setup to automatically assist grasping activities. The results show very good performance across all participants who share similar opinions regarding the execution of each of the proposed control modes.

Accessibility Evaluation of an Assistive Social Robotic Platform for Rehabilitation and Its Improvement by Means of Haptic Devices

The use of robotic platforms with social capabilities is becoming increasingly common to support people’s daily lives. Such systems are commonly referred to as Socially Assistive Robots (SAR). Many SARs focus on a human-machine interaction based on visual and sound information, which could limit access for users with sight, hearing, or cognitive impairments, as it is usual in health environments. In this paper, we report a qualitative evaluation of the accessibility of Inrobics Rehab platform, arehabilitation platform based on the NAO robot. From the main outcomes, we propose to augment communication channels in social rehabilitation robots with haptic devices. The main aim of this proposal is to increase the accessibility of the platforms by combining multimodal information provided by visual, sound, and tactil channels.

A novel socially assistive robotic platform for cognitive-motor exercises for individuals with Parkinson's Disease: a participatory-design study from conception to feasibility testing with end users.

The potential of socially assistive robots (SAR) to assist in rehabilitation has been demonstrated in contexts such as stroke and cardiac rehabilitation. Our objective was to design and test a platform that addresses specific cognitive-motor training needs of individuals with Parkinson's disease (IwPD). We used the participatory design approach, and collected input from a total of 62 stakeholders (IwPD, their family members and clinicians) in interviews, brainstorming sessions and in-lab feasibility testing of the resulting prototypes. The platform we developed includes two custom-made mobile desktop robots, which engage users in concurrent cognitive and motor tasks. IwPD (n = 16) reported high levels of enjoyment when using the platform (median = 5/5) and willingness to use the platform in the long term (median = 4.5/5). We report the specifics of the hardware and software design as well as the detailed input from the stakeholders.

Assistive Robot with an AI-Based Application for the Reinforcement of Activities of Daily Living: Technical Validation with Users Affected by Neurodevelopmental Disorders

In this work, we propose the first study of a technical validation of an assistive robotic platform, which has been designed to assist people with neurodevelopmental disorders. The platform is called LOLA2 and it is equipped with an artificial intelligence-based application to reinforce the learning of daily life activities in people with neurodevelopmental problems. LOLA2 has been integrated with an ROS-based navigation system and a user interface for healthcare professionals and their patients to interact with it. Technically, we have been able to embed all these modules into an NVIDIA Jetson Xavier board, as well as an artificial intelligence agent for online action detection (OAD). This OAD approach provides a detailed report on the degree of performance of a set of daily life activities that are being learned or reinforced by users. All the human–robot interaction process to work with users with neurodevelopmental disorders has been designed by a multidisciplinary team. Among its main features are the ability to control the robot with a joystick, a graphical user interface application that shows video tutorials with the activities to reinforce or learn, and the ability to monitor the progress of the users as they complete tasks. The main objective of the assistive robotic platform LOLA2 is to provide a system that allows therapists to track how well the users understand and perform daily tasks. This paper focuses on the technical validation of the proposed platform and its application. To do so, we have carried out a set of tests with four users with neurodevelopmental problems and special physical conditions under the supervision of the corresponding therapeutic personnel. We present detailed results of all interventions with end users, analyzing the usability, effectiveness, and limitations of the proposed technology. During its initial technical validation with real users, LOLA2 was able to detect the actions of users with disabilities with high precision. It was able to distinguish four assigned daily actions with high accuracy, but some actions were more challenging due to the physical limitations of the users. Generally, the presence of the robot in the therapy sessions received excellent feedback from medical professionals as well as patients. Overall, this study demonstrates that our developed robot is capable of assisting and monitoring people with neurodevelopmental disorders in performing their daily living tasks.

Preventing Food Waste by the Shelf-Life Dynamical Control in Smart Homes

Currently, smart homes are designed and improved according to four main goals: residents’ wellness, security, comfort, and reduced energy waste. No focus has yet been reserved for one of the most impacting problems of recent years: domestic food waste. In this context, this letter proposes a case study that jointly involves recent advances in smart homes and the need for food waste reduction. The proposed system is divided into two main blocks: the sensing block and the actuation one. The sensing block consists of multiple nodes, which, in the proposed case study, work as dynamic labels being stuck to the good to be monitored. Each node embeds, on a miniaturized board, a set of sensors (i.e., temperature, humidity, and ambient light), whose outcomes are used to extract, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">on-board</i> , the dynamic food shelf life (SL). The presence of an onboard inertial measurement unit also permits the nodes' localization inside the environment. If a sudden decrease in the food SL is recorded by the node and no human interventions occur in a preset timeout, the node is designed to send a call for intervention to the actuation block. In this letter, the actuation block is realized through an assistive robotic platform that can gather coordinates of food from sensor nodes, navigate to them to manipulate the goods, and actuate actions to improve their preservation conditions (increasing the perspective SL). The actuation block is also responsible for notifying the user of the bad storage conditions. The system has been experimentally tested in a laboratory environment. The whole mitigation chain successfully completed all the operations through the robotic platform in 60% of cases. Moreover, comparing food left in poor storage conditions and the same food managed by the our proposed system, an improvement of the food expiration date of ∼55% (on average) has been recorded.

Marvin: An Innovative Omni-Directional Robotic Assistant for Domestic Environments.

Population aging and pandemics have been shown to cause the isolation of elderly people in their houses, generating the need for a reliable assistive figure. Robotic assistants are the new frontier of innovation for domestic welfare, and elderly monitoring is one of the services a robot can handle for collective well-being. Despite these emerging needs, in the actual landscape of robotic assistants, there are no platforms that successfully combine reliable mobility in cluttered domestic spaces with lightweight and offline Artificial Intelligence (AI) solutions for perception and interaction. In this work, we present Marvin, a novel assistive robotic platform we developed with a modular layer-based architecture, merging a flexible mechanical design with cutting-edge AI for perception and vocal control. We focus the design of Marvin on three target service functions: monitoring of elderly and reduced-mobility subjects, remote presence and connectivity, and night assistance. Compared to previous works, we propose a tiny omnidirectional platform, which enables agile mobility and effective obstacle avoidance. Moreover, we design a controllable positioning device, which easily allows the user to access the interface for connectivity and extends the visual range of the camera sensor. Nonetheless, we delicately consider the privacy issues arising from private data collection on cloud services, a critical aspect of commercial AI-based assistants. To this end, we demonstrate how lightweight deep learning solutions for visual perception and vocal command can be adopted, completely running offline on the embedded hardware of the robot.

Extending the Evaluation of Social Assistive Robots With Accessibility Indicators: The AUSUS Evaluation Framework

The introduction of robots in the real world requires previous evaluation of the envisaged performance. Factors like usability, user experience, social acceptance, or societal impact, among others, have been taken into account in evaluation frameworks defined during the last years. However, one of the most important factors that need to be evaluated in any kind of interaction is whether all the users are able to work with the system with the same opportunities and easiness, and none of the current human–robot interaction (HRI) evaluation frameworks include this factor yet. This article proposes an extension of a popular HRI evaluation framework, including accessibility as a new evaluation factor. The proposed approach, named AUSUS, considers Accessibility, Usability, Social acceptance, User experience, and Societal impact. This article presents a use case of the framework, which is evaluated through a socially assistive robotic platform created to perform comprehensive geriatric assessment: the CLARC system. The details of the evaluation process in a hospital and a retirement home are reported, and the main difficulties and recommendations of using AUSUS are discussed.

Role Assignment Analysis of an Assistive Robotic Platform in a High School Mathematics Class, Through a Gamification and Usability Evaluation

This project implements an assistive robotic platform in a mathematics high school class to support the professor’s teaching process while analyzing its performance by using a gamification approach and the Octalysis framework. The results obtained from this study evaluated both the platform usability and the general class perception from the students and the professors involved in the experimentation. This paper demonstrates that the implementation of a robotic platform as a supportive tool for the professor improves the class’ dynamism and the cooperative behavior of the students, by following the Octalysis approach. Finally, the results helped to determine a better role assignment for future cases where the professor implements a robotic platform during class, leaving the theoretical explanations and class control to the professor, and giving the robot the role of enhancing the activities and review exercises.

I-Support: A robotic platform of an assistive bathing robot for the elderly population

In this paper we present a prototype integrated robotic system, the I-Support bathing robot, that aims at supporting new aspects of assisted daily-living activities on a real-life scenario. The paper focuses on describing and evaluating key novel technological features of the system, with the emphasis on cognitive human–robot interaction modules and their evaluation through a series of clinical validation studies. The I-Support project on its whole has envisioned the development of an innovative, modular, ICT-supported service robotic system that assists frail seniors to safely and independently complete an entire sequence of physically and cognitively demanding bathing tasks, such as properly washing their back and their lower limbs. A variety of innovative technologies have been researched and a set of advanced modules of sensing, cognition, actuation and control have been developed and seamlessly integrated to enable the system to adapt to the target population abilities. These technologies include: human activity monitoring and recognition, adaptation of a motorized chair for safe transfer of the elderly in and out the bathing cabin, a context awareness system that provides full environmental awareness, as well as a prototype soft robotic arm and a set of user-adaptive robot motion planning and control algorithms. This paper focuses in particular on the multimodal action recognition system, developed to monitor, analyze and predict user actions with a high level of accuracy and detail in real-time, which are then interpreted as robotic tasks. In the same framework, the analysis of human actions that have become available through the project’s multimodal audio–gestural dataset, has led to the successful modeling of Human–Robot Communication, achieving an effective and natural interaction between users and the assistive robotic platform. In order to evaluate the I-Support system, two multinational validation studies were conducted under realistic operating conditions in two clinical pilot sites. Some of the findings of these studies are presented and analyzed in the paper, showing good results in terms of: (i) high acceptability regarding the system usability by this particularly challenging target group, the elderly end-users, and (ii) overall task effectiveness of the system in different operating modes.

A Socially Assistive Robotic Platform for Upper-Limb Rehabilitation: A Longitudinal Study With Pediatric Patients

In motor rehabilitation therapies, especially with pediatric patients, there is often a loss of interest and motivation due to the lack of variety in exercises and therapeutic activities. NAOTherapist (NT) is a socially assistive robotics (SAR) platform designed to support hands-off rehabilitation sessions through two interactive games: mirror and Simon. It integrates a cognitive architecture with an NAO humanoid robot that acts as a coach, as well as a red-green-blue-depth (RGB-D) sensor that eases body capture. This work aims to deploy and evaluate the developed technology for a long-term experience.

Soft Biometrics for a Socially Assistive Robotic Platform

AbstractIn thiswork, a real-time system able to automatically recognize soft-biometric traits is introduced and used to improve the capability of a humanoid robot to interact with humans. In particular the proposed system is able to estimate gender and age of humans in images acquired from the embedded camera of the robot. This knowledge allows the robot to properly react with customized behaviors related to the gender/age of the interacting individuals. The system is able to handle multiple persons in the same acquired image, recognizing the age and gender of each person in the robot’s field of view. These features make the robot particularly suitable to be used in socially assistive applications.

Assistive/Socially Assistive Robotic Platform for Therapy and Recovery: Patient Perspectives

Improving adherence to therapy is a critical component of advancing outcomes and reducing the cost of rehabilitation. A robotic platform was previously developed to explore how robotics could be applied to the social dimension of rehabilitation to improve adherence. This paper aims to report on feedback given by end users of the robotic platform as well as the practical applications that socially assistive robotics could have in the daily life activities of a patient. A group of 10 former and current patients interacted with the developed robotic platform during a simulated exercise session before taking an experience-based survey. A portion of these participants later provided verbal feedback as part of a focus group on the potential utility of such a platform. Identified applications included assistance with reaching exercise goals, managing to-do lists, and supporting participation in social and recreational activities. The study participants expressed that the personality characteristics of the robotic system should be adapted to individual preferences and that the assistance provided over time should align with the progress of their recovery. The results from this study are encouraging and will be useful for further development of socially assistive robotics.