The Anticipation of Human Behavior Using "Parasitic Humanoid"

This paper proposes the concept of Parasitic Humanoid (PH) that can realize a wearable robot to establish intuitive interactions with wearers rather than conventional counter-intuitive ways like key-typing. It requires a different paradigm or interface technology which is called behavioral or ambient interface that can harmonize human-environment interactions to naturally lead to a more suitable state with the integration of information science and biologically inspired technology. We re-examine the use of wearable computers or devices from the viewpoint of behavioral information. Then, a possible way to realize PH is shown as integrated wearable interface devices. In order that PH establishes the harmonic interaction with wearers, a mutually anticipated interaction between a computer and human is necessary. To establish the harmonic interaction, we investigate the social interaction by experiments of human interactions where inputs and outputs of subjects are restricted in a low dimension at the behavioral level. The results of experiments are discussed with the attractor superimposition. Finally, we will discuss integrated PH system for human supports.

[1]  W. Prinz,et al.  The imitative mind : development, evolution, and brain bases , 2002 .

[2]  Kunihiko Kaneko,et al.  A Generic Mechanism for Adaptive Growth Rate Regulation , 2007, PLoS Comput. Biol..

[3]  David W. Murray,et al.  Wearable Visual Robots , 2000, Digest of Papers. Fourth International Symposium on Wearable Computers.

[4]  J. Nadel The Imitative Mind: Imitation and imitation recognition: Functional use in preverbal infants and nonverbal children with autism , 2002 .

[5]  John Hallam,et al.  From Animals to Animats 10 , 2008 .

[6]  Kerstin Dautenhahn,et al.  Robots as embodied beings - interactionally sensitive body movements in interactions among autistic children and a robot , 2005, ROMAN 2005. IEEE International Workshop on Robot and Human Interactive Communication, 2005..

[7]  Gentaro Taga,et al.  A model of the neuro-musculo-skeletal system for human locomotion , 1995, Biological Cybernetics.

[8]  B. Scassellati Imitation and mechanisms of joint attention: a developmental structure for building social skills on a humanoid robot , 1999 .

[9]  K. Kaneko,et al.  Adaptive Response of a Gene Network to Environmental Changes by Fitness-Induced Attractor Selection , 2006, PloS one.

[10]  Chrystopher L. Nehaniv Computation for Metaphors, Analogy, and Agents , 2000, Lecture Notes in Computer Science.

[11]  N. Fox,et al.  Social perception in infants , 1985 .

[12]  Ezequiel A. Di Paolo,et al.  Behavioral Coordination, Structural Congruence and Entrainment in a Simulation of Acoustically Coupled Agents , 2000, Adapt. Behav..

[13]  Kazufumi Hosoda,et al.  Synthetic ecosystem of Escherichia coli for discovery of novel cooperative and self-adaptive algorithms , 2008, BIONETICS.

[14]  Pattie Maes,et al.  Toward the Evolution of Dynamical Neural Networks for Minimally Cognitive Behavior , 1996 .

[15]  T. Maeda,et al.  Tele-existence simulator with artificial reality (1)- design and evaluation of a binocular visual display using solid models- , 1988, IEEE International Workshop on Intelligent Robots.

[16]  R. S. Johansson,et al.  Roles of glabrous skin receptors and sensorimotor memory in automatic control of precision grip when lifting rougher or more slippery objects , 2004, Experimental Brain Research.

[17]  Kenji Leibnitz,et al.  Biologically inspired self-adaptive multi-path routing in overlay networks , 2006, Commun. ACM.

[18]  Hiroyuki Iizuka,et al.  Adaptability and Diversity in Simulated Turn-taking Behavior , 2003, Artificial Life.

[19]  Hideyuki Ando,et al.  SmartFinger: nail-mounted tactile display , 2002, SIGGRAPH '02.

[20]  J. Nadel,et al.  Expectancies for social contingency in 2‐month‐olds , 1999 .

[21]  H. Harry Asada,et al.  Distributed Photo-Plethysmograph Fingernail Sensors: Finger Force Measurement Without Haptic Obstruction , 1999, Dynamic Systems and Control.