Light-based nonverbal signaling with passive demonstrations for mobile service robots

With emerging applications in robotics that have the potential to bring them into our daily lives, it is expected for them to not only operate in close proximity to humans but also interact with them as well. When operating in crowded, human-populated environments there are many communication challenges faced by robots due to variable levels of interactions (e.g. asking for help, giving information, or navigating near humans). A crucial factor for success in these interactions is a robot’s ability to express information about their intent, actions, and knowledge to co-located humans. Many of the robot platforms developed for service roles have non-anthropomorphic form factors in order to simplify and tailor them to their jobs. Due to a lack of anthropomorphic features, these types of robots primarily communicate using an on-screen display and/or spoken language. To overcome the limitation of not communicating as people do, we explore the viability of nonverbal light-based signals as a communication modality for mobile service robots. These types of signals have many benefits over existing modalities which they can either complement or replace when appropriate, such as having long-range visibility and persisting over time. We present a novel light-based signal control architecture implemented as a custom Robot Operating System (ROS) software package generalized to allow for various signal implementations. We implement our framework on a BWIBot, an autonomous mobile service robot created as part of the Building-Wide Intelligence Project, and evaluate its validity through a real-world user study on the scenario where a robot and human are traversing a shared corridor from opposite ends, and the potential conflict created when their paths meet. Our results demonstrate that exposing users to the robot’s use of an animated light signal only once prior to when it is information critical for the user is sufficient to disambiguate its meaning, and thus greatly enhances its utility in-situ, with no direct instruction or training to the user. These findings suggest a paradigm of passive demonstration of light-based signals in future applications.Computer Science

Intelligent Physical Robots in Health Care: Systematic Literature Review

Background: Intelligent physical robots based on artificial intelligence have been argued to bring about dramatic changes in health care services. Previous research has examined the use of intelligent physical robots in the health care context from different perspectives; however, an overview of the antecedents and consequences of intelligent physical robot use in health care is lacking in the literature. Objective: In this paper, we aimed to provide an overview of the antecedents and consequences of intelligent physical robot use in health care and to propose potential agendas for future research through a systematic literature review. Methods: We conducted a systematic literature review on intelligent physical robots in the health care field following the guidelines of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). Literature searches were conducted in 5 databases (PubMed, Scopus, PsycINFO, Embase, and CINAHL) in May 2021, focusing on studies using intelligent physical robots for health care purposes. Subsequently, the quality of the included studies was assessed using the Mixed Methods Appraisal Tool. We performed an exploratory content analysis and synthesized the findings extracted from the included articles. Results: A total of 94 research articles were included in the review. Intelligent physical robots, including mechanoid, humanoid, android, and animalistic robots, have been used in hospitals, nursing homes, mental health care centers, laboratories, and patients’ homes by both end customers and health care professionals. The antecedents for intelligent physical robot use are categorized into individual-, organization-, and robot-related factors. Intelligent physical robot use in the health care context leads to both non–health-related consequences (emotional outcomes, attitude and evaluation outcomes, and behavioral outcomes) and consequences for (physical, mental, and social) health promotion for individual users. Accordingly, an integrative framework was proposed to obtain an overview of the antecedents and consequences of intelligent physical robot use in the health care context. Conclusions: This study contributes to the literature by summarizing current knowledge in the field of intelligent physical robot use in health care, by identifying the antecedents and the consequences of intelligent physical robot use, and by proposing potential future research agendas in the specific area based on the research findings in the literature and the identified knowledge gaps.publishedVersionPeer reviewe

Robust Door Operation with the Toyota Human Support Robot. Robotic perception, manipulation and learning

Robots are progressively spreading to urban, social and assistive domains. Service robots operating in domestic environments typically face a variety of objects they have to deal with to fulfill their tasks. Some of these objects are articulated such as cabinet doors and drawers. The ability to deal with such objects is relevant, as for example navigate between rooms or assist humans in their mobility. The exploration of this task rises interesting questions in some of the main robotic threads such as perception, manipulation and learning. In this work a general framework to robustly operate different types of doors with a mobile manipulator robot is proposed. To push the state-of-the-art, a novel algorithm, that fuses a Convolutional Neural Network with point cloud processing for estimating the end-effector grasping pose in real-time for multiple handles simultaneously from single RGB-D images, is proposed. Also, a Bayesian framework that embodies the robot with the ability to learn the kinematic model of the door from observations of its motion, as well as from previous experiences or human demonstrations. Combining this probabilistic approach with state-of-the-art motion planninOutgoin

Sistema Autónomo de Teleasistencia Robótica mediante técnicas de Inteligencia Artificial

El objetivo de este proyecto es implementar una arquitectura de control autónoma en un robot comercial orientado a ofrecer servicios de asistencia domiciliaria. Para ello, la arquitectura de control debe ser capaz de generar un plan que cumpla con los objetivos fijados por el usuario, permitiendo la movilidad por todo el hogar. Además, dicha arquitectura de control debe monitorizar el estado de ejecución del plan asegurando la integridad del robot mediante la verificación de la ejecución de las acciones planificadas en un entorno dinámico, consiguiendo un grado de autonomía aceptable para la aplicación que se quiere conseguir.The aim of this project is to implement an autonomous control architecture in a commercial robot with the objective of providing home care services. This control architecture should be able to generate a plan that meets the targets set by the user, allowing mobility throughout the home. In addition the control architecture should monitor the execution status of the plan, ensuring the integrity of the robot by verifying the implementation of the actions planned in a dynamic environment, achieving an acceptable degree of autonomy for the application to be achieved.Máster Universitario en Ingeniería de Telecomunicación (M125