TY - GEN
T1 - Probability of love between robots and humans
AU - Samani, Hooman Aghaebrahimi
AU - Cheok, Adrian David
PY - 2010
Y1 - 2010
N2 - In order to develop a close relationship between humans and robots, we proposed a multi-modal sentimental model which considers both long and short term affective parameters of interaction. Our model is inspired from scientific studies of love in humans and aims to generate a bi-directional love between humans and robots. We refer to this sentimental connection as "Lovotics" . We have formulated probabilistic mathematical models for identified factors of love, and aim to provide a clear, distinct and discrete interpretation of the intimacy between humans and robots. Such mathematical models are assembled by a Bayesian Network depicting the relationship between intimacy and the causal factors for love. Furthermore, a novel affective state transition system is proposed which takes into account not only the current state caused by interactions, but also the effects of the previous states and internal factors of the robot. Hence, the robot is capable of acting consistently and naturally. The behavior of the robot is controlled by the above two modules via an Artificial Neural Network to develop a realistic affective communication between a human and a robot.
AB - In order to develop a close relationship between humans and robots, we proposed a multi-modal sentimental model which considers both long and short term affective parameters of interaction. Our model is inspired from scientific studies of love in humans and aims to generate a bi-directional love between humans and robots. We refer to this sentimental connection as "Lovotics" . We have formulated probabilistic mathematical models for identified factors of love, and aim to provide a clear, distinct and discrete interpretation of the intimacy between humans and robots. Such mathematical models are assembled by a Bayesian Network depicting the relationship between intimacy and the causal factors for love. Furthermore, a novel affective state transition system is proposed which takes into account not only the current state caused by interactions, but also the effects of the previous states and internal factors of the robot. Hence, the robot is capable of acting consistently and naturally. The behavior of the robot is controlled by the above two modules via an Artificial Neural Network to develop a realistic affective communication between a human and a robot.
UR - http://www.scopus.com/inward/record.url?scp=78651504102&partnerID=8YFLogxK
U2 - 10.1109/IROS.2010.5650886
DO - 10.1109/IROS.2010.5650886
M3 - Conference contribution
AN - SCOPUS:78651504102
SN - 9781424466757
T3 - IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings
SP - 5288
EP - 5293
BT - IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010 - Conference Proceedings
T2 - 23rd IEEE/RSJ 2010 International Conference on Intelligent Robots and Systems, IROS 2010
Y2 - 18 October 2010 through 22 October 2010
ER -