Overcoming barriers and increasing independence: service robots for elderly and disabled people

This paper discusses the potential for service robots to overcome barriers and increase independence of elderly and disabled people. It includes a brief overview of the existing uses of service robots by disabled and elderly people and advances in technology which will make new uses possible and provides suggestions for some of these new applications. The paper also considers the design and other conditions to be met for user acceptance. It also discusses the complementarity of assistive service robots and personal assistance and considers the types of applications and users for which service robots are and are not suitable

Cognitive assisted living ambient system: a survey

The demographic change towards an aging population is creating a significant impact and introducing drastic challenges to our society. We therefore need to find ways to assist older people to stay independently and prevent social isolation of these population. Information and Communication Technologies (ICT) provide various solutions to help older adults to improve their quality of life, stay healthier, and live independently for a time. Ambient Assisted Living (AAL) is a field to investigate innovative technologies to provide assistance as well as healthcare and rehabilitation to impaired seniors. The paper provides a review of research background and technologies of AAL

Semantics-based platform for context-aware and personalized robot interaction in the internet of robotic things

Robots are moving from well-controlled lab environments to the real world, where an increasing number of environments has been transformed into smart sensorized IoT spaces. Users will expect these robots to adapt to their preferences and needs, and even more so for social robots that engage in personal interactions. In this paper, we present declarative ontological models and a middleware platform for building services that generate interaction tasks for social robots in smart IoT environments. The platform implements a modular, data-driven workflow that allows developers of interaction services to determine the appropriate time, content and style of human-robot interaction tasks by reasoning on semantically enriched loT sensor data. The platform also abstracts the complexities of scheduling, planning and execution of these tasks, and can automatically adjust parameters to the personal profile and current context. We present motivational scenarios in three environments: a smart home, a smart office and a smart nursing home, detail the interfaces and executional paths in our platform and present a proof-of-concept implementation. (C) 2018 Elsevier Inc. All rights reserved

Learning human navigational skill for smart wheelchair.

by Hon Nin Chow.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.Includes bibliographical references (leaves 79-84).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Motivation --- p.1Chapter 1.2 --- Organization of the Thesis --- p.3Chapter 2 --- Literature Survey --- p.6Chapter 2.1 --- Learning-by-Demonstration --- p.6Chapter 2.2 --- Neural Networks --- p.7Chapter 2.3 --- Navigation Learning --- p.8Chapter 2.4 --- Localization --- p.9Chapter 2.5 --- Robotic Wheelchair --- p.10Chapter 3 --- System Implementation --- p.12Chapter 3.1 --- Hardware Platform --- p.12Chapter 3.2 --- Software Platform --- p.14Chapter 3.3 --- Basic Functionality --- p.15Chapter 3.3.1 --- Collision Avoidance --- p.15Chapter 3.3.2 --- Wearable Eye-jaw Control Interface --- p.16Chapter 4 --- Learning Human Navigational Skill --- p.22Chapter 4.1 --- Introduction --- p.22Chapter 4.2 --- Problem Formulation --- p.23Chapter 4.3 --- Approach --- p.23Chapter 4.4 --- Experimental Study --- p.26Chapter 4.4.1 --- Settings --- p.26Chapter 4.4.2 --- Results --- p.30Chapter 4.5 --- Discussions --- p.31Chapter 5 --- Learning from Multi-phase Demonstrations --- p.33Chapter 5.1 --- Introduction --- p.33Chapter 5.2 --- Problem Formulation --- p.34Chapter 5.3 --- Approach --- p.35Chapter 5.4 --- Experimental Study --- p.35Chapter 5.4.1 --- Settings --- p.35Chapter 5.4.2 --- Results --- p.37Chapter 5.5 --- Evaluation of Learning Performance --- p.37Chapter 5.6 --- Discussions --- p.43Chapter 6 --- Localization Learning --- p.44Chapter 6.1 --- Introduction --- p.44Chapter 6.2 --- Problem Formulation --- p.45Chapter 6.3 --- Approach --- p.45Chapter 6.4 --- Experimental Study --- p.46Chapter 6.4.1 --- Settings --- p.46Chapter 6.4.2 --- Result 1: Localization Performance --- p.47Chapter 6.4.3 --- Result 2: Similar Sensor Patterns in Various Configurations . --- p.53Chapter 6.4.4 --- Result 3: Small Variations in Major Dimensions of Environ- mental Feature along the Route --- p.53Chapter 6.5 --- Discussions --- p.59Chapter 6.5.1 --- Accuracy --- p.59Chapter 6.5.2 --- Choices of Sensor-Configuration Mappings --- p.60Chapter 7 --- Conclusion --- p.62Chapter 7.1 --- Contributions --- p.62Chapter 7.2 --- Future Work --- p.65Chapter A --- Cascade Neural Network --- p.67Chapter B --- Trajectories for the Navigation Learning in Chapter 4 --- p.69Chapter C --- Publications Resulted from the Study --- p.7

Mechatronic Systems

Mechatronics, the synergistic blend of mechanics, electronics, and computer science, has evolved over the past twenty five years, leading to a novel stage of engineering design. By integrating the best design practices with the most advanced technologies, mechatronics aims at realizing high-quality products, guaranteeing at the same time a substantial reduction of time and costs of manufacturing. Mechatronic systems are manifold and range from machine components, motion generators, and power producing machines to more complex devices, such as robotic systems and transportation vehicles. With its twenty chapters, which collect contributions from many researchers worldwide, this book provides an excellent survey of recent work in the field of mechatronics with applications in various fields, like robotics, medical and assistive technology, human-machine interaction, unmanned vehicles, manufacturing, and education. We would like to thank all the authors who have invested a great deal of time to write such interesting chapters, which we are sure will be valuable to the readers. Chapters 1 to 6 deal with applications of mechatronics for the development of robotic systems. Medical and assistive technologies and human-machine interaction systems are the topic of chapters 7 to 13.Chapters 14 and 15 concern mechatronic systems for autonomous vehicles. Chapters 16-19 deal with mechatronics in manufacturing contexts. Chapter 20 concludes the book, describing a method for the installation of mechatronics education in schools

Towards a Legal end Ethical Framework for Personal Care Robots. Analysis of Person Carrier, Physical Assistant and Mobile Servant Robots.

Technology is rapidly developing, and regulators and robot creators inevitably have to come to terms with new and unexpected scenarios. A thorough analysis of this new and continuosuly evolving reality could be useful to better understand the current situation and pave the way to the future creation of a legal and ethical framework. This is clearly a wide and complex goal, considering the variety of new technologies available today and those under development. Therefore, this thesis focuses on the evaluation of the impacts of personal care robots. In particular, it analyzes how roboticists adjust their creations to the existing regulatory framework for legal compliance purposes. By carrying out an impact assessment analysis, existing regulatory gaps and lack of regulatory clarity can be highlighted. These gaps should of course be considered further on by lawmakers for a future legal framework for personal care robot. This assessment should be made first against regulations. If the creators of the robot do not encounter any limitations, they can then proceed with its development. On the contrary, if there are some limitations, robot creators will either (1) adjust the robot to comply with the existing regulatory framework; (2) start a negotiation with the regulators to change the law; or (3) carry out the original plan and risk to be non-compliant. The regulator can discuss existing (or lacking) regulations with robot developers and give a legal response accordingly. In an ideal world, robots are clear of impacts and therefore threats can be responded in terms of prevention and opportunities in form of facilitation. In reality, the impacts of robots are often uncertain and less clear, especially when they are inserted in care applications. Therefore, regulators will have to address uncertain risks, ambiguous impacts and yet unkown effects