[Reprint] Human-Robot Interaction
Personal service robots are predicted to be the next big thing in technology (e.g., Jones & Schmidlin, 2011). The term personal service robot refers to a type of robot that will assist people in myriad household activities, such as caring for the elderly, gardening, or even assisting children with their homework. Jones and Schmidlin (2011) examined the factors that need to be taken into consideration in the design of personal service robots.
For example, a personal service robot must be able to do the following:
- Understand users’ intentions and infer the ability of users to accomplish tasks (e.g., does a senior citizen want to get medicine from the cupboard, and, if so, can the senior citizen get the medicine without any help?).
- Determine the appropriate time to interrupt users (e.g., stopping a person on her way to work to inform her that a trivial task is complete may not be an appropriate time to intercede).
- Approach users in the appropriate direction (e. g., approaching from front or rear vs. left or right). This is based on the user group (e.g., women vs. men) and the circumstance (e.g., user is sitting vs. user is standing).
- Position itself at an appropriate distance from users. This distance is dependent on the users’ attitudes toward robots.
- Capture users’ attention by identifying receptive users, positioning itself appropriately, and speaking to users.
The physical appearance of a robot is another important element that designers need to take into account. Appearance plays a significant role in the capabilities that users perceive a robot to possess. For example, Lee, Lau, and Hong (2011) found that users expected more emotion and communication (e.g., speech) capabilities from human-like robots compared with machine-like robots.
Further, the appearance of a robot influenced the environment in which it is likely to be used. Specifically, human-like robots (which are expected to have more warmth) were preferred for social and service occupations that required interaction with humans compared with task-oriented occupations.
Like personal service robots, professional robots are becoming increasingly popular. These robots assist people with professional tasks in nonindustrial environments. For example, professional robots are used in urban search-and-rescue missions, with operators remotely in control. Designing robots for use in such complex environments brings a unique set of challenges.
For example, Jones, Johnson, and Schmidlin (2011) found that one of the problems involved with teleoperating urban search-and-rescue robots is that the robot gets stuck because operators lack the ability to accurately judge whether they could drive a robot through an aperture. In that situation, operators may have to jeopardize their lives to retrieve the robot.
The failure to make accurate judgment arises because driveability decisions are based solely on whether the robot is smaller or larger than the aperture and not on the ability to drive the robot through the aperture.
In summary, bear in mind the following points when designing your “R2D2”:
- A personal service robot must be able to infer the user’s intentions and desires; must determine whether the user is able to complete the task without assistance; needs to decide when to interrupt the user; has to approach and position itself at a suitable distance from the user; and needs to be able to engage the user.
- The appearance of robots should match users’ mental models. Humans expect human-like robots to have warmth capabilities (e.g., emotion, cognition) and prefer human-like robots in occupations requiring interactions with people. However, not all robots need to be human-like; machine-like robots are considered suitable for task-oriented, blue-collar occupations.
- Teleoperating a robot successfully through an aperture is dependent not only on the robot’s width but also on a safety margin that is associated with the operator’s control of the robot. Therefore, robots used in urban search-and rescue missions must be designed to account for the safety margin that operators fail to consider when making driveability judgments.
Jones, K. S., Johnson, B. R., & Schmidlin, E. A. (2011). Teleoperation through apertures: Passability versus driveability. Journal of Cognitive Engineering and Decision Making, 5, 10–28. http://edm.sagepub.com/ content/5/1/10.full.pdf+html.
Jones, K. S., & Schmidlin, E. A. (2011). Human-robot interaction: Toward usable personal service robots. In Reviews of Human Factors and Ergonomics (vol. 7, pp. 100–148). Santa Monica, CA: Human Factors and Ergonomics Society. http://rev.sagepub.com/ content/7/1/100.full.pdf+html.
Lee, S., Lau, I. Y., & Hong, Y. (2011). Effects of appearance and functions on likability and perceived occupational suitability of robots. Journal of Cognitive Engineering and Decision Making, 5, 232–250. http://edm.sagepub .com/content/5/2/232.full.pdf+html.