This paper studies a sensory-motor control mechanism of human's reaching movements from the perspective of robotics aspect. By formulating the musculo-skeletal redundant system which takes into account a nonlinear muscle property obtained by some physiological understandings, we suggest that the human-like reaching movements can be realized by using only simple task-space feedback scheme together with the internal force effect which comes from mechanical property of muscles without any complex mathematical computation such as an inverse dynamics or some optimal trajectory derivation. Firstly, we introduce both kinematics and dynamics of a three-link serial manipulator with six single-joint muscles and three double-joint muscles model whose movements are confined within a horizontal plane. Secondly, the nonlinear muscle property, which comes from several physiological understandings based on Hill's muscle model, is taken into consideration and illustrated by some numerical simulations that the end-point of the manipulator can converge to the desired point smoothly using only simple task-space feedback scheme by considering the muscle property and internal forces induced by the redundancy of muscles, which makes it possible to modulate the damping factors in joint-space, even if the system owns both kinematic and dynamic redundancies. Then we discuss the effectiveness of our control scheme, and suggest it as one direction to study brain-motor control mechanism of human movements.
Recently, novel information processing mechanisms inspired by biological immune system are proposed and showed better capability than Neural Network and Genetic Algorithm. Biological immune system consists of high information processing mechanisms such as diverse antibody production mechanisms, self-regulating mechanism and primary and secondary immune responses based on antigen's specificity and immunological memory. Immune Algorithm (IA) based on this biological immune system can obtain multi optimal solutions without the constraint. However, in order to require very much computational time, it is not suitable for the actual problems. Therefore, the dedicated hardware is important in order to apply IA to actual problems. In this paper, we proposed Immune Algorithm processor for nurse scheduling problem. The proposed architecture is realized parallel processing on the calculation for affinity degree. Furthermore, the architecture is proposed not only the pipeline at evaluation phase, but also the pipeline on the whole at reconstruction phase. Experiment result evaluating the proposed architecture was shown to achieve more than 20 times the speed keeping the scheduling quality compared with software processing.
It is found from the locomotion of snake-like underwater robot using Ionic Polymer-Metal Composite (IPMC) as its actuator that, although we specify the same amplitude of driven voltages to each segmented IPMC unit, the resultant bending amplitudes along the body's progressive waves change from small to large toward the robot's tail. To analyze this phenomenon, which is also observed in locomotions of slender fishes, we discuss the modeling and analysis of bending motions of IPMC actuators using the Euler-Bernoulli beam theory. Eigenfunction expansion technique is used to solve the model of a partial differential equation. The envelope curve can be drawn by the obtained solution, and simulation results reappear the same phenomenon. Deflection of the real robot is measured by video camera and laser beam. Experimental results verifies the validity of the proposed model. Parameter identification is also performed with measured data.