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This paper is concerned with construction of a mathematical model for a class of lumped-parameter dynamics of a pair of robot fingers with soft and deformable tips pinching a rigid object. It is then shown that, in the case of a pair of planer fingers with two and three joints and a 2D rigid object with parallel or non-parallel flat surfaces, there exists a(More)
This paper proposes a method for controlling an object with parallel surfaces in a horizontal plane by a pair of finger robots. The control method can achieve stable grasping, relative orientation control, and relative position control of the grasped object. The control inputs require neither any object parameters nor any object sensing, such as tactile(More)
This study proposes a mathematical uncertainty model for the spatial measurement of visual features using Kinect™ sensors. This model can provide qualitative and quantitative analysis for the utilization of Kinect™ sensors as 3D perception sensors. In order to achieve this objective, we derived the propagation relationship of the uncertainties between the(More)
A mathematical model expressing motion of a pair of multi-DOF robot fingers with hemi-spherical ends grasping a 3-D rigid object with parallel flat surfaces is derived together with non-holonomic constraints. By referring to the fact that human grasp an object in the form of precision prehension dynamically and stably by opposable forces between the thumb(More)
This paper presents a development of an anthropomorphic robot hand, `KITECH Hand' that has 4 full-actuated fingers. Most robot hands have small size simultaneously many joints as compared with robot manipulators. Components of actuator, gear, and sensors used for building robots are not small and are expensive, and those make it difficult to build a small(More)
We propose an efficient and powerful alternative for adaptation of human motions to humanoid robots keeping the bipedal stability. For achieving a stable and robust whole body motion of humanoid robots, we design a biologically inspired control framework based on neural oscillators. Entrainments of neural oscillators play a key role to adapt the nervous(More)
This paper focuses on the Riemannian distance and its application to skilled-motion plannings for the system. The Riemannian distance from one pose to another and vice versa is defined as the minimum curve-length measured by the Riemannian metric based upon the system inertia matrix among all curves connecting the two poses. The minimum-length curve in this(More)
Recently, biologically inspired control approaches for robotic systems that involve the use of central pattern generators (CPGs) have been attracting considerable attention owing to the fact that most humans or animals move and walk easily without explicitly controlling their movements. Furthermore, they exhibit natural adaptive motions against unexpected(More)