| Many years of Human Factors research have shown that the development of effective, efficient, and usable interfaces requires the inclusion of the user’s perspective throughout the entire design and development process. [Unfortunately] Human-Robot Interface development tends to be an after thought, as researchers approach the problem from an engineering perspective. Such a perspective implies that the interface is designed and developed after the majority of the robotic system design has been completed. The goal of this line of research is to develop robotic systems usable for humans. |
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A user interface provides the means by which humans and machines interact. Another term for user interface is a man-machine interface (MMI). The MMI includes all the components that the user encounters. The components include the input language, output language and interaction protocol. The term ”human-computer interaction” was adopted in the mid-1980’s, and it describes a field of study that deals with all aspects of interaction between participants and computers. Human-Computer Interaction (HCI) is defined by the Association for Computing Machinery (ACM) Special Interest Group on Computer-Human Interaction (SIGCHI) as ”a discipline concerned with the design, evaluation, and implementation of interactive computing systems for human use and with the study of the major phenomenon surrounding them”. |
Initially, human-robot interfaces began in the form of robotic-arms tele-operation, limited by the lack of sensing and intelligence; in this first stage, the robot was just seen as an extension of the operator body. As computational capabilities increased, research advances were made in sensing, artificial intelligence, computer graphics, etc. This drastically changed the HRI system, from a master-slave system to collaborative systems. Such an HRI system should improve the mission or task results because it benefits from the capabilities of the artificial agent and the human. This system should bring four advantages to the simple master-slave telesystem:
- Improve both the speed and quality of the operator’s problem-solving performance;
- reduce cognitive fatigue by managing the presentation of information;
- maintain low communication bandwidths associated with semi-autonomous control by requesting only the relevant sensory data from the remote;
- improve efficiency by reducing the need for supervision so that the operator can perform other tasks; and
- support the incremental evolution of telesystems to full autonomy
