Who Should Attend

The intended audience is both novices and experts in quantitative and qualitative methods for capturing, designing, and developing human-robot interaction systems. This tutorial is appropriate for:

students and researchers in the engineering and computer science disciplines without prior experience in formal methods for HRI.
students and researchers in psychology and sociology who may be familiar with some or all the techniques but have limited experience applying their knowledge to robots

What You Will Learn

The deployment of land, sea and aerial robots into real-time, dynamic domains continues to expand. Additionally, the roles of the humans when interacting with robots continues to evolve and it becomes increasingly important to understand how the humans "behind" the robots and the robots "in front" of the robots need to interact with the robot. History has shown that defining system requirements and needs based upon feedback from actual or potential users is a critical factor when designing and developing technology. While there are a limited number of deployed robotic systems that are used on a regular basis by those not trained in robotics or engineering, the design of the human-robot interaction for robotic systems is a key usability factor that directly impacts users’ willingness to adopt the technology. Cognitive task analysis and cognitive work analysis techniques have been applied to a large number of domains outside of robotics in order to inform system design. These techniques have been employed infrequently in the field of robotics; however, such applications have resulted in valuable feedback that directly impacted human-robot interaction design.

Getting feedback from robotics users is particularly challenging as domains may either be normative or formative. In normative domains, the robot is expected to provide or meet existing task demands, e.g., replace humans or slightly modify how the task is currently done. In formative domains, the robot is being used to do tasks that have never been possible before and users may generate new applications on the fly.

This half-day, four hour tutorial will contain four primary components:

A comparison of cognitive task analysis and cognitive work analysis methods.
Data collection methods for these analysis methods that include experiments and observations "in the wild".
A review of cognitive task analysis methods and the presentation of real case studies.
A review of cognitive work analysis methods and the presentation of real case studies.

The tutorial will begin with a high level overview and comparison of cognitive task analysis and cognitive work analysis techniques. This portion of the tutorial will focus on the fundamental differences between the analysis methods, when to apply the different analysis methods, the analytical power achievable with the different analysis methods, and the type of information and results that can be provided by the analysis methods.

The second component of the tutorial focuses on data collection methods necessary for conducting this type of analysis and to validate the resulting models. In particular, this section will focus on sources of information and the associated advantages and disadvantages of the sources of information. Sources of information range from documentation and user logs to subject matter interviews, observations of real users in staged or full scale simulations, and direct observations during actual use. Based upon the organizers’ experience, real data collection examples and experiences will be provided. This portion of the tutorial will also cover processing and post-processing of the collected data.

The remaining two tutorial components will have a similar overall structure, while one component focuses solely on cognitive task analysis and the other focuses solely on cognitive work analysis. Both components will provide a more detailed overview of the associated analysis methods that includes the different types and variations to each overall method. For example, the cognitive task analysis component may focus on goal-directed task analysis, constraint task analysis [9] and hierarchical task analysis. Both components will also provide case studies that apply cognitive task analysis and cognitive work analysis to human-robot interaction domains and systems.

Cognitive task analysis results in models of the world and how work is completed in the world. Such models represent physical or intangible (e.g. software) things in the world and the relationships between the things in the world. Such analysis is intended to understand existing systems in order to understand what users need to achieve, how they achieve it, and why they need to achieve it.

Cognitive work analysis focuses on the analysis of human work based on device-independent constraints independent of worker competencies. Because it does not assume that the technology is replacing or substituting for an existing task or method, it is well suited for emerging domains.

How Do I Sign up or Get More Information?

This tutorial will be held in conjunction with the 2010 ACM/IEEE International Conference on Human Robot Interaction. Additional information pertaining to the conference and tutorials is available on the conference attendance website. The registration fee is $50 for this half-day tutorial and the registration can be completed at the conference registration website.

Organizers' Bios

Julie A. Adams

Dr. Julie A. Adams joined the faculty of the Electrical Engineering and Computer Science Department at Vanderbilt University in August 2003, founding the Human-Machine Teaming Laboratory at that time. Dr. Adams received her Ph.D. degree in Computer and Information Sciences in 1995 from the University of Pennsylvania, performing her research on human-robotic interaction for multi-robot systems in Penn's General Robotics, Automation, Sensing and Perception (GRASP) Laboratory. Dr. Adams has published over 50 articles in the areas of multiple robot coalition formation, human-robot interaction, human-computer interaction, and complex human-machine systems. She has received the NSF Career Award. She is an associate editor for the IEEE Transactions on Systems, Man and Cybernetics - Part A and serves on the editorial board of the Human Factors and Engineering in Manufacturing. Dr. Adams serves as a member of the National Research Council’s Army Research Laboratory Technical Assessment Review Panel on Solider Systems. Dr. Adams has served on several international conference organizing and program committees and is the co-chair of the Human-Robot Interaction Steering Committee.

Robin R. Murphy

Robin Roberson Murphy received a B.M.E. in mechanical engineering, a M.S. and Ph.D in computer science in 1980, 1989, and 1992, respectively, from Georgia Tech, where she was a Rockwell International Doctoral Fellow. She is the Raytheon Professor of Computer Science and Engineering at Texas A&M and Director of the Center for Robot-Assisted Search and Rescue. Her research interests are artificial intelligence, human-robot interaction, and heterogeneous teams of robots. She co-chaired the 2001 DARPA/NSF Study on Human-Robot Interaction, which is credited with bootstrap the community. In 2008, she was awarded the Al Aube Outstanding Contributor award by the AUVSI Foundation, for her insertion of ground, air, and sea robots for urban search and rescue (US&R) at the 9/11 World Trade Center disaster, Hurricanes Katrina and Charley, and the Crandall Canyon Utah mine collapse. In addition to participating and recording 11 disasters, she has observed over 20 full scale exercises and documented human-robot interaction in the rescue robotics community. She is a Distinguished Speaker for the IEEE Robotics and Automation Society, and has served on numerous boards, including the Defense Science Board, USAF SAB, NSF CISE Advisory Council, and DARPA ISAT.