Maja Mataric - US grants

9512448 Mataric The proposed project is to establish and support a new laboratory for adaptive behavior which will be equipped with mobile robots; and the computational, electronic, and mechanical equipment. The laboratory supports interdisciplinary research involving engineering and cognitive science in behavior and learning on autonomous agents. Studies to be carried in areas of directed and emergent programming, reinforcement learning, neural network learning, and evolutionary and genetic programming approaches. A set of related research projects in multi-agent and multi-robot will be initiated for dealing with a variety of agents, environments, and tasks; for selecting control strategies; and for simplifying the task of designing complex multi-agent systems. The laboratory will also be used for student projects in advanced computer science courses. ***

The representations used by humans for motor control can be readily studied by imitation learning. Subjects imitate the movements of an instructor under different conditions. During these trials eye and hand movements are recorded. Preliminary results show that the representations of copied and copied from memory movements are different implying different internal systems.

Multihop wireless capabilities are enabling communication and coordination among autonomous nodes in unplanned environments and configurations. At the same time wireless channels present challenges of dynamic operating conditions, power constraints for autonomously-powered nodes, and complicated interactions between high level behavior and lower level channel characteristics (e.g. increased synchronized communication significantly degrades channel characteristics).
The major goal of the research proposed here is the development, testing, and characterization of algorithms for scalable, application-driven, wireless network services using a heterogeneous collection of communicating mobile nodes. Some of these nodes will be autonomous (robots) in that their movements will not be human-controlled. The others will be portable, thus making them dependent on humans for transportation. While the focus of the work is on the mobile nodes, the project includs immobile computers on the network as well. The project emphasizes that most (though not all) of the mobile nodes will have modest sensing, computational, and communication resources.
The chief scientific motivation behind the work is the design of robust, efficient, and scalable algorithms. The project hypothesizes that distributed algorithms that rely on local interactions have many compelling characteristics, resulting in these properties. There is significant overlap between the problems of coordinating the autonomous mobile nodes that carry some of the sensors and the algorithms that direct the flow of information from sources(s)to sink(s) in the network. Both sets of algorithms need to be carefully designed to improve robustness, efficiency, and scalability.
As motivation the project proposes that the experimental part of the research be conducted on a testbed which simulates some characteristics of an urban post-earthquake scenario in a building. The sensors in the experiments will be distributed geographically (within the building) and linked by a wireless network. Many of the mobile nodes will be largely autonomous, serving as easily-accessible knowledge collectors and repositories, and exercising a wide range of independent options in the dispatch and control of information flow and resources. Other mobile nodes will be carried about the environment by people. The project will study issues of scale (how many sensor nodes does the application software accommodate), fault tolerance (how robust is the system to loss of sensors and/or communication) and efficiency (e.g. time vs. quality of service).
As part of a one-year pilot study funded by NSF, the project has been conducting initial research in the issues underlying a system such as the one above. The project also recently received a substantial equipment grant from the Office of Naval Research to support the experimental portion of this work. The project has identified two key unsolved sub-problems that are relevant to the overall goals: localization and communication coverage. In this proposal the project discusses the broad research challenges in the area of communication and coordination of autonomous mobile nodes. The project then focuses on the two key problems as concrete questions that will be addressed in the research and describes a method involving simulation and experimentation to study them systematically.

EIA-0121141
Requicha, Aristides
University of Southern California

ITR/SI+AP: Active Sensor Networks with Applications in Marine Microorganism Monitoring





The proposed research combines networking, distributed robotics, nanorobotics, and microbiology in an effort to develop and apply technology for the in-situ, real-time monitoring of microbial populations in aquatic environments, such as the ocean or water supply systems. The application context provides feedback from experiments with realistic systems, and this feedback is essential to the progress of the Information Technology (IT) research proposed here. This project addresses two key challenges for IT during this decade: moving from virtual to physical applications, and moving from macro to micro and nano.

The IT focus is on the study of Physically-Coupled Scalable Information Infrastructures (PCSIIs), which effectively "embed the internet". The sensors and actuators in the proposed PCSII must have small physical dimensions, comparable to those of the microorganisms to be monitored. They must be deployed in very large numbers to achieve the unprecedented spatial and temporal resolution necessary to investigate the causal relationships between environmental conditions and microorganisms. Control and coordination of a multitude of such devices of limited and heterogeneous capabilities raise major challenges for networking, distributed coordination and distributed algorithms. Sensing for detection and identification of microorganisms is another challenge, which will be tackled by using nanorobotic Scanning Probe Microscope technology.

The goal of the project is to develop a formal foundation for the synthesis and analysis of implicit multi-robot coordination mechanisms. Such a formal understanding will allow the multi-robot community to move away from ad-hoc solutions and toward the principled design and analysis of coordinated multi-robot systems. This will be achieved by introducing a formal language to describe the entities interacting in a coordinated multi-robot system, and apply this framework to the principled synthesis of robot controllers using logic-based induction. At the same time, this project will develop a methodology for modeling the coupled robot-environment system and derive the equations describing dynamics of the system. Finally, these procedures will be combined, so that results of analysis can be used to drive performance-enhancing modifications in the robot controller. To validate the formal concepts of the proposed research, these methods will be applied to the design and analysis of multi-robot coordination methods for a real-world sensor/actuator network deployment and maintenance task. The proposed research is novel in that it combines formal techniques from Computer Science, Mathematics, and Physics. As such, the work will serve as a vehicle for raising the profile of mathematical analysis in the robotics community. Undergraduate and graduate robotics courses will benefit from the inclusion of the developed formal analysis techniques. In addition, twice a year demonstrations will be given at local high schools to teach the students the concepts of collective behavior and give them the skills to better understand and approach complex problems.

This is funding to support attendance by approximately 40 participants from the United States in the 2005 IEEE International Conference on Robotics and Automation (ICRA'05), which will be held in Barcelona, Spain, on April 18-22, 2005. This annual IEEE event, sponsored by the IEEE Robotics and Automation Society, has become the largest annual conference in robotics and automation worldwide, and serves as the premier forum for gathering international researchers together for the exchange of ideas on technical problems and their solutions, and on emerging technologies. NSF funds will help ensure a high U.S. presence at ICRA'05, by providing partial airfare reimbursement to selected U.S. researchers who have had papers accepted but who due to financial hardship would otherwise be unable to attend the conference to present their work.

Broader Impacts: The PI has established a 4-member Selection Committee to choose the beneficiaries from the NSF funds. The committee will pay special attention to enabling participation by student (co)authors and by members of traditionally under-represented groups and institutions. This funding will expose participants to the latest research results while also enabling them to build and/or enhance their social network of peers and mentors within the research community, which will in the future benefit them and the country as a whole.

A great deal of important human activity requires navigating and otherwise using physical spaces. Human spatial behavior, individual and collective, depends on the structure of the environment, the structure and content of cognitive representations of the environment (mental maps), individual and group goals, and interactions among individuals, groups, and crowds. As a result, human spatial behavior needs to be studied by considering all these aspects together; to do this requires a multidisciplinary effort. The proposed research brings together a team of researchers representing diverse disciplines of computation, psychology, and mathematics into an integrated program that will address human individual and collective use of physical space.
This project's multidisciplinary effort uses the tools of cognitive science, computational modeling, and mathematical analysis of collective behavior to study the dynamics of human spatial behavior. The project's goals are as follows:
1) To understand how individuals develop cognitive maps of complex environments in real-world situations that include rich spatial interactions with other people, individually and in groups;
2) To examine how cognitive maps influence the behavior of groups in high-density crowd conditions, and to develop the cognitive foundations for models of pedestrian dynamics and emergency evacuations;
3) To forge a mathematical link between microscopic (small scale) and macroscopic (large scale) models of adaptive human social behavior in spatial tasks.
The research program will develop novel cognitive map-driven models that will include the shared spatial information that individual people derive from social interactions. The models will be used to improve simulations of individuals and crowds, and provide a basis for mathematical analysis of collective spatial behavior dynamics. Validation and evaluation will exploit virtual reality technology, computer simulations of crowd behavior, and people's behavior in real environments. Through partnerships with two museums, the team will be working with real-world situations whose relevance to societal needs includes the design of emergency evacuation systems, automated detection of anomalies in large spaces and crowds, and the development of complex but human-friendly environments. The generation, validation, and free dissemination of powerful predictive models that will be developed will allow architects, planners, and developers of public spaces to design and/or modify public venues so as to optimize their navigability and safety. Finally, a comprehensive program of education, outreach, and dissemination will serve a broad audience of graduate and undergraduate students, inner-city K-12 students and teachers, and the general public will accompany the research.

This is funding to support a PI Workshop on the campus of the University of Southern California in Los Angeles, on September 27-28, 2006. HRI is one of the two cross-cutting technical areas defined in IIS Division's new solicitation entitled "Information and Intelligent Systems: Advancing Human-Centered Computing, Information Integration and Informatics, and Robust Intelligence" (NSF 06-572). The 1.5-day workshop will bring together current NSF PIs with ongoing HRI research programs, along with selected additional members of the research community with related interests, to help NSF identify emerging trends in this rapidly evolving field. Participants will discuss and prioritize the important subfields of HRI that the scientific community believes will have a major impact in the near-to-medium term. This workshop is one of several similar events, each focusing on a particular aspect of the new solicitation, being sponsored by IIS Division with the goal of encouraging the research community to provide input to NSF in its strategic planning process as we prepare for the challenges and opportunities anticipated during the coming period of explosive technological growth and change.

Broader Impacts: This workshop will present a unique opportunity for NSF PIs and other members of the rapidly growing human-robot interaction (HRI) research community to discuss the state of the art and to engage in strategic planning toward shaping the direction of this new and interdisciplinary research area with major implications on the future of robotics in society. The workshop organizers will produce a comprehensive workshop report, and the workshop website will become a permanent repository of the workshop discussions, breakout group reports, etc for general access by the research community at large.

This project, acquiring a mobile humanoid robotics platform as the centerpiece of a Human-Centered Robotics Lab, aims at assisting a broad population in need, based on the belief that the most suitable form of multi-purpose assistive machine for humans will be human-like. This new kind of robot, not highly accurate, stationary, single task machine with sensing abilities as for typical industrial applications, is richly equipped with multi-model sensing, a high level of dexterity, compliance for safe operation, and mobility. Endowed with the appearance and behavior of a social system appropriate for human environments, it can perform a large number of assistive tasks, autonomously or in collaborative instruction with humans. A humanoid robot instigates a variety of original research. Developing humanoid behavior advances robotics and automation technology while promoting interdisciplinary interaction with natural sciences

Proposal #: CNS 07-09296
PI(s): Mataric, Maja J.
Narayanan, Shrikanth S.
Institution: University of Southern California
Los Angeles, CA 90089-1147
Title: IAD:Computing Research Infrastructure for Human-Robot Interaction and Socially Assistive Robotics

This project, acquiring infrastructure for socially assistive robotics (SAR), enables interdisciplinary integrative research covering a broad spectrum of human robot interaction (HRI) topics. SAR studies a unique series of problems related to utilizing robot embodiment to provide social assistance to users in a variety of convalescence, rehabilitation, education, and training settings. The infrastructure consists of richly interactive humanoid robot platforms and state-of-the-art data collection equipment. The work enables the growth of SAR, providing grounding for a major area of HRI research by requiring realistic validation with human subjects/users for studies that include embodiment, affect/attitude modeling and recognition, mixed initiative interactions, user modeling, modeling personality and empathy, and engagement and learning through imitation. The facility is expected to produce a large corpus of data that will be made available to the community.

Broader Impact: Socially accepted robotics research aims to improve quality of life. Enabling the acquisition of pilot data necessary for NIH funding, this research brings new expertise through an interdisciplinary team that includes CS, EE, kinesiology, pediatrics, and development of disorder experts. Furthermore, the infrastructure impacts human resource development through educational and K-12 outreach programs that reach hundreds of students.

Robotics has the potential of positively impacting quality of life, especially for people with special needs. If we are to meet the demand for personalized one-on-one care for the growing populations of elderly individuals and those with special cognitive and social needs throughout life, great strides must be made in human-robot interaction (HRI) in order to bring robotics into everyday application domains. This interdisciplinary project identifies a specific set of HRI research questions in socially assistive robotics, the study of robotic systems capable of providing help through social rather than physical interaction. The research foci of the study are: embodiment, personality, empathy, and adaptivity toward the development of an assistive HRI model for customized time-extended assistive interaction. The research will be grounded in the stroke rehabilitation domain, where personalized and dedicated care is needed to provide supervision, motivation, and training during the critical post-stroke period and beyond, and where assistive HRI can play a key role. Specifically, a novel assistive HRI model will be developed based on personality matching between the user and the robot, in order to optimize the user's task performance on rehabilitation exercises. The model will be evaluated on multiple testbeds with a large pool of human subjects from the stroke patient population. An online learning algorithm will enable the robot to adapt to the user both over the course of short-term interactions during a single therapy sessions (e.g., in response to mood and fatigue), and time-extended interactions over multiple therapy sessions (e.g., in response to the evolving recovery process over months of rehabilitation). The work is the first to study the role of personality and empathy in assistive HRI with human subjects, as well as to engage in longitudinal assistive HRI research to assess time-extended human-machine interaction in the assistive context. An important contribution of the research is the unified and tightly integrated end-to-end approach, which combines key HRI issues of embodiment, personality, empathy and adaptivity in hypothesis-testing experiments. Project outcomes will also include a large and unique corpus of multi-modal data, which will be collected and analyzed, and made available to researchers across the relevant disciplines. The scientific impact will go well beyond novel insights toward a better understanding of the fundamentals of assistive HRI, and the role and potential for assistive human-machine interaction for stroke patient populations and rehabilitation in general.

Broader Impacts: Currently there are about 750,000 new strokes per year in the United States, and some expect the number to double in the next twenty years with the growing elderly population. Project outcomes will provide pilot data necessary for translating the methodologies developed toward clinical applications.

Robotics is currently at the forefront of technologies with recognized potential for impacting quality of human life. In response to the large need for personalized one-on-one care for the growing populations of elderly individuals and those with special cognitive and social needs throughout life, great strides must be made in the domain of human-robot interaction (HRI) in order to bring robotics into such application domains in human everyday life. This interdisciplinary project identifies a specific set of HRI research questions in socially assistive robotics, the study of robotic systems capable of providing help through social rather than physical interaction. The research focus is on two key issues: (1) the role of the robot's physical embodiment in the interaction; and (2) the use of expressive embodied communication and user modeling toward personalized time-extended assistive interaction. A specific consideration is given to interactions under the challenges of socio-communicative heterogeneity and deficits. A novel assistive robot control architecture is developed, based on multi-modal perception, embodied expression and communication, and on-line user modeling, implemented in three different types of real-world socially assistive systems. To give a realistic context to the research, the experimental testing and evaluation are performed with children drawn from a typical population and a population with Autism Spectrum Disorders (ASD), a family of disorders that have already been identified as amenable to technological, and in particular robotic, intervention and therapy. A key contribution of the research lies in the unified and tightly integrated end-to-end approach that jointly studies embodiment and multimodal expressive communication, grounded in data from hypothesis-driven experiments, and the development and use of novel signal processing and user modeling methods for human-machine interaction design.

This project, by its very nature, aims to impact the large and growing population affected by Autism Spectrum Disorders. With the support of the large and unique corpus of data that will be collected and analyzed, the expected scientific impact will go well beyond novel insights toward a better understanding of the fundamentals of HRI and its relevance for diverse user populations and for socialization of children with ASD. In addition to the basic research, two complementary educational outreach programs broaden the impact of the work: (1) a novel K-12 outreach and teacher training program specifically aimed at special education through the use of robotics for teaching STEM topics; and (2) undergraduate research training and pipelined role-modeling from pre-university to undergraduate to graduate students. The education programs dovetail with the research plan, resulting in integrated activities involving all participants in the research team.

This award provides funding for a three year standard award to support a Research Experiences for Teachers (RET) in Engineering Site program at the University of Southern California (USC), entitled, "Societally Relevant Engineering Technologies-Research Experiences for Teachers (SRET-RET)", under the direction of Dr. Maja J. Mataric.

The vision of this RET in Engineering Program is to leverage the considerable resources of the USC to create long-term partnerships among world-renowned engineering researchers and K-12 teachers in Los Angeles inner-city schools. The six week SRET-RET summer program will bring knowledge of science, technology and engineering directly to middle and high school educators (10 teachers/year for 3 years) by involving them in mentored, discovery-based authentic learning and research experiences in state of the art engineering research facilities including the NSF Engineering Research Center for Biomimetic MicroElectronic Systems (BMES). In addition to immersion in the research environment SRET-RET teachers will participate in engineering, technology, ethics, and pedagogy professional development workshops which will facilitate the synthesis and translation of their newly gained knowledge and skills into meaningful and rigorous K-12 classroom activities that sprark enthusiasm for science, technology, engineering and math, using Stigler's lesson study approach to processional development. The academic year follow-up component of the SRET-RET program is structured to sustain and elaborate on the accomplishments the teachers make during the summer and facilitate communication between the teachers and their K-12 colleagues as well as their university partners. The SRET-RET teachers will be role models and conduits of science, technology, and engineering, bridging the traditional gaps between university centers of research and 6-12th grade classrooms.

The world's population is growing older; it is estimated that in 2050 there will be three times more people over the age 85 than there are today. Many are expected to need physical and cognitive assistance, and all will need additional healthcare. Shortages in primary care physicians, nurses, and managed care facility space and staff are already an issue today, creating a niche for assistive technologies to fill the care gap. A growing body of research shows that certain behavior patterns have a positive impact on longevity and wellness, including regular physical exercise, social interaction, and cognitive engagement. This project aims to develop and evaluate socially assistive human-machine interaction techniques that influence the user to engage in and comply with wellness-promoting behaviors in the home or nursing home in order to enhance longevity and quality of life.
This work is focused on developing socially assistive systems (SAS) using peer-level human-machine interaction in which the machine serves in the role of a knowledgeable embodied agent capable of providing time-extended, sustained, and engaging interaction. The research focuses on two types of wellness-promoting human-machine interactions: 1) exercise sessions (cognitive and/or physical) and 2) socializing sessions. For one-on-one exercise sessions, the project is developing SAS capabilities that provide exercise monitoring, coaching, and motivation. For socialization, the research is developing SAS capabilities that provide social interaction and friendly reminders and encouragement to comply with health regimens (taking medicine, being physically active) and healthy habits (calling family, meeting friends). The two types of interactions share the common goal of influencing human behavior, and the main contribution of the research is the set of methods and algorithms for influencing behavior though human-machine interaction. This is achieved through a novel two-fold approach: 1) adaptive interaction steering for short-term interactions, and 2) motivation and coaching of behavior in longer-term interactions to maintain engagement and enhance task performance. The embodiment of the SAS is leveraged to maximize engagement and compliance; a key focus of the work is on developing a comprehensive method for natural, persuasive and engaging embodied communication. The methods and algorithms being developed are general, and will be implemented and tested on both computer-based and robot-based agents. In this way the work validates the developed methods on multiple technology platforms and embodiments, and compares their relative effectiveness and acceptability by the intended user population. The specifics of the implementation are informed by an early focus group with elderly participants, the target user population. The developed techniques are being implemented in both human-computer interaction (HCI) and human-robot interaction (HRI) versions, and are being evaluated with a large group of elderly users interacting with the SAS implementations over a multi-week user study. The work is focused on generating methods, algorithms, and a large corpus of multi-modal data (video, audio, and questionnaires) for grounding continued research into health and wellness-relevant HRI and HCI.
This project aims to address a component of the nationally recognized healthcare challenge of promoting wellness and longevity in the aging population. Beyond basic algorithm and method development, the project implements and tests real-world socially assistive systems, both computer-based and robot-based, with a large population of elderly retirement home residents. The project is expected to produce insights useful for both research and healthcare product development for addressing this growing segment of the population. In addition to the socially relevant research focus, the project team is also engaged in a comprehensive program of K-12 outreach activities, which use robotics to promote STEM topic learning using the health theme of the proposal. The project involves inner city K-12 teachers and students in annual open houses, assemblies, and workshops that provide hands-on experiences with assistive systems for the elderly, as well as take-home materials for continued learning. The project team includes PhD students, undergraduates, and K-12 volunteers, and establishes a mentoring pipeline so that university students are both mentored and serve as mentors and role models for their younger peers.

PI Name: Krishna Nayak
Institution Name: University of Southern California
Proposal Title: BE-LA: Body Engineering Los Angeles
Proposal ID: 1045595

This project will establish a new GK-12 program at USC that will develop graduate fellows majoring in engineering and related disciplines into well-rounded STEM leaders of tomorrow, while introducing cutting-edge body engineering research into urban Los Angeles middle school science classrooms. Graduate fellows will be provided with training and practice in education, communication, leadership, collaboration, and cultural sensitivity that enhances their doctoral training. Each graduate fellow will be paired with a middle school science teacher, and will serve as an in-class science resource throughout the school year. Fellows will develop and deliver original lesson plans incorporating their doctoral research and the research of their faculty advisors. Topics will include: non-invasive sensing and imaging, speech articulation, hand articulation, neuromuscular control, vision and recognition, cardiovascular mechanics, nutrition and metabolism, biological and bio-compatible materials, and human-machine interaction. The intellectual merit of this project includes 1) the research theme of body engineering, which is a strength of USC, and provides an engaging vehicle for demonstrating scientific and engineering principles and introducing university research into K-12 classrooms; and 2) the development and use of powerful pedagogical structures that will help graduate fellows communicate their research to middle school students.

The broader significance of this project includes 1) development of a cadre of graduate fellows that possess the communication, leadership, and collaboration skills, and cultural sensitivity required to become STEM leaders; and 2) development of skills and interest in students at a critical stage for STEM learning.

Dr. Maja Mataric received her Ph.D. in Computer Science and Artificial Intelligence from MIT in 1994. She is Professor of Computer Science and Neuroscience, and Pediatrics Director of the Center for Robotics and Embedded Systems, Co-Director of the Robotics Research Lab, and Senior Associate Dean for Research at the Viterbi School of Engineering at the University of Southern California. Dr. Mataric has established a mentoring philosophy that encompasses the need to encourage students continuously as they progress in their educations. Her stated philosophy is that mentoring must be viewed as a pipeline process, in which role models and training opportunities are provided from as early as possible and the pipeline is continually fueled. The pipeline mentoring program is based on the established literature about critical times for capturing interest and recruiting women and underrepresented students into STEM areas. To build the pipeline, the comprehensive spectrum of mentoring activities performed to date span: K-12 STEM outreach and teacher training, undergraduate student mentoring toward placement in graduate programs, graduate and postdoctoral student mentoring and placement in academic positions, peer mentoring of female faculty, mentoring of junior faculty in engineering, and developing a culture of mentoring at USC. Dr. Mataric's mentoring programs have resulted in new courses and programs at the K-12 level that have trained generations of teachers and students and continue to recruit generations of inner-city at-risk students into STEM topics. Approaches have yielded the recruitment of underrepresented groups at each level, from all-girls elementary school teams winning robotics contests at the state level, to outstanding placement of Ph.D. students and postdoctoral fellows in academic positions, to outstanding outcomes in female faculty mentoring leading toward nationally competitive research grants, to developing novel mentoring programs with impact across the entire university. The programs have resulted in the placement of Ph.D. students in minority serving universities and of Ph.D. students from underrepresented groups (women and African Americans) in top research universities in the US and world-wide. The programs have also established a role-modeling and networking pipeline between the K-12 inner city institutions, USC undergraduates, Ph.D. students, and faculty. Dr. Mataric's mentoring programs have effectively aided in the recruitment and retention of women faculty in engineering at USC and have had a significant impact on institutional-wide cultural change.

This collaborative project is conducting a research study to delineate the effective components of mentoring for underrepresented and non-underrepresented students in STEM, utilizing a robotics educational program. To understand STEM expectations of success and interests in pursuing STEM careers, it is imperative to understand the achievement-related choices people make when deciding what areas to study and what careers to pursue. If mentoring is to be used to its fullest capacity in increasing students' interest in pursuing STEM careers, it is imperative to delineate what type of mentoring is most effective in increasing STEM self-efficacy and achievement-related choices. This proposal is addressing the following research questions: "Can a general 'best practices' mentoring approach be effective or is a specific self-efficacy approach needed? Is a combination of the two approaches optimal? In addition, does student ethnicity moderate the impact of the mentoring approaches?" Forty-eight teams of approximately 480 male and female participants represent middle school classes that have not previously participated in robotics or a similar STEM activity. Team mentors are divided into those receiving best-practices mentor training, self-efficacy mentor training, a combination, and no mentor training (control group). All teams participate in a Botball regional robotics competition organized by the KISS Institute for Practical Robotics. Employing a mixed factorial design, the study examines three types of mentor training for their impact on STEM self-efficacy and expectations of success and/or STEM achievement-related choices. The results along with the feedback from mentors will be used to develop a mentor-training package that could be used in all robotics programs and be generalized to other similar STEM activities.

Socially Assistive Robots
Lead PI/Institution: Brian Scassellati, Yale University
This Expedition will develop the fundamental computational techniques that will enable the design, implementation, and evaluation of robots that encourage social, emotional, and cognitive growth in children, including those with social or cognitive deficits. The need for this technology is driven by critical societal problems that require sustained, personalized support that supplements the efforts of educators, parents, and clinicians. For example, clinicians and families struggle to provide individualized educational services to children with social and cognitive deficits, whose numbers have quadrupled in the US in the last decade alone. In many schools, educators struggle to provide language instruction for children raised in homes where a language other than English is spoken (over 20%), the fastest-growing segment of the school-age population. This Expedition aims to support the individual needs of these children with socially assistive robots that help to guide the children toward long-term behavioral goals, that are customized to the particular needs of each child, and that develop and change as the child does.
To achieve this vision, this Expedition will advance the state-of-the-art in socially assistive human-robot interaction from short-term interactions in structured environments to long-term interactions that are adaptive, engaging, and effective. This progress will require transformative computing research in three broad and naturally interrelated research areas. First, the Expedition will develop computational models of the dynamics of social interaction, so that robots can automatically detect, analyze, and influence agency, intention, and other social interaction primitives in dynamic environments. Second, the Expedition will develop machine learning algorithms that adapt and personalize interactions to individual physical, social, and cognitive differences, enabling robots to teach and shape behavior in ways that are tailored to the needs, preferences, and capabilities of each individual. Third, the Expedition will develop systems that guide children toward specific learning goals over periods of weeks and months, allowing for truly long-term guidance and support. Research in these three areas will be integrated into socially assistive robots that are deployed in schools and homes for durations of up to one year.
This Expedition has the potential to substantially impact the effectiveness of education and healthcare for children, and the technological tools developed will serve as the basis for enhancing the lives of children and other groups that require specialized support and intervention. The proposed computing research is tied to a comprehensive student training program, bringing a compelling, engaging, and grounded STEM experience to K-12 students through in-school and after-school activities. It also establishes an annual training summit to provide undergraduates with the multi-disciplinary background to engage in this promising research area in graduate school. Finally, by establishing a brand name for socially assistive robotics, this effort will create a central authority for the distribution of high-quality, peer-reviewed information, providing a coherent focal point for enhancing outreach and education.
For more information visit www.yale.edu/SAR

To enable natural and productive human-robot interaction (HRI), a co-robot must both understand and control "proxemics" -- the social use of space -- in order to communicate in ways commonly used and understood by humans. This project focuses on answering the question: How do social (speech and gesture), environmental (loud noises and low lighting), and personal (hearing and visual impairments) factors influence positioning and communication between humans and co-robots, and how should a co-robot adjust its social behaviors to maximize human perception of its social signals?

The project will develop principled computational models for the recognition and control of proxemic co-robot behavior in HRI using both telepresence and autonomous co-robots. The research will establish a foundational component of HRI for co-robotics, with specific impact on special needs users in socially assistive contexts -- particularly the elderly, both aging in place and in institutions -- with the goal of mitigating isolation and depression, and encouraging exercise and socialization.

Broader impacts: The work will inform robot design and control, and provide software and a corpus of public HRI data for use by researchers worldwide. Beyond robotics, the project promises to inform, validate, and extend longstanding research in the social sciences. This project also includes a strong public and K-12 outreach component consisting of weaving the HRI themes being developed into annual regional and international outreach events. The events feature large-scale open houses and educational workshops with interactive demonstrations and hands-on activities that highlight human factors in computational systems as an effective means of increasing interest in STEM-related activities.

It is widely acknowledged that improving health and quality of life in the United States will require contributions and advances in many technical and non-technical areas, including computer science, engineering, economics, as well as in the social and behavioral sciences. The NSF Smart Health and Wellbeing Program focused on fundamental research in these areas and has supported a diverse set of multidisciplinary projects and investigators that received their awards in 2011 and 2012. The workshop for the principal investigators in the Smart Health and Wellbeing Program was organized to bring together these researchers with diverse projects and varied backgrounds and areas of expertise to exchange ideas, network, learn from each other, form new collaborations, and help to shape the future of this dynamic and rapidly growing set of fields. In addition to the presentation of posters associated with the funded projects, the participants have the opportunity to attend several invited presentations by leaders in several relevant fields focused on healthcare challenges and potential solutions. To capture their creativity and innovative ideas, the workshop attendees were invited to participate in several breakout sessions. The summary of the workshop outcomes will be accessible at http: http://nsfsmarthealthwellness2013.usc.edu/

This award renews an exemplary Research Experience for Teachers (RET) Site at the University of Southern California (USC). The USC Viterbi School of Engineering has partnered with the Los Angeles Unified School District (LAUSD) to develop an integrated engineering and computer science RET Site targeting middle school science and math educators. The resulting program is a collaborative research-based professional development effort that combines the computer science, engineering, technological, and pedagogical expertise of USC faculty with inner-city teachers in 6th- thru 8th-grade science and math classrooms in the LAUSD. The primary goals of the program are to: (1) increase teachers' knowledge of computationally-focused science and engineering technologies; (2) increase middle school teachers' disciplinary pedagogic competence in computer science, engineering, and applied math through a comprehensive program that includes targeted lab-based research experiences focused on computer science and engineering aligned with Next Generation Science Standards, Common Core Math Standards, and advanced lesson study; and (3) build and maintain long-term collaborative partnerships between LAUSD middle school teachers and the research community that positively impact student achievement and career paths.

The intellectual merit of this project lies in the strong research foundation at the core of the RET Site combined with a leadership team that excels at both research and educational outreach. This RET Site is focused on innovative, societally relevant computer science and engineering research and brings this research to high-need middle school science and math teachers using lesson-study focused professional development approaches. The goal is to facilitate team teaching between math and science teachers to integrate their subject areas with engineering and computer science problem solving aligned with the Next Generation Science and the Common Core Math standards. This project effectively translates research into educational practice and provides exemplary models for weaving computing and engineering concepts into K-12 education.

The RET Site program has significant broader impacts. It will result in innovative curricula that not only address new curriculum standards, but also address an area of significant need in middle school content. It will provide video-based middle school lesson exemplars and units of study for teachers nationwide to use in their classrooms. The LAUSD, the second largest public school district in the United States, has a significant population of students from under-represented groups. Thus this project has the potential to have a positive influence on many students who are traditionally under-represented as computer scientists and engineers.

This project is to design, develop, and freely distribute novel, affordable, modular hardware and accompanying software platforms for enabling non-contact human-robot interaction (HRI) research. Such research is a significant portion of HRI today, and encompasses a broad spectrum of computing challenges and compelling application domains, including education, training, rehabilitation, and health. The goal of this project is to significantly increase access to hardware to a large body of researchers, so that computing advances can be applied to physical systems and evaluated in real-world environments, in order to drive progress in the computing community.

Advances in sensor and communication technologies have facilitated progress in computing research on physical platforms. The field of human-robot interaction in particular has grown significantly and actively brings together an interdisciplinary community of researchers across computing, robotics, and social science. However, progress has been limited by the lack of affordable, general-purpose, modular hardware platforms with available low-level software that would enable large numbers of computing researchers to enter the field and develop and test algorithms, as well as conduct statistically significant user studies by deploying systems in the real world and collecting user data to inform further computational research in HRI.

Participating in the school environment is essential to children's social, emotional, and cognitive development and learning. It has long been recognized that the quality of a student's school experience is important not only for the academic and achievement outcomes, but for fostering self-esteem, self-confidence, and general psychological well-being. Yet annually 26.6% of America's children have health or behavioral challenges that cause them to miss significant amounts of school, and 13% of all US K-12 public school students receive interventions due to learning disabilities or emotional disturbances. This project focuses on the problem of using mobile remote presence co-robots as a means to provide numerous K-12 aged children who cannot be present in school access to the curricular and social learning experiences critical to their development and future outcomes. Using mobile remote presence for access to K-12 classrooms for homebound students may be a powerful gateway for minimizing the effects of physical separation from the school environment. This project develops methods that enable the creation of personalizable robots that allow shared autonomy, socially appropriate movement and socially expressive nonverbal communication in dynamic in-class K-12 environments, allowing children to be truly embodied in the classroom, even from a distance. The impact of this NRI project spans K-12 education at large, but also applies to general uses of mobile remote presence systems outside of the classroom setting, for both education and training. In addition, the project connects the research themes with outreach; it engages K-12 students and teachers in co-robot-themed activities and holds annual NRI-themed workshops at large-scale public venues. The broader outreach program is designed to train students in STEM, so they can become not only end users of robotics and other technologies but capable of developing such technologies themselves, thereby contributing to the US STEM workforce.

This proposal focuses on developing control algorithms for mobile remote presence (MRP) co-robot systems that will improve human access to a learning/training environment, focusing on homebound K-12 students, but with general implications to users of all ages and a variety of contexts. Work with MRP systems has identified key missing technical capabilities necessary for facilitating natural remote interaction and learning: 1) simple, socially-appropriate autonomous behavior and context awareness that reduces user cognitive load; 2) expressiveness for conveying the user's affect and communicative intent; and 3) the ability to personalize the way the user interacts through the MRP. This project addresses these challenges with participatory user-informed algorithm development, system integration, and evaluation. Specifically, it first develops an approach to automating and facilitating spatial and social context awareness for the operator and the MRP, and uses it to enable the two research thrusts, social appropriateness and expressiveness, with algorithmic methods for personalizing both. To ground the results in the selected real-world context, iterative design and evaluation is performed in the K-12 in-class setting, involving users across the age and education span, providing a test of the co-robot's relevance, effectiveness, and robustness. The project brings together a pair of interdisciplinary experts with a track record of successful past collaborations and three partners: industry, deployment, and outreach, committed to a project timeline with specific evaluable milestones.

1548502(Mataric)

The number of adults over the age of 65 is predicted to reach 83.7 million by 2050. There is accordingly a growing need for technologies for the elderly to complement human care in addressing the fast-growing needs of the elderly population. This project takes a novel approach to developing and evaluating an assistive technology for the elderly: it views the family unit as a team, and focuses on developing a robots as a team member (rather than individual assistant) designed to aid in the achievement of team/family goals. In the project, these goals are focused on the wellbeing of the elderly family member, and include daily social connectedness with others in the family, regular physical and cognitive activity, and medication adherence. These goals are part of the family dynamic and involve the interaction of various team members, pairwise, in subgroups, or all together. The project will develop a hardware and software infrastructure for deploying a socially assistive robot in the home and methods for enabling the robot to adapt to the family members in order to aid in facilitating team dynamics and aiding family goal achievement. The project brings together leading experts in socially assistive robotics, gerontology, and social work, who will spend two years in a tightly knit process of technology development combined with in home system evaluation with participating families.

This project is focused on engineering team interactions and dynamics, with the robot as a member of the team, embedded in a real-world environment and interacting with other team members in real time. The engineering goal is to develop data-driven robot control algorithms and the associated hardware and software infrastructure for enabling robots to serve as team members in the context of family-supported eldercare. The control algorithms, combined with the hardware and software infrastructure, will enable the robot system to perceive and understand the relevant aspects of the family interaction dynamics, be a participant/component in those team dynamics, and influence/streer those team dynamics toward desired family team goals. The project will enable and then iteratively probe the effects of the robot as team member in different interaction contexts (user-family, user-caregiver, family-caregiver). Furthermore, the project tackles three fundamental components in team goal achievement: evaluation of team performance, coordination of actions across multiple team members, and team member role assignment. It also investigates the application of unsupervised, supervised, and reinforcement learning techniques to the domain of elderly care. The research is complemented with a K-12 STEM outreach program consisting of annual free interactive workshops for students in secondary education (grades 6-12; up to 30 students per workshop). Simple robot programming and demonstrations of the hardware and software being developed in the project will be used to discuss how assistive robots could play a role in society, starting with the students' families.

This is funding to support a Pioneers Workshop (doctoral consortium) of approximately 31 graduate students (16 of whom are from the United States and therefore eligible for funding) from diverse research communities (e.g., computer science and engineering, psychology, cognitive science, robotics, human factors, human-computer interaction design, and communications), along with distinguished research faculty. The event will take place on March 7, 2016, immediately preceding the 11th International Conference on Human Robot Interaction (HRI 2016), to be held March 8-10 in Christchurch, New Zealand, and which is jointly sponsored by ACM and IEEE. HRI is a single-track, highly selective annual international conference that seeks to showcase the very best inter- and multi-disciplinary research in human-robot interaction with roots in diverse fields including social psychology, cognitive science, HCI, human factors, artificial intelligence, robotics, organizational behavior, anthropology and many more, and to this end the conference invites broad participation. The theme of HRI 2016 is "Natural Interaction" which seeks contributions from a broad set of perspectives, including technical, design, methodological, behavioral, and theoretical, that advance fundamental and applied knowledge and methods in human-robot interaction, with the goal of enabling human-robot interaction through new technical advances, novel robot designs, new guidelines for design, and advanced methods for understanding and evaluating interaction. More information about the conference is available online at http://humanrobotinteraction.org/2016/. This workshop will afford a unique opportunity for the best of the next generation of researchers in human-robot interaction to be exposed to and discuss current and relevant topics as they are being studied in several different research communities (including but not limited to computer science and engineering, psychology, robotics, human factors and ergonomics, and HCI). This is important for the field, because it has been recognized that transformative advances in research in this fledgling area can only come through the melding of cross-disciplinary knowledge and multinational perspectives. Participants will be encouraged to create a social network both among themselves and with senior researchers at a critical stage in their professional development, to form collaborative relationships, and to generate new research questions to be addressed during the coming years. Participants will also gain leadership and service experience, as the workshop is largely student organized and student led. The PI has expressed her strong commitment to recruiting women and members from under-represented groups. To further ensure diversity the event organizers will consider an applicant's potential to offer a fresh perspective and point of view with respect to HRI, will recruit students who are just beginning their graduate degree programs in addition to students who are further along in their degrees, and will strive to limit the number of participants accepted from a particular institution to at most two.

The Pioneers Workshop is designed to complement the conference, by providing a forum for students and recent graduates in the field of HRI to share their current research with their peers and a panel of senior researchers in a setting that is less formal and more interactive than the main conference. During the workshop, participants will talk about the important upcoming research themes in the field, encouraging the formation of collaborative relationships across disciplines and geographic boundaries. To these ends, the workshop format will encompass a variety of activities including three keynotes, a distinguished panel session, and breakout sessions. To start the day, all workshop attendees will briefly introduce themselves and their interests. Following the opening keynote, approximately half of the participants will present 3-minute overviews of their work, leading into an interactive poster session. This will enable all participants to share their research and receive feedback from students and senior researchers in an informal setting. The workshop organizers will facilitate the post-presentation discussion and will encourage participants to ask questions of their peers during the interactive break and poster session. After lunch, the remaining workshop participants will give their 3-minute overviews, followed by presentation of their posters during a second interactive poster session. Senior researchers (in addition to those on the panel) will be invited to attend the student presentations and poster sessions in order to provide feedback to participants, and workshop participants will be invited to present their posters during the main poster session of the HRI conference as well. The conversations between the panel and participants will continue over lunch and during dinner.

Typically developing (TD) infants use movement to explore their environment, to interact, and to control their bodies. By moving, they learn which movements lead to desired outcomes: obtaining a smile from a caregiver, reaching a toy, etc. In contrast to TD infants, infants at risk (AR) for developmental delays often have difficulty moving and decreased motivation for movement. Consequently, less movement experience results in less exploration and may contribute to delays in development. The goal of this project is to develop a robot that can interact with an infant and encourage the infant to explore different types of movements. The robot will guide and engage the infant to produce movements in ranges that the infant is not experiencing on his/her own. The proposed research has the potential to advance knowledge about which aspects of movement infants can adjust and how to most effectively guide their movement to help them learn to control their bodies. End users (therapists and parents) are participating in the development of the infant-robot interaction system with the goal that it be easily adaptable to other conditions, such as autism. The project includes education and training components: 1) a K-12 STEM outreach component ties the research to educating youth about STEM and motor disabilities, and 2) graduate students in engineering, computer science, and biokinesiology receive training and mentorship to become effective interdisciplinary researchers.

This research project is developing an interactive infant-robot system by: 1) analyzing existing movement data from TD and AR infants to produce expected behavior distributions for movement characteristics; 2) using those results to inform the contingent feedback for the robot to determine which movement characteristics infants can act to adjust; and 3) determining whether personalized, robot-guided feedback (motivating the infant in the desired movement) is more effective than a standard robot reward (fixed robot movement pattern). Wearable sensor and 3D vision technology is being used to quantify infant movement characteristics: limb movement quantity, duration, peak acceleration, and amplitude. A non-cumbersome light-weight wearable eye-tracker is being used to measure visual attention. The hypotheses to be tested are that: 1) infants are able to perceive and act on information to adjust the amplitude, peak acceleration, and duration of their limb movements; and 2) personalized, robot-guided feedback is more effective than a fixed robot reward at eliciting target movement behaviors.

Robots designed for social interactions can enrich the quality of life for individuals and society in a myriad of ways, such as automating undesirable physical work, supporting activities of daily living, and facilitating social connections. However, seamless integration of robots into society depends on both people and robots understanding how to communicate naturally and effectively with each other. Humans need to understand the capabilities of a robot and develop trust in the robot. Robots need to understand the capabilities and interests of the human and adapt their behavior accordingly. This project will use virtual reality and augmented reality technologies to help people and robots to better understand each other before they meet in person. During a Shared Virtual Teaching Experience (SVTE), human users will be able to interact with a virtual version of a robot using virtual reality and augmented reality technologies. The SVTE will help both the robot and the users learn how to communicate with each other, build trust and rapport by sharing information about themselves, and adapt based on what each learns from the other. While an SVTE is a general approach for improving human-robot interactions, this project will focus on the needs of older adults, who may be hesitant to use and trust new technologies, including robots. Research has shown that older adults can benefit from social interactions with robots, especially when the robots help to create social connections with other older adults. This project helps to develop new approaches, leveraging virtual reality and augmented reality, to help users and robots work together. It will address societal needs of an aging population using socially assistive robots and advance the state of the art in human-robot interaction. It will also involve K-12 students in order to stimulate interest in science and engineering while engaging with the elderly community in the context of a real-world need for human-centered technology.

This project uses immersive communication modalities of virtual reality (VR) and augmented reality (AR) to overcome the barriers to social communication that hinder seamless integration of co-robots into human everyday lives. Specifically, the project is developing an immersive mixed reality experience, Shared Virtual Teaching Experience (SVTE), allows human users to get accustomed to robots, and vice versa, before interacting together in the real world. Both VR and AR are potentially useful for this purpose, since VR provides a consistent graphical environment that makes communication clear for users, while AR allows for situating the interaction with a simulated robot in a real, physical environment, while benefiting from graphical enhancements. This project develops SVTE pre-exposures in both VR and AR formats to enable immersive user training on how to communicate with the robot and to understand its functional and affective limitations. Throughout SVTE interactions, the system will collect information about users that will allow the robot to adapt for personalized interactions in the physical world. To evaluate the SVTE, during development and when completed, this project will perform a series of user studies, first with university students and then with older adults in a senior living facility. In the SVTE evaluation with elderly users, this work will focus on the use of robots for assisting in social engagement and facilitation for preventing social isolation, which has been shown to raise morbidity and mortality. Overall, this project will include the development of a mixed reality open-source testbed capable of communicating with physical robots via ROS and virtual communication strategies for robots. Using data from those virtual modalities, this work will generate multimodal user models that are typically difficult to perceive and create within the physical world. The models will, in turn, allow non-experts to understand how to effectively interact with physical robots. This research will provide a framework for evaluating multimodal user models for naturally communicating, adapting, and personalizing human-robot interactions in various real world contexts.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Human-machine interaction is an area of research where scientist study how users work together with robots and other devices. It is a broad, cross-cutting area of computing with great potential for supporting wellness, education, and training of people from various backgrounds and with diverse needs. The technology in this field is expanding rapidly, and leverages major areas of development, including computer vision and computer intelligence. However, this area of research is stifled by the lack of tools and software platforms that are accessible, affordable, and appropriate for use with real-world users in replicable real-world research studies. This planning project aims to spend a year understanding this field of research community needs toward designing, what is called “OpenHMI:, an open-source, affordable and modular platform for enabling scalable and accessible research and outreach in human-machine interaction (HMI)”. OpenHMI aims to broaden participation in research by enabling affordable and inclusive real-world studies and data collections. By creating an accessible low-cost and a community accessible platform, this infrastructure will broaden participation of researchers from a range of institutions and levels of research support, in particular opening doors to under-resourced researchers and groups. By involving researchers in the community in the design process, this work establishes an ecosystem that aims to remove barriers to entry for researchers from traditionally under-represented, under-resourced, and/or minority-serving groups and institutions, thereby expanding computing research ideas and projects. The low cost of OpenHMI hardware can also make it an affordable platform for demonstrating introductory computing, computer coding, robotics, and design topics to K-12 and enabling safe hands-on learning.<br/><br/>This one-year planning project uses surveys, interviews, and workshops to collect information about the computing community needs toward developing OpenHMI. Specifically, three nation-wide surveys assess detailed needs of the community, including hardware and software infrastructure needed and specific prioritized features of each. Using that input, mockups, early prototypes, and simulations of hardware and software are developed and used in two nation-wide virtual workshops designed to be broadly accessible and inclusive. The workshops serve to train the participants with hands-on experiential activities while collecting information about usability, priorities, and preferences. The large corpus of collected community data informs the design of OpenHMI so that it can be community-informed and designed to ensure its ability to significantly advance research in human machine interaction research by being open-source, accessible, modular and scalable and to facilitate inclusive, safe, privacy-centered and effective integration of this field of research into everyday lives of users to better support ethical data-driven research. The community design process also establishes an open and collaborative ecosystem to accelerate the transition from research studies in small-scale short-term laboratory settings to large-scale long-term deployments in real-world environments.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Support groups help people to learn from others who share similar experiences; they are known to be effective in reducing stress caused by negative life events. With broader access to the Internet, support groups have also expanded into video conferencing format. In-person and remote support groups are led by facilitators with wide ranging backgrounds and qualifications. Unfortunately, such facilitators often suffer from burnout, leading to support group closure. Hence, automated facilitators offer a way for maintaining support groups when human facilitators are unavailable. The main aims of this project are (i) to identify and evaluate the characteristics of an effective autonomous group facilitator; (ii) to study and develop computational methods for measuring individual engagement and group cohesion in video-mediated multiparty interaction; and (iii) to develop and evaluate an autonomous group facilitator that can maximize group cohesion through computational means. To achieve these aims, this project builds and studies an autonomous agent facilitator in the form of a socially assistive robot for remote support groups via Zoom or a similar platform. The interpersonal connectedness and alliances in a group make a support group more effective. Therefore, the project will enable the robot facilitator to choose the facilitation strategy that increases group members’ participation and connectedness. This research advances AI technologies for understanding human-robot interaction and contributes to the development of technologies that can broaden access to mental health support. The project activities will include annual outreach sessions for local inner-city K-12 students demonstrating the automated facilitator and discussing stress management, to educate about STEM and mental health. This project will also broaden participation in computing through the K-12 outreach activities and through training and mentoring five undergraduate researchers per year from systematically underserved groups.<br/><br/>This project advances the state-of-the-art in socially interactive agents and robots capable of interacting with multiple users, in video-mediated interaction. The research incorporates the study of expressive robot and agent embodiment, algorithm for autonomous conversation facilitation, and user engagement for novel facilitation strategies. To this end, the project will first use a human-driven agent, through a Wizard-of-Oz (WoZ) strategy, to design the agent’s action space (both verbal and nonverbal behaviors) necessary for moderating a support group. The WoZ study will also test the hypothesis that an embodied agent facilitator is as effective as a human facilitator in engaging users and projecting competence to group participants. After coding the data recorded during the WoZ study, multimodal machine learning models will be trained for automatic recognition of engagement and conversational stages and acts. Group cohesion will be assessed based on dyadic engagement and individual responses, through network analysis. The research team will finally build an autonomous facilitator leveraging a reinforcement learning model that optimizes for increasing group cohesion. The autonomous facilitator will be evaluated against a second agent that optimizes for equal access to the conversational floor, in terms of individual engagement and group cohesion assessed by post-session questionnaires. This work will build technologies for automated group facilitation that can assist to bridge the gaps in delivering support groups when human facilitators are absent or in short supply.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.