A multi-modal perception based assistive robotic system for the elderly

Edited by Giovanni Maria Farinella, Takeo Kanade, Marco Leo, Gerard G. Medioni, Mohan TrivediInternational audienceIn this paper, we present a multi-modal perception based framework to realize a non-intrusive domestic assistive robotic system. It is non-intrusive in that it only starts interaction with a user when it detects the user's intention to do so. All the robot's actions are based on multi-modal perceptions which include user detection based on RGB-D data, user's intention-for-interaction detection with RGB-D and audio data, and communication via user distance mediated speech recognition. The utilization of multi-modal cues in different parts of the robotic activity paves the way to successful robotic runs (94% success rate). Each presented perceptual component is systematically evaluated using appropriate dataset and evaluation metrics. Finally the complete system is fully integrated on the PR2 robotic platform and validated through system sanity check runs and user studies with the help of 17 volunteer elderly participants

Case Study on Human-Robot Interaction of the Remote-Controlled Service Robot for Elderly and Disabled Care

The tendency of continuous aging of the population and the increasing number of people with mobility difficulties leads to increased research in the field of Assistive Service Robotics. These robots can help with daily life tasks such as reminding to take medications, serving food and drinks, controlling home appliances and even monitoring health status. When talking about assisting people in their homes, it should be noted that they will, most of the time, have to communicate with the robot themselves and be able to manage it so that they can get the most out of the robot's services. This research is focused on different methods of remote control of a mobile robot equipped with robotic manipulator. The research investigates in detail methods based on control via gestures, voice commands, and web-based graphical user interface. The capabilities of these methods for Human-Robot Interaction (HRI) have been explored in terms of usability. In this paper, we introduce a new version of the robot Robco 19, new leap motion sensor control of the robot and a new multi-channel control system. The paper presents methodology for performing the HRI experiments from human perception and summarizes the results in applications of the investigated remote control methods in real life scenarios

Multi-layered map based navigation and interaction for an intelligent wheelchair

Intelligent wheelchair is a paradigm of assisted living applications for elderly and disabled people. Its autonomous navigation and human-robot interaction is the major challenge. The previous intelligent wheelchair research has been mainly focused on geometric map based navigation, which is computational expensive in a large scale environment. This paper proposes the use of multi-layered maps for navigation and interaction of an intelligent wheelchair. The semantic information can improve the efficiency of path planning and navigation as well as extend the capability of task planning for the wheelchair. Some experimental results are given to demonstrate the feasibility and performance of the proposed approach

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

A survey of technologies supporting design of a multimodal interactive robot for military communication

Purpose – This paper presents a survey of research into interactive robotic systems for the purpose of identifying the state of the art capabilities as well as the extant gaps in this emerging field. Communication is multimodal. Multimodality is a representation of many modes chosen from rhetorical aspects for its communication potentials. The author seeks to define the available automation capabilities in communication using multimodalities that will support a proposed Interactive Robot System (IRS) as an AI mounted robotic platform to advance the speed and quality of military operational and tactical decision making. Design/methodology/approach – This review will begin by presenting key developments in the robotic interaction field with the objective of identifying essential technological developments that set conditions for robotic platforms to function autonomously. After surveying the key aspects in Human Robot Interaction (HRI), Unmanned Autonomous System (UAS), visualization, Virtual Environment (VE) and prediction, the paper then proceeds to describe the gaps in the application areas that will require extension and integration to enable the prototyping of the IRS. A brief examination of other work in HRI-related fields concludes with a recapitulation of the IRS challenge that will set conditions for future success. Findings – Using insights from a balanced cross section of sources from the government, academic, and commercial entities that contribute to HRI a multimodal IRS in military communication is introduced. Multimodal IRS (MIRS) in military communication has yet to be deployed. Research limitations/implications – Multimodal robotic interface for the MIRS is an interdisciplinary endeavour. This is not realistic that one can comprehend all expert and related knowledge and skills to design and develop such multimodal interactive robotic interface. In this brief preliminary survey, the author has discussed extant AI, robotics, NLP, CV, VDM, and VE applications that is directly related to multimodal interaction. Each mode of this multimodal communication is an active research area. Multimodal human/military robot communication is the ultimate goal of this research. Practical implications – A multimodal autonomous robot in military communication using speech, images, gestures, VST and VE has yet to be deployed. Autonomous multimodal communication is expected to open wider possibilities for all armed forces. Given the density of the land domain, the army is in a position to exploit the opportunities for human–machine teaming (HMT) exposure. Naval and air forces will adopt platform specific suites for specially selected operators to integrate with and leverage this emerging technology. The possession of a flexible communications means that readily adapts to virtual training will enhance planning and mission rehearsals tremendously. Social implications – Interaction, perception, cognition and visualization based multimodal communication system is yet missing. Options to communicate, express and convey information in HMT setting with multiple options, suggestions and recommendations will certainly enhance military communication, strength, engagement, security, cognition, perception as well as the ability to act confidently for a successful mission. Originality/value – The objective is to develop a multimodal autonomous interactive robot for military communications. This survey reports the state of the art, what exists and what is missing, what can be done and possibilities of extension that support the military in maintaining effective communication using multimodalities. There are some separate ongoing progresses, such as in machine-enabled speech, image recognition, tracking, visualizations for situational awareness, and virtual environments. At this time, there is no integrated approach for multimodal human robot interaction that proposes a flexible and agile communication. The report briefly introduces the research proposal about multimodal interactive robot in military communication

Robotic Platforms for Assistance to People with Disabilities

People with congenital and/or acquired disabilities constitute a great number of dependents today. Robotic platforms to help people with disabilities are being developed with the aim of providing both rehabilitation treatment and assistance to improve their quality of life. A high demand for robotic platforms that provide assistance during rehabilitation is expected because of the health status of the world due to the COVID-19 pandemic. The pandemic has resulted in countries facing major challenges to ensure the health and autonomy of their disabled population. Robotic platforms are necessary to ensure assistance and rehabilitation for disabled people in the current global situation. The capacity of robotic platforms in this area must be continuously improved to benefit the healthcare sector in terms of chronic disease prevention, assistance, and autonomy. For this reason, research about human–robot interaction in these robotic assistance environments must grow and advance because this topic demands sensitive and intelligent robotic platforms that are equipped with complex sensory systems, high handling functionalities, safe control strategies, and intelligent computer vision algorithms. This Special Issue has published eight papers covering recent advances in the field of robotic platforms to assist disabled people in daily or clinical environments. The papers address innovative solutions in this field, including affordable assistive robotics devices, new techniques in computer vision for intelligent and safe human–robot interaction, and advances in mobile manipulators for assistive tasks

Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language

Large foundation models can exhibit unique capabilities depending on the domain of data they are trained on. While these domains are generic, they may only barely overlap. For example, visual-language models (VLMs) are trained on Internet-scale image captions, but large language models (LMs) are further trained on Internet-scale text with no images (e.g. from spreadsheets, to SAT questions). As a result, these models store different forms of commonsense knowledge across different domains. In this work, we show that this model diversity is symbiotic, and can be leveraged to build AI systems with structured Socratic dialogue -- in which new multimodal tasks are formulated as a guided language-based exchange between different pre-existing foundation models, without additional finetuning. In the context of egocentric perception, we present a case study of Socratic Models (SMs) that can provide meaningful results for complex tasks such as generating free-form answers to contextual questions about egocentric video, by formulating video Q&A as short story Q&A, i.e. summarizing the video into a short story, then answering questions about it. Additionally, SMs can generate captions for Internet images, and are competitive with state-of-the-art on zero-shot video-to-text retrieval with 42.8 R@1 on MSR-VTT 1k-A. SMs demonstrate how to compose foundation models zero-shot to capture new multimodal functionalities, without domain-specific data collection. Prototypes are available at socraticmodels.github.io.Comment: https://socraticmodels.github.io