Abstract
Reduced workspace is the main parallel robot disadvantage. It is generally due to the robot configuration, mainly the platform orientation constraint, the present work intends to find the maximum sphere within the orientation workspace, i.e., the singularity-free orientation regions. These regions are related to the platform orientation through Roll-Pitch-Yaw angles. Therefore, an optimization genetic algorithm is used to determine the initial platform orientation corresponding to the largest sphere volume. In this algorithm, the geometrical parameters and the direct and inverse singularities are the optimization constraints. The geometrical constraints may be studied using vectorial analysis. The reciprocity property from screw theory is implemented to analyze the direct and inverse kinematic. In this work it is used a methodology to verify the singularity closeness measure associated with direct kinematic. This measure is related to the rate of work done by each leg upon the platform twist. To determine how close is the parallel robot to a direct singularity a index value is proposed. It is considered that the passive joints reachable regions may be limited by a cone, whereby the cone symmetric axis is the same than the passive joint axis. In the optimization problem, the sphere volume, i.e., the maximal angular displacement of the moving platform around any axis is the objective function. Thus, the genetic algorithm individuals explore all feasible regions looking for an optimal solution.
Highlights
According to their structural topology, a parallel robot consists of two platforms, connected through serial kinematic chains [1]
The parallel robot orientation-workspace is reduced if it is compared with the serial robot orientation workspace
The main contribution of this work is to develop an optimization algorithm to establish the initial platform orientations, where the platform achieves a higher rotation in all directions
Summary
According to their structural topology, a parallel robot consists of two platforms (fixed and moving), connected through serial (open-loops) kinematic chains [1]. The optimization algorithm explores all feasible parallel robot configurations to find the optimal solution In this optimization problem the kinematics singularities are the constraints, while the geometrical parameters are the input data to calculate the optimal singularity-free cylindrical workspace and to determine continuous singularity-free zones. In [14], an algorithm is developed to detect the optimal singularity-free cylindrical workspace ranging from an initial orientation angle in platform to any prescribed orientation In this case, the algorithm is implemented in a 3-RPR planar robot, using robot structural parameters as constraints. The first are associated with platform orientation and the second to the parallel robot physical parameters These constraints are considered the workspace boundaries which are analyzed in Section 4 to describe the feasible regions related to the platform orientations.
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