Service robots are designed to assist and aid humans in the day to day tasks as well as specific and minute tasks. In recent years there has been an increase in both demand and production of service robots. These robots are slowly becoming more prolific both in personal settings such as the home, and professional settings such as restaurants and hospitals. Despite this growth, there are still major challenges preventing service robots from being ubiquitous and operating intelligently in these unstructured domestic environments. Like many autonomous robots, the technical challenges of service robots revolve around three main facets: sensing and modeling their environment, understanding and reasoning about said environment, and acting in a way that is safe and conducive towards a task goal. Unlike industry robots, service robots operate in dynamic environments and have tasks that cannot always be completed repetitively. This presents a rich set of challenges to solve in all three areas. One exemplary task of this for service robots is tidying objects within the home. This task is important as it helps assist with activity of daily living (ADL) while meeting consumer demand. A few concrete illustrations of the challenges of this task are shown when we consider the robot must sense objects and ground language of these objects before we can determine where the objects belong. Notions of a correct placement vary as each user has their own personal preference to organization. Grasping and manipulating the objects as well as navigating within the environment must also be accomplished in order to successfully complete the task. In this dissertation we present several contributions that help address these challenges and the surrounding gaps towards solving these issues. First, we explore the use of a service robot to put away the groceries in a precise and stable configuration that satisfies the desired semantic relationship of grocery and pantry objects. Second we explore the ability of our robot to put away objects throughout a home environment based on a user preference using a recommender system approach. We share details of our implementation of these systems through real-world experiments.

Copyright ©2015 Zhejiang University Press, Published by Elsevier Inc. Household Service Robotics is a collection of the latest technological advances in household service robotics in five main areas: robot systems, manipulation, navigation, object recognition, and human-robot interaction. The book enables readers to understand development s and apply them to their own working areas, including: Robotic technologies for assisted living and elderly care Domestic cleaning automation Household surveillance Guiding systems for public spaces Service robotics is a highly multidisciplinary field, requiring a holistic approach. This handbook provides insights to the disciplines involved in the field as well as advanced methods and techniques that enable the scale-up of theory to actual systems. It includes coverage of functionalities such as vision systems, location control, and HCI, which are important in domestic settings. Provides a single source collection of the latest development in domestic robotic systems and control Covers vision systems, location control, and HCI, important in domestic settings Focuses on algorithms for object recognition, manipulation, human-robot interaction, and navigation for household robotics

Maintaining an organized lifestyle is an important domestic routine that reduces the effects of poor mental and physical health associated with clutter. While there have been many previous studies on domestic assistive robotics, a gap remains in creating a system of (wall-based) robotic organizers to understand human behaviors. This dissertation proposes a multi-robot system of wall-climbing organizers called SORT (Stuff Organizing Robot Team), aimed to help people sort, retrieve and deliver domestic items. This research contributes knowledge in four main areas: wall-climbing assistive robots, human-multi robot interaction, impact of cultural differences on HRI, and understanding people's organizational behaviors. To explore previously under-utilized domains within the home where robots can live, SORT is proposed as a wall-climbing system that demonstrates potentials for indoor assistive uses. This dissertation presents the design and fabrication process of two prototypes, one based on vacuum suction which was successfully tested on a whiteboard wall with a tethered controller, the other based on magnets and was successfully tested on a ferrous surface controlled by a cellphone app. To enrich the field of human-multi robot interaction, multiple user studies (online and in-person) were conducted to understand people's reactions toward SORT. The results showed users' preferences on robot group size, speed, formation shapes, movement path, communication gestures and perceived usefulness and usability. An additional online study was conducted to explore how cultural differences may play a role in shaping users' preferences and perceptions toward SORT with 191 participant responses from US, China and India. Our results showed significant differences that contradict prior stereotypes and reinforced the importance of considering cultural differences in HRI studies. The qualitative results in this dissertation reveal important findings on human behaviors in sorting tasks, such as organizational logic, decision making, and perceptions of control. These findings can provide insights on how future researchers may design multi-robot assistive systems at home. As assistive robots are becoming more ubiquitous in our everyday lives, it is important for designers, engineers and researchers to understand people's needs, preferences and perceptions toward robotic assistants, especially when the robots are embedded within a larger Internet of Things ecosystem. This dissertation shows that a multi-robot group, like SORT, can successfully enhance domestic routines to improve people's life qualities (80% participant satisfaction). We as design researchers must also take a multi-disciplinary approach, considering previously under-studied areas such as human-multi robot interaction and building cultural differences as design variables to ensure the robot group's holistic success.

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. Highlights different data techniques in healthcare data analysis, including machine learning and data mining Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks Includes applications and case studies across all areas of AI in healthcare data

Trust in Human-Robot Interaction addresses the gamut of factors that influence trust of robotic systems. The book presents the theory, fundamentals, techniques and diverse applications of the behavioral, cognitive and neural mechanisms of trust in human-robot interaction, covering topics like individual differences, transparency, communication, physical design, privacy and ethics. Presents a repository of the open questions and challenges in trust in HRI Includes contributions from many disciplines participating in HRI research, including psychology, neuroscience, sociology, engineering and computer science Examines human information processing as a foundation for understanding HRI Details the methods and techniques used to test and quantify trust in HRI

The U.S. Census Bureau has reported that 56.7 million Americans had some type of disability in 2010, which represents 18.7 percent of the civilian noninstitutionalized population included in the 2010 Survey of Income and Program Participation. The U.S. Social Security Administration (SSA) provides disability benefits through the Social Security Disability Insurance (SSDI) program and the Supplemental Security Income (SSI) program. As of December 2015, approximately 11 million individuals were SSDI beneficiaries, and about 8 million were SSI beneficiaries. SSA currently considers assistive devices in the nonmedical and medical areas of its program guidelines. During determinations of substantial gainful activity and income eligibility for SSI benefits, the reasonable cost of items, devices, or services applicants need to enable them to work with their impairment is subtracted from eligible earnings, even if those items or services are used for activities of daily living in addition to work. In addition, SSA considers assistive devices in its medical disability determination process and assessment of work capacity. The Promise of Assistive Technology to Enhance Activity and Work Participation provides an analysis of selected assistive products and technologies, including wheeled and seated mobility devices, upper-extremity prostheses, and products and technologies selected by the committee that pertain to hearing and to communication and speech in adults.