Scope/Topics of Interest

It is our dream to understand principles of animals' surprising abilities in adaptive motion and to transfer such abilities on a robot. However, principles of adaptation to various environments have not yet been clarified, and autonomous adaptation is left unsolved as seriously difficult problem in robotics. Apparently, the adaptation ability shown by animals and needed by robots in a real world can not be explained or realized by one single function in control system and mechanism. That is, adaptation in motion is induced at every level in a wide spectrum from central neural system to musculoskeletal system.

We are organizing AMAM2003 for scientists and engineers concerned with adaptation on various levels to be brought in contact, to discuss on principles on each level and to investigate principles governing total systems.

Some topics of particular interest to guide prospective contributors are:

+ Visual Adaptation Mechanisms of Systems in Locomotion
+ Sensory-Motor Coordination in Locomotion
+ Locomotion of Primates
+ Embodied Intelligence in Locomotion
+ Learning Methods for Adaptive Motion
+ Neuro-Mechanics
+ Adaptive Locomotion 
+ Non-linear Dynamics in Locomotion    
+ Adaptive Mechanics                          
+ Modeling and Analysis of Motion
+ Behavior and Motion of Humans and Humanoids
+ Prosthesis, Hemiparesis and Rehabilitation
+ Evolution for Adaptive Motion
+ Technical Development of Mechanism and Control for Adaptive Motion

In this symposium, each role of skeleton(mechanism), muscle(actuator) and ervous(control) system in adaptive motion and relations between them will be discussed. Of couse, nervous system includes low level (generatin and control at spinal cord), medium level (adaptation at cerebellum), and high level (adaptation at cerebrum).

Papers should focus on principles of adaptive motion. But new ideas engineeringly proposed are also of great interest. The comparison and competition between biologically inspired methods and engineeringly derived methods in view of ability and complexity in adaptation is important for the future development of novel machines.