[ 2] Nielsen, J. and R.L. Mack eds., Heuristic evaluation, Usability Inspection Methods, New York: John Wiley & Sons, 1994. Available at http://www.useit.com/ jakob/ inspectbook.html

[ 3] Shneiderman, B. Designing the User Interface: Strategies for Effective Human-Computer Interaction, Boston: Addison Wesley, 1997. Available at http://www.cs.umd. edu/hcil/pubs/books/ dtui.shtml

[ 4] Scholtz, J. “Evaluation Methods for Human-System Performance of Intelligent Systems,” Proceedings of the 2002 Performance Metrics for Intelligent Systems Workshop (PerMIS), Gaithersburg, MD, 2002. Available at http://www.isd.cme.nist. gov/research_areas/ research_engineering/ Performance_Metrics/ PerMIS_2002_ Proceedings/Scholtz. pdf

March + April 2008

[ 5] Jenson, Scott, The Simplicity Shift, Cambridge University Press, 2002.

of the robot, and the robot will drive forward toward the dot.

We organized the large list of “stories” into several areas, and we found four key areas where there are many challenges in HRI—these are the areas that we will focus on improving for next-generation HRI.

Situational Awareness.

Especially during teleoperation, users need to know the internal states of the robot, the robot’s position in the environment, and the environment. For example, good cameras help users understand the robot’s position and state.

Robot Control and Movement.

Robots are capable of complex movements, and it is important to be able to clearly and effectively command the robot to do what you want it to do. For example, controls to drive the robot and move its arm need to be flexible enough to complete the task, while remaining accessible for human operators.

Controller/UI. Teleoperated robots follow a client/server model in which the controller interface is a client that can operate independently of the robot. This area has many of its own challenges, like ergonomics, because the operator is working separately from the robot itself.

Communications. Communications between the controller and the robot create limits on the robot’s behavior, such as how far away you can send the robot.

Using these stories as a basis for our future work, we’ve looked at HCI and HRI theories and defined a list of key HCI/ HRI principles to focus on. This list of “heuristics” was developed from three core sources: Jakob Nielsen’s classic list of

usability heuristics [ 2], Ben Schneiderman’s core principles [ 3], and Jean Scholtz’s methods for evaluation of intelligent systems [ 4]. Certainly, this is an untested, initial list—there is room for research in this area.

Many of these principles are not unique to HRI, but their relative value of weighting is slightly different from other HCI communities. During our evaluations, we found the most space for improvement in the areas of “required information should be present and clear,” “prevent errors if possible, if not, help users diagnose and recover,” and “use metaphors and language the users already know.” That’s why these three are on the top of the list.

Sholtz’s work on intelligent systems adds a new spin to some of these universal HCI principles in the context of HRI.

“Design should be aesthetic and minimalist” has been the most important interaction design principle used in iRobot’s projects intended for use in homes, like the Roomba. Since Roomba is a consumer product, a simple user interface keeps the cost of the robot down while keeping its operation simple. As the product matures, the Roomba team is taking on a broader ethnographic approach, including more in-home studies.

Sholtz also suggests that HRI developers “make the architecture scalable” and “support evolution of platforms,” because robotics is still an immature medium and the robots are often required to do much more than they were designed for. In short, if you don’t make it easy for the system to grow, it will be outdated very soon.