ROBOT WORKSPACE OPTIMIZATION USING A NOVEL MODIFIED DIFFERENTIAL EVOLUTIONARY TECHNIQUE

Robotic manipulators with three-revolute (3R) family of positional configurations are very common in the industrial robots (IRs). The capability of a robot largely depends on the workspace (WS) of the manipulator apart from other parameters. With the constraints in mind, the optimization of the workspace is of prime importance in designing the manipulator. The problem is formulated as a constrained optimization problem with workspace volume as objective function. It is observed that the previous literature is confined to use of conventional soft computing algorithms only, while a new search algorithm is conceptualized and proposed to improve the computational time. The proposed algorithm differs from the conventional differential evolutionary (DE) algorithm only in the place of initialization and selection. The algorithm gives a good set of geometric parameters of manipulator within the applied constrained limits. The availability of such an algorithm for optimizing the workspace is important, especially for highly constrained environments. The efficiency of the proposed approach to optimize the workspace of 3R manipulators is exhibited through diverse cases.