  This technical report gives an overview of our work on control algorithms
dealing with redundant robot systems for achieving human-like motion
characteristics. Previously, we developed a novel control law to exhibit
human-motion characteristics in redundant robot arm systems as well as
arm-trunk systems for reaching tasks [1], [2]. This newly developed method
nullifies the need for the computation of pseudo-inverse of Jacobian while the
formulation and optimization of any artificial performance index is not
necessary. The time-varying properties of the muscle stiffness and damping as
well as the low-pass filter characteristics of human muscles have been modeled
by the proposed control law to generate human-motion characteristics for
reaching motion like quasi-straight line trajectory of the end-effector and
symmetric bell shaped velocity profile. This report focuses on the experiments
performed using a 7-DOF redundant robot-arm system which proved the
effectiveness of this algorithm in imitating human-like motion characteristics.
In addition, we extended this algorithm to a 19-DOF Hand-Arm System for a
reach-to-grasp task. Simulations using the 19-DOF Hand-Arm System show the
effectiveness of the proposed scheme for effective human-like hand-arm
coordination in reach-to-grasp tasks for pinch and envelope grasps on objects
of different shapes such as a box, a cylinder, and a sphere.
