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Bar-Cohen : Biomimetics: Biologically Inspired Technologies DK3163_c016 Final Proof page 403 21.9.2005 11:49pm

Biomimetic and Biologically Inspired Control 403

16.2.1 Nonlinear and Redundant Sensory-Motor Organization

Even simple reaching movements that can be performed by a 5-month-old baby are never simple in
cybernetics. At least, it requires solving several nonlinear coordination transformations from the
object space to the muscle space. The transformations may also contain the problem of redundancy.
Figure 16.1 shows a 3D computer simulation model of whole body dynamic musculo-skeletal
system of human developed in RIKEN BMC. As seen from this model, in order to realize the
natural human motions, it is necessary to control more than 105 D.O.F by over 300 muscles. Figure
16.2 shows another research example on how to control the 3 D.O.F. position of an object by whole
arm cooperative manipulation under the influence from the external forces. Here, each arm has 4
D.O.F. and interacts with the object by all links not the end-effectors. Human body is such a super-
redundant system, and the redundancy exists in a lot of levels of the motor coordinates. The inverse
solution of the redundancy problem generally forms a solution manifold in the motor control space,
the solution is not unique and thus is not easy to define. Therefore, although the redundant D.O.F.
provides the biological system with powerful hardware foundation to realize various smooth and
delicate motions that have high tolerance (fault-tolerance to the functional disability in some
parts of the system) and adaptability (adapt to the environmental uncertainties, variations, and
different objectives), in order to enjoy these benefits, during organizing the sensory-motor coord-
ination, we have to overcome the ill-posed nonlinear problems. These problems come not only from
the kinematics but also from the dynamics. By now, there are many researches proposed from the
viewpoints of robotic engineering as well as biologically inspired learning theory. The proposed
approaches can be largely summarized as: (1) learning approach based on neural network; and (2)
Jacobian approach from robotic engineering.

Figure 16.1 (See color insert following page 302) A 3D computer simulation model of whole body human
dynamic musculo-skeletal system.