In this work we research the role of body dynamics in the complexity of kinematic patterns in a quadruped robot with compliant legs. Two gait patterns, lateral sequence walk and trot, along with leg length control patterns of different complexity were implemented in a modular, feed-forward locomotion controller. The controller was tested on a small, quadruped robot with compliant, segmented leg...

This paper deals with the kinematic synthesis of manipulator. A new method based on distributed solving is used to determine the dimensional parameters of a general manipulator which is able to reach a set of given tasks speciied by orientation and position. First, a general Distributed Solving Method (DSM) is presented in three steps : the problem statement, the objective functions formulation...

In this paper‎, ‎an efficient dropping criterion has been used to compute the IUL factorization obtained from Backward Factored APproximate INVerse (BFAPINV) and ILU factorization obtained from Forward Factored APproximate INVerse (FFAPINV) algorithms‎. ‎We use different drop tolerance parameters to compute the preconditioners‎. ‎To study the effect of such a dropping on the quality of the ILU ...

In multibody mechanics, the motion analysis for a platform (the kinematics problem) can be classified into two cases: the forward kinematics and the inverse kinematics problems. For the forward kinematics problem, the trajectory of a point on a mechanism (for example, the end effector of a robot arm or the center of a platform support by a parallel link manipulator) is computed as a function of...

This paper proposes a classification of three-revolute orthogonal manipulators that have at least one of their DH parameters equal to zero. This classification is based on the topology of their workspace. The workspace is characterized in a half-cross section by the singular curves. The workspace topology is defined by the number of cusps and nodes that appear on these singular curves. The mani...

The emergence of the theory of dynamic neural computing has made it possible to develop neural learning and adaptive schemes that can be used to obtain feasible solutions to complex control problems, such as inverse kinematic control for robotic systems. In this paper, such a neural learning scheme using a multilayered dynamic neural network (MDNN) is proposed. The basic dynamic computing eleme...