To execute visually guided reaching movements, the central nervous system (CNS) must transform a desired hand trajectory (kinematics) into appropriate muscle-related commands (dynamics). It has been suggested that the CNS might face this challenging computation by using internal forward models for the dynamics. Previous work in humans found that new internal models can be acquired through exper...

In this chapter, a Recurrent Higher Order Neural Network (RHONN) is used to identify the plant model of discrete time nonlinear systems, under the assumption that all the state is available for measurement. Then the Extended Kalman Filter (EKF) is used to train the RHONN. The applicability of this scheme is illustrated by identification for an electrically driven nonholonomic mobile robot. Trad...

Recently, fast and practical inverse kinematics (IK) methods for complicated human models have gained considerable interest owing to the spread of convenient motion-capture or human-augmentation technologies. Although IK algorithms developed in robotics can also be applied humans, they experience computational speed issues, especially real-time applications. This paper presents a new algorithm ...

All axisymmetric self-similar equilibria of self-gravitating, rotating, isothermal systems are identified by solving the nonlinear Poisson equation analytically. There are two families of equilibria: (1) Cylindrically symmetric solutions in which the density varies with cylindrical radius as R, with 0 ≤ α ≤ 2. (2) Axially symmetric solutions in which the density varies as f(θ)/r, where r is the...

We present a combined analysis of the kinematics of the Large Magellanic Cloud through its H I gas, carbon stars, and red supergiant stars. After correcting the line-of-sight velocities for the recent accurate measurement of the LMC’s space motion, we find that each kinematic tracer clearly defines a flat rotation curve with similar shape but different amplitude for each tracer: 61 km s for the...

This paper presents a novel unified theoretical framework for differential kinematics and dynamics for complex robot motion optimization. By introducing 18×18 comprehensive motion transformation matrix (CMTM), forward differential kinematics and dynamics including velocity and acceleration can be written in a simple chain product like ordinary rotational matrix. This formulation enables analyti...