Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/30260
Title: Lovotics: Love + Robotics, Sentimental Robot With Affective Artificial Intelligence
Authors: HOOMAN AGHAEBRAHIMI SAMANI
Keywords: Lovotics, Robotics, Artificial Intelligence, Human - Robot Interaction, Social robot, Affective Computing
Issue Date: 28-Jul-2011
Source: HOOMAN AGHAEBRAHIMI SAMANI (2011-07-28). Lovotics: Love + Robotics, Sentimental Robot With Affective Artificial Intelligence. ScholarBank@NUS Repository.
Abstract: Lovotics refers to the research of human - robot relationship. The general idea of Lovotics is to develop a robotic system which strives to achieve a high level of attachment between humans and robot by exploring human love. Such relationship is a contingent process of attraction, affection, and attachment from humans towards robots and the belief of the vice versa from robots to humans. The first step in Lovotics is to develop a deep understanding of the physics, physiology, and emotions of the human being in order to model this in the robot. Even though various fields have proposed ideas about the role and function of love, the current understanding about love is still quite limited. Furthermore, developing an affection system similar to that of the human being presents considerable technological challenges. A robot was designed and developed using several design theories for the hardware and various novel algorithms for the software. The artificial intelligence of the robot employs probabilistic mathematical models for the formulation of love. An artificial endocrine system is implemented in the robot by imitating human endocrine functionalities. Thus, the robot has the capability of experiencing complex and human-like biological and emotional states as governed by the artificial hormones within its system. The robot goes through various affective states during the interaction with the user. It also builds a database of interacting users and keeps the record of the previous interactions and degree of love. The novel advanced artificial intelligence system of Lovotics includes an Artificial Endocrine System (AES), based on physiology of love, Probabilistic Love Assembly (PLA), based on psychology of love, and Affective State Transition (AST), based on emotions, modules. Psychological unit of the Lovotics artificial intelligence calculates probabilistic parameters of love between humans and the robot. Various parameters such as proximity, propinquity, repeated exposure, similarity, desirability, attachment, reciprocal liking, satisfaction, privacy, chronemics, attraction, form, and mirroring are taken into consideration. Physiological unit of the Lovotics artificial intelligence employs artificial endocrine system consisting of artificial emotional and biological hormones. Artificial emotional hormones include Dopamine, Serotonin, Endorphin, and Oxytocin. For biological hormones Melatonin, Norepinephrine, Epinephrine, Orexin, Ghrelin, and Leptin hormones are employed which modulate biological parameters such as blood glucose, body temperature and appetite. A wealth of information about a person?s emotions and state of mind can be drawn from facial expressions, voice, gesture, etc. The affective system of the robot analyzes system inputs to generate suitable states and behaviors for the robot in real-time. The affective system is modeled as closely to the human being as possible in order to be an emotionally engaging system. The robot is an active participant in the communication process and adjusts its internal affective states depending on inputs and feedback from the human. Based on love measurement methods for humans, a novel method for measuring human - robot love is proposed. This method is employed in order to evaluate the performance of Lovotics robot. Two possible further applications of Lovotics of Lovotics are also proposed, which are kissing transfer system and leader robots. Also ethical issues of Lovotics are also discussed.
URI: http://scholarbank.nus.edu.sg/handle/10635/30260
Appears in Collections:Ph.D Theses (Open)

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