Industrial Applications of Informatics and Microsystems (IAIM)
Humanoid robotics is a new challenging field.To cooperate with human beings, humanoid robots not only have to feature human-like form and structure but, more importantly, they must possess human-like characteristics
regarding motion, communication and intelligence. In this paper, we propose an algorithm for solving the inverse kinematics problem associated with the redundant robot arm of the humanoid robot ARMAR. The formulation of the problem is based on the decomposition of the workspace of the arm and on the analytical description of the redundancy of the arm. The solution obtained is characterized by its accuracy and low cost of computation. The algorithm is enhanced in order to generate human-like manipulationmotions from object trajectories.
I. INTRODUCTION
From the mechanical point of view, a robot arm imitating the human arm motions should be kinematically redundant like the human arm. According to [1], the
human arm mechanism is composed of seven degrees of freedom (DOF) from the shoulder to the wrist. Because there is kinematic redundancy, an infinite number of joint angle trajectories leads to the same end-effector trajectory. Kinematics redundancy can be used to avoid joint limits [2], obstacles [3], and singular configurations [4],
as well as to provide a fault tolerant operation [5] or to optimize the robot arm dynamics [6]. Standard methods
that deal with redundancy can be divided in two global and local methodes [7]. The former require prior information
about the entire Cartesian space trajectory of the endeffector to generate, usually iteratively, a set of joint
angle trajectories with global optimality. Therefore, global control schemes are computationally expensive and not
suitable for real-time implementation. On the other hand, local methods use only the instantaneous position of the
end-effector to perform local optimization in real time. Therefore, local control schemes are required in case of
cooperation tasks between humans and humanoid robots. The use of redundancy for the generation of humanlike
robot arm motions has been already proposed in the literature and a variety of hypothetical cost functions
has been suggested to explain principles of the human arm movements [8]. In [9], for instance, the kinematic
redundancy is used to achieve human-like joint motions Fig. 1. The humanoid robot ARMAR
of a robot arm during the writing task. Recently, human motion capture has been used for the generation of
kinematics models describing human and humanoid robotmotions [10]. This method has been successfully applied to the generation of human-like motions of our humanoid robot ARMAR [11]. However, the applicability of this method to generate human-like manipulation motions is not yet clear from the literature. In this paper we consider the problem of generating human-like motions from the kinematics point of view.We rely on a hypothesis from neurophysiology and present its on-line application for generating human-like motions of
a redundant humanoid robot arm. The paper is organized as follows. Section II describes the kinematics of the 7- DOF arm of the humanoid robot ARMAR. The description of the arm redundancy and the algorithm for solving
the inverse kinematics problem is given in section III. Section IV presents the approach we use to generate
human-like motions. Finally section V summarizes the
results and concludes the paper.
