CARE: Cooperation of ai Robot Enablers to Create a Vibrant Society

Abstract

emographic changes in our society are putting a heavy burden on care facilities and health-care infrastructure. While the elderly population is steadily increasing, there is an acute shortage of caregiving experts and professionals. This problem is becoming more severe in superaging societies, namely, Japan. Hence, this urges new and practical solutions for welfare facilities to mitigate the burden on caregivers and human supporting partners by introducing robotics assistance through information and communication technology (ICT). In this work, we present a new multirobot cooperation and coordination framework at different intellectual computation levels for care facilities. The framework is developed to bring the health-care 4.0 concept one step closer to reality, under the ongoing project "Moonshot Research & Development, " in Japan. First, we present an Internet of Things (IoT) integration system that is designed to include different passive and active assistive robots. Then, we redesign robot systems and develop a semiautonomous platform that can perform tasks based on user/patient interaction in real-world care facility scenarios. Our framework provides human-robot interaction under shared autonomy between the user and assisting robots to improve the efficacy of the users in everyday tasks. Tohoku University's new state-of-the-art Living Lab facility is used to prepare a real-world scenario, where we present our experimental results. We also discuss the open problems in future care and human assistance aspects.

Safety for Human-Robot Interaction with a Shared Autonomy

“…In this problem, the person's information is captured with inertia measurement sensors (IMU). The whole concept of multi-robot cooperation for human assistance is given in our previous study [7]. Similarly, a wireless IMU sensor is attached to a person's chest.…”

An Object-oriented Navigation Strategy for Service Robots Leveraging Semantic Information

“…After the termination criteria are met, the user can provide the following input, and the navigation sequence is repeated. In future, we will extend the semantic navigation node so it can interface with different services like Siri or Alexa [16].…”

“…Semantic SLAM is also important to foster human-robot interactions and multi-robot collaboration tasks. A high-level 'scene-awareness' is critical to deploying service robots in environments like healthcare facilities or restaurants [15], [16] Earlier approaches in semantic mapping used the 'bag of key points' approach for object detection, and image descriptors such as SIFT for localizing the object in the map [17]. More recently, the Habitat challenge [18], [19] focused on the context-driven exploration of indoor scenes.…”

Nursing Care Teaching System Based on Mixed Reality for Effective Caregiver-Patient Interaction

“…2). This nursing care action is not easy to learn because it requires the appropriate nursing care action according to the current situation in multiple steps [16]. In this study, we propose a system that can teach appropriate nursing care actions according to the current situation in multiple procedures by combining pose estimation of a patient using depth camera information and teaching using an MR device.…”