| Summary: | The optimal kinematic design of robots is an interesting problem in contemporary
robotics. It is important to have measures for determining the precision of the mechanism
and size of the robot manipulator at the design phase. This all has been done before
mostly on the basis of experience. The most essential issue for setting up any measures
seems to be the ease of changing arbitrarily the position and orientation of the end-effector
at the tip of the manipulator.
In the majority of recent works on optimal robot design, one of the most important
criteria is that the robot can achieve isotropic configurations. The operation near isotropic
configuration is considered as a high performance for robotic manipulators. At these
configurations, the best servo accuracy can be achieved, the likelihood of error is equal in
all directions, and equal forces may be exerted in all directions [29].
A measure of isotropy called the Global Isotropy Index or GII [49] has been used in this
work, which is based on the robot behavior in the entire workspace. The GII is computed
as the ratio of the minimum singular value of a robot's Jacobian matrix to the maximum
one throughout its workspace. In search for finding the optimum design parameters that
provide the most isotropic performance, the positions that offer the minimum ratio of
singular values for each set of design parameters are compared to each other to find the
maximum one. This strategy illustrates in fact a minimax optimization problem.
A "Genetic Algorithm" has been developed to optimize the minimax problem in order to
find optimal design parameters such as link lengths of the best isotropic robot
configurations at optimal working points of the end-effector and later, it has been
implemented to optimize globally throughout the whole robot workspace. The method
has been demonstrated for two types of robotic manipulators. === Applied Science, Faculty of === Mechanical Engineering, Department of === Graduate
|
|---|
