Babybot: a biologically inspired developing robotic agent

The study of development, either artificial or biological, can highlight the mechanisms underlying learning and adaptive behavior. We shall argue whether developmental studies might provide a different and potentially interesting perspective either on how to build an artificial adaptive agent, or on understanding how the brain solves sensory, motor, and cognitive tasks. It is our opinion that the acquisition of the proper behavior might indeed be facilitated because within an ecological context, the agent, its adaptive structure and the environment dynamically interact thus constraining the otherwise difficult learning problem. In very general terms we shall describe the proposed approach and supporting biological related facts. In order to further analyze these aspects from the modeling point of view, we shall demonstrate how a twelve degrees of freedom baby humanoid robot acquires orienting and reaching behaviors, and what advantages the proposed framework might offer. In particular, the experimental setup consists of five degrees-of-freedom (dof) robot head, and an off-the-shelf six dof robot manipulator, both mounted on a rotating base: i.e. the torso. From the sensory point of view, the robot is equipped with two space-variant cameras, an inertial sensor simulating the vestibular system, and proprioceptive information through motor encoders. The biological parallel is exploited at many implementation levels. It is worth mentioning, for example, the space- variant eyes, exploiting foveal and peripheral vision in a single arrangement, the inertial sensor providing efficient image stabilization (vestibulo-ocular reflex).

[1]  Giulio Sandini,et al.  An incremental growing neural network and its application to robot control , 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

[2]  C. Hofsten,et al.  Development of smooth pursuit tracking in young infants , 1997, Vision Research.

[3]  S. Lisberger Physiologic basis for motor learning in the vestibulo-ocular reflex , 1998, Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery.

[4]  Rodney A. Brooks,et al.  Behavior-based humanoid robotics , 1996, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS '96.

[5]  Giulio Sandini,et al.  Visuo-inertial stabilization in space-variant binocular systems , 2000, Robotics Auton. Syst..

[6]  G T Gdowski,et al.  Firing behavior of vestibular neurons during active and passive head movements: vestibulo-spinal and other non-eye-movement related neurons. , 1999, Journal of neurophysiology.

[7]  F. A. Miles,et al.  Adaptive plasticity in the vestibulo-ocular responses of the rhesus monkey. , 1974, Brain research.

[8]  Roger D. Quinn,et al.  A hydrostatic robot for marine applications , 2000, Robotics Auton. Syst..

[9]  Giulio Sandini,et al.  Oculo-motor stabilization reflexes: integration of inertial and visual information , 1998, Neural Networks.

[10]  Albert F. Fuchs,et al.  Development of conjugate human eye movements , 1988, Vision Research.

[11]  S. Lisberger The neural basis for motor learning in the vestibulo-ocular reflex in monkeys , 1988, Trends in Neurosciences.

[12]  Rolf Pfeifer,et al.  Sensory - motor coordination: The metaphor and beyond , 1997, Robotics Auton. Syst..

[13]  G Turkewitz,et al.  Limitations on input as a basis for neural organization and perceptual development: a preliminary theoretical statement. , 1982, Developmental psychobiology.

[14]  A. Fuchs,et al.  Infant eye movements: Quantification of the vestibulo-ocular reflex and visual-vestibular interactions , 1991, Vision Research.

[15]  T. Sejnowski,et al.  Irresistible environment meets immovable neurons , 1997, Behavioral and Brain Sciences.

[16]  R. Beer,et al.  Biorobotic approaches to the study of motor systems , 1998, Current Opinion in Neurobiology.

[17]  R. Carpenter,et al.  Movements of the Eyes , 1978 .

[18]  A van Opstal,et al.  A two-dimensional ensemble coding model for spatial-temporal transformation of saccades in monkey superior colliculus , 1993 .

[19]  Giulio Tononi,et al.  A robotic system emulating the adaptive orienting behavior of the barn owl , 1997, Proceedings of International Conference on Robotics and Automation.

[20]  T. Takenaka,et al.  The development of Honda humanoid robot , 1998, Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146).

[21]  Giulio Sandini,et al.  Learning VOR-like stabilization reflexes in robots , 2000, ESANN.

[22]  Giulio Sandini,et al.  Human Sensori-Motor Development and Artificial Systems , 1997 .

[23]  M. Goodale,et al.  The visual brain in action , 1995 .

[24]  Gordon Cheng,et al.  Complex continuous meaningful humanoid interaction: a multi sensory-cue based approach , 2000, Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065).

[25]  E Bizzi,et al.  The coordination of eye-head movements. , 1974, Scientific American.

[26]  Yasuo Kuniyoshi,et al.  Learning of oculo-motor control: a prelude to robotic imitation , 1996, Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems. IROS '96.