{"id":1282,"date":"2015-07-17T08:54:10","date_gmt":"2015-07-17T06:54:10","guid":{"rendered":"http:\/\/visilab.etsii.uclm.es\/?page_id=1282"},"modified":"2015-07-21T09:39:19","modified_gmt":"2015-07-21T07:39:19","slug":"casimiro-an-engineering-approach-to-sociable-robots","status":"publish","type":"page","link":"http:\/\/visilab.etsii.uclm.es\/?page_id=1282","title":{"rendered":"CASIMIRO: AN ENGINEERING APPROACH TO SOCIABLE ROBOTS"},"content":{"rendered":"

CASIMIRO: AN ENGINEERING APPROACH TO SOCIABLE ROBOTS<\/h1>\n

Oscar Deniz Suarez
\nUniversidad de Las Palmas de Gran Canaria<\/p>\n\n\n\n
\"CASIMIRO\"<\/td>\n\"Cabeza<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

A relatively new area for robotics research is the design of robots that can engage with humans in socially interactive situations. These robots have expressive power (i.e. they all have an expressive face, voice, etc.) as well as abilities to locate, pay attention to, and address people. In humans, these abilities fall within the ambit of what has been called \u00absocial intelligence\u00bb. For this class of robots, the dominant design approach has been that of following models taken from human sciences like developmental psychology, ethology and even neurophysiology.<\/p>\n

We show that the reproduction of social intelligence, as opposed to other types of human abilities, may lead to fragile performance, in the sense of having very different performances between training\/testing and future (unseen) conditions. This limitation stems from the fact that the abilities of the social spectrum, which appear earlier in life, are mainly unconscious to us. This is in contrast with other human tasks that we carry out using conscious effort, and for which we can easily conceive algorithms. Thus, a coherent explanation is also given for the truism that says that anything that is easy for us is hard for robots and vice versa.<\/p>\n

For some types of robots like manipulators one can extract a set of equations (or algorithms, representations,…) that are known to be valid for solving the task. Once that these equations are stored in the control computer the manipulator will always move to desired points. Sociable robots, however, will require a much more inductive development effort. That is, the designer tests implementations in a set of cases and hopes that the performance will be equally good for unseen (future) cases. Inductive processes crucially depend on a priori knowledge: if there is little available one can have good performance in test cases but poor performance in unseen cases (overfitting).<\/p>\n

In Machine Learning, complexity penalization is often used as a principled means to avoid overfitting. Thus, we propose to develop sociable robots starting from simple algorithms and representations.
\nImplementations should evolve mainly through extensive testing in the robot niche (the particular environment and restrictions imposed on the robot tasks, physical body, etc.). Such approach places more emphasis in the engineering decisions taken throughout the robot development process, which depend very much on the niche.<\/p>\n

This work describes the ideas and techniques involved in the design and development of CASIMIRO, a robot with a set of basic interaction abilities. The robot has been built following the mentioned approach. In particular, the main difficulties lay in parsimoniously exploiting the characteristics of the robot niche in order to obtain better performances.<\/p>\n