Enabling Lifelong Human-Robot Interaction at ICDL 2007

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Enabling Lifelong Human-Robot Interaction
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A Special Session of the
International Conference on Development and Learning

July 12, 2007
Imperial College London

http://robotics.cs.brown.edu/icdl07/

Session Scope

What are the applications of robotics critical to society?

It is unclear how the capabilities of current and future robots will meet needs of their human users over the course of time. As robots move beyond laboratories into real-world human environments, human-robot interaction will be increasingly longitudinal. The performance of personal robots, similar to personal computers, will be subject to the dynamic expectations of human users and evaluated over of the span of years. Such long-term interaction poses distinct challenges for the scalability of autonomous robotic systems.

Scalability highlights the need for enhanced robot learning and development. Specifically, how can robots scale to perform unknown tasks across different environments and hardware platforms according to the preferences of individual users? To meet this challenge, we must revisit basic issues in developmental robotics about innate mechanisms and adapting behavior. Can innate robot capabilities be crafted to sufficiently encompass the space of relevant tasks, environments, and platforms? Can these innate capabilities be formalized mathematically and interfaced with human decision making? Should learning and adaptation be the central means for scalability? Can appropriate learning methods be performed tractably over large datasets online? How will users produce training data without programming or a prohibitive burden? How could innate mechanisms be structured to permit abstraction and generalization by learning? Are there common concepts used in existing approaches to these issues? (What learning methods and representations are needed to allow for assimilation of knowledge over extended periods of time and from different perceptual mechanisms?)

Further, scalability for lifelong HRI raises questions about how to evaluate across the uncontrolled factors. Is evaluation solely in a laboratory setting still sufficient? What combination of quantitative, qualitative, usability, and longitudinal aspects are needed for evaluation? Given the overhead for experimental infrastructure, how can we realize platforms that enable truly normalized evaluation across different algorithmic approaches? For longitudinal studies, could such robots be feasibly deployed to lay users? Is robotics at a point where normalized evaluation is realistic?

This special session of ICDL will address the issues facing lifelong HRI including but not limited to the questions raised above. We will assemble a diverse group of researchers in and beyond robotics to explore the convergence of theories about human development, human-machine interfaces, machine learning, and robot engineering towards developing scalable autonomous robots.