Human-Robot Interaction (HRI) has recently received considerable attention in the academic community, in labs, in technology companies, and through the media. Because of this attention, it is desirable to present a survey of HRI to serve as a tutorial to people outside the field and to promote discussion of a unified vision of HRI within the field. The goal of this review is to present a unified treatment of HRI-related problems, to identify key themes, and discuss challenge problems that are likely to shape the field in the near future. Although the review follows a survey structure, the goal of presenting a coherent "story" of HRI means that there are necessarily some well-written, intriguing, and influential papers that are not referenced. Instead of trying to survey every paper, we describe the HRI story from multiple perspectives with an eye toward identifying themes that cross applications. The survey attempts to include papers that represent a fair cross section of the universities, government efforts, industry labs, and countries that contribute to HRI, and a cross section of the disciplines that contribute to the field, such as human, factors, robotics, cognitive psychology, and design.

/pdf/human-robot-interaction-a-survey-4q8yi606a9.pdf

Human-Robot Interaction: A Survey

Research on sensor-based activity recognition has, recently, made significant progress and is attracting growing attention in a number of disciplines and application domains. However, there is a lack of high-level overview on this topic that can inform related communities of the research state of the art. In this paper, we present a comprehensive survey to examine the development and current status of various aspects of sensor-based activity recognition. We first discuss the general rationale and distinctions of vision-based and sensor-based activity recognition. Then, we review the major approaches and methods associated with sensor-based activity monitoring, modeling, and recognition from which strengths and weaknesses of those approaches are highlighted. We make a primary distinction in this paper between data-driven and knowledge-driven approaches, and use this distinction to structure our survey. We also discuss some promising directions for future research.

Sensor-Based Activity Recognition

http://www.eis.mdx.ac.uk/staffpages/juanaugusto/CookAJ2009.pdf

Review: Ambient intelligence: Technologies, applications, and opportunities

How smart are our environments? An updated look at the state of the art

The machine learning and pervasive sensing technologies found in smart homes offer unprecedented opportunities for providing health monitoring and assistance to individuals experiencing difficulties living independently at home. In order to monitor the functional health of smart home residents, we need to design technologies that recognize and track activities that people normally perform as part of their daily routines. Although approaches do exist for recognizing activities, the approaches are applied to activities that have been preselected and for which labeled training data are available. In contrast, we introduce an automated approach to activity tracking that identifies frequent activities that naturally occur in an individual's routine. With this capability, we can then track the occurrence of regular activities to monitor functional health and to detect changes in an individual's patterns and lifestyle. In this paper, we describe our activity mining and tracking approach, and validate our algorithms on data collected in physical smart environments.

/pdf/discovering-activities-to-recognize-and-track-in-a-smart-4qq6qosqiq.pdf

Discovering Activities to Recognize and Track in a Smart Environment

The rise of Alzheimer’s disease is one of the greatest health crises facing the industrialized world. Today, approximately four million Americans suffer from Alzheimer’s disease; by 2050, the number is expected to rise to 15 million people. As a result of the increasing longevity of the elderly, many sufferers are now aware that their capacities to remember, to learn, and to carry out the tasks of everyday life are slowly being lost. The Assisted Cognition Project is a new joint effort between the University of Washington’s Department of Computer Science, Medical Center, and Alzheimer’s Disease Research Center that is exploring the use of AI systems to support and enhance the independence and quality of life of Alzheimer’s patients. The goal of the Assisted Cognition project is to develop novel computer systems that will enhance the quality of life of people suffering from Alzheimer’s Disease and similar cognitive disorders. Assisted Cognition systems use ubiquitous computing and artificial intelligence technology to replace some of the memory and problem-solving abilities that have been lost by an Alzheimer’s patient. Two concrete examples of the Assisted Cognition systems we are developing are an ACTIVITY COMPASS that helps reduce spatial disorientation both inside and outside the home, and an ADAPTIVE PROMPTER that helps patients carry out multi-step everyday tasks.

/pdf/an-overview-of-the-assisted-cognition-project-12azjo3ynh.pdf

An Overview of the Assisted Cognition Project

Labscape is a smart environment that we designed to improve the experience of people who work in a cell biology laboratory. Our goal in creating it was to simplify, laboratory work by making information available where it is needed and by collecting and organizing data where and when it is created into a formal representation that others can understand and process. By helping biologists produce a more complete record of their work with less effort, Labscape is designed to foster improved collaboration in conjunction with increased individual efficiency and satisfaction. A user-driven system, although technologically conservative, embraces a central goal of ubiquitous computing: to enhance the ability to perform domain tasks through fluid interaction with computational resources. Smart environments could soon replace the pen and paper commonly used in the laboratory setting.

/pdf/labscape-a-smart-environment-for-the-cell-biology-laboratory-2z17bemjdk.pdf

Labscape: a smart environment for the cell biology laboratory

To be successful, ubicomp applications must be designed with their environment and users in mind and evaluated to confirm that they do not disrupt the users' natural workflow. Well-established techniques for understanding users and their environment exist, but are not specifically designed to assess how well the computing and physical task environments blend. We present strengths and weaknesses of several qualitative and quantitative user study techniques for ubicomp. We applied these techniques to the design and evaluation of a ubicomp application for cell biology laboratories (Labscape). We describe how these techniques helped identify design considerations that were crucial for Lab-scape's adoption and demonstrate their ability to measure how effectively applications blend into an environment.

User Study Techniques in the Design and Evaluation of a Ubicomp Environment

Labscape, a ubiquitous computing environment for cell biologists, was implemented twice: once using only standard tools for distributed systems (TCP sockets and shared file systems) and once using one.world, a runtime system designed specifically to support ubiquitous applications. We analyze Labscape in terms of the system properties that are required to provide a fluid user experience. Though the two implementations are functionally and architecturally similar, we found a significant difference in the degree to which they each exhibited the required properties. The fact that one.world was not designed specifically with Labscape in mind yet was found to support the application's requirements well suggests that ubiquitous applications have many aspects in common, and can benefit from a system support layer for coping with dynamic environments. We present, in detail, the concepts embodied in one.world that we have found to be most important for Labscape, and how some of these concepts might be extended.

/pdf/systems-support-for-ubiquitous-computing-a-case-study-of-two-2qhyxlaqag.pdf

Systems Support for Ubiquitous Computing: A Case Study of Two Implementations of Labscape

Our objective is to eliminate the digital divide that persists between the physical and information spaces of wet-lab based enterprises by embedding computational resources into the shared laborato...

https://journals.sagepub.com/doi/pdf/10.1016/S1535-5535-04-00119-4

Larry Arnstein

Papers

An Overview of the Assisted Cognition Project

Labscape: a smart environment for the cell biology laboratory

User Study Techniques in the Design and Evaluation of a Ubicomp Environment

Systems Support for Ubiquitous Computing: A Case Study of Two Implementations of Labscape

Ubiquitous Computing in the Biology Laboratory